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  • Editorial A Message From the Editor-in-Chief
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2020-02-14
    Tolga M. Duman

    I took over as the Editor-in-Chief (EiC) of IEEE Transactions on Communications (TCOM) exactly one month ago, on January 1, 2020. First of all, I would like to state that I am deeply honored and excited to serve as the new EiC. I have been closely involved with TCOM since 2007, both as an Editor and an Area Editor, and I am delighted that I now have the opportunity to lead the Transactions.

    更新日期:2020-02-18
  • Prefix-Free Code Distribution Matching for Probabilistic Constellation Shaping
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-06-25
    Junho Cho

    In this paper, we construct variable-length prefix-free codes that are optimal (or near-optimal) in the sense that no (or few) other codes of the same cardinality can achieve a smaller expected energy per code symbol for the same resolution rate. Under stringent constraints of 4096 codewords or below per codebook, the constructed codes yield an energy per code symbol within a few tenths of a dB of the unconstrained theoretic lower bound, across a wide range of resolution rates with fine granularity. We also propose a framing method that allows variable-length codes to be transmitted using a fixed-length frame. The penalty caused by framing is studied using simulations and analysis, showing that the energy per code symbol is kept within 0.3 dB of the unconstrained theoretic limit for some tested codes with a large frame length. When the proposed method is used to implement probabilistic constellation shaping for communications in the additive white Gaussian noise channel, simulations show that between 0.21 dB and 0.98 dB of shaping gains are achieved relative to uniform 4-, 8-, 16-, and 32-ary quadrature amplitude modulation.

    更新日期:2020-02-18
  • Performance Bounds and Estimates for Quantized LDPC Decoders
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-13
    Homayoon Hatami; David G. M. Mitchell; Daniel J. Costello; Thomas E. Fuja

    The performance of low-density parity-check (LDPC) codes at high signal-to-noise ratios (SNRs) is known to be limited by the presence of certain sub-graphs that exist in the Tanner graph representation of the code, for example trapping sets and absorbing sets. This paper derives a lower bound on the frame error rate (FER) of any LDPC code containing a given problematic sub-graph, assuming a particular message passing decoder and decoder quantization. A crucial aspect of the lower bound is that it is code-independent, in the sense that it can be derived based only on a problematic sub-graph and then applied to any code containing it. Due to the complexity of evaluating the exact bound, assumptions are proposed to approximate it, from which we can estimate decoder performance. Simulated results obtained for both the quantized sum-product algorithm (SPA) and the quantized min-sum algorithm (MSA) are shown to be consistent with the approximate bound and the corresponding performance estimates. Different classes of LDPC codes, including both structured and randomly constructed codes, are used to demonstrate the robustness of the approach.

    更新日期:2020-02-18
  • Construction of QC LDPC Codes With Low Error Floor by Efficient Systematic Search and Elimination of Trapping Sets
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-14
    Bashirreza Karimi; Amir H. Banihashemi

    We propose a systematic design of protograph-based quasi-cyclic (QC) low-density parity-check (LDPC) codes with low error floor. We first characterize the trapping sets of such codes and demonstrate, using edge coloring techniques, that the QC structure of the code eliminates some of the trapping set structures that can exist in a code with the same degree distribution and girth but lacking the QC structure. Based on this characterization, our design aims at eliminating a targeted collection of trapping sets. Considering the parent/child relationship between the trapping sets in the collection, we search for and eliminate those trapping sets that are in the collection but are not a child of any other trapping set in the collection. An efficient layered algorithm is designed for the search of these targeted trapping sets. Compared to the existing codes in the literature, the designed codes are superior in the sense that they are free of the same collection of trapping sets while having a smaller block length, or a larger collection of trapping sets while having the same block length. In addition, the efficiency of the search algorithm makes it possible to design codes with larger degrees which are free of trapping sets within larger ranges compared to the state-of-the-art.

    更新日期:2020-02-18
  • Robust BICM Design for the LDPC Coded DCO-OFDM: A Deep Learning Approach
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-19
    Yuan He; Ming Jiang; Xintong Ling; Chunming Zhao

    In this paper, a deep learning (DL) approach for enhancing the bit-interleaved coded modulation (BICM) receiver is designed to mitigate the clipping distortion in the low-density parity-check (LDPC) coded direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) systems. This work aims to combine the neural network (NN) with the physical layer communications by using a model-driven DL architecture. We first develop a non-iterative NN-aided BICM (NN-BICM) receiver, where the NN is trained with the loss function of cross-entropy to output the modified conditional probability through the $softmax$ activation function, thereby assisting in a log-likelihood ratio (LLR) improvement. Then, we propose two iterative NN-BICM receivers for iterative demapping and decoding. The single iterative design feeds the soft decisions from the LDPC decoder back to the demapper only, while the joint iterative design feeds the soft decisions back to the demapper and NN jointly. By adopting the iteration-wise pre-training strategy, the joint iterative design has been improved by representing the intractable relationship between the conditional probability and the $a~priori$ probability with a deeper NN architecture. We further investigate an efficient bit loading algorithm for DCO-OFDM systems employing the NN-BICM receiver. Both NN-BICM receivers and iterative schemes can obtain remarkable performance gains over the existing benchmarks.

    更新日期:2020-02-18
  • Active Deep Decoding of Linear Codes
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Ishay Be’Ery; Nir Raviv; Tomer Raviv; Yair Be’Ery

    High quality data is essential in deep learning to train a robust model. While in other fields data is sparse and costly to collect, in error decoding it is free to query and label thus allowing potential data exploitation. Utilizing this fact and inspired by active learning, two novel methods are introduced to improve Weighted Belief Propagation (WBP) decoding. These methods incorporate machine-learning concepts with error decoding measures. For BCH(63,36), (63,45) and (127,64) codes, with cycle-reduced parity-check matrices, improvement of up to 0.4dB at the waterfall region, and of up to 1.5dB at the error-floor region in FER, over the original WBP, is demonstrated by smartly sampling the data, without increasing inference (decoding) complexity. The proposed methods constitutes an example guidelines for model enhancement by incorporation of domain knowledge from error-correcting field into a deep learning model. These guidelines can be adapted to any other deep learning based communication block.

    更新日期:2020-02-18
  • Short-Packet Physical-Layer Network Coding
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-02
    Shakeel Salamat Ullah; Soung Chang Liew; Gianluigi Liva; Taotao Wang

    This paper explores the application of physical-layer network coding (PNC) for short-packet transmissions. PNC can potentially reduce the communication delay in relay-assisted wireless networks and can thus be instrumental in realizing short-packet communication systems with stringent delay requirements. In this work, first, we first derive an achievability bound for channel-coded short-packet PNC systems. Based on the random-coding error-exponent, the bound serves as a benchmark for short-packet PNC operating with traditional preamble-aided channel estimation and XOR channel decoding. Second, we design a blind channel estimation algorithm and a code-aided channel estimation algorithm for short-packet PNC systems. Both outperform the traditional preamble-aided channel estimation for PNC systems operating with mismatched channel-state-information. As a case study, we compare the three algorithms for packets of 128 symbols over a two-way relay channel. The results show that the blind algorithm outperforms the code-aided algorithm and preamble-aided algorithm by almost 0.2 and 1.5 dB respectively. Furthermore, the blind algorithm achieves the target packet error rate of 10 −4 within 0.5 dB of the random coding bound of an imaginary system in which perfect channel-state-information is available at the relay at no cost (i.e., channel estimation is not required in the imaginary system). The bound and the algorithms give us a fundamental framework for applying PNC to short-packet transmissions.

    更新日期:2020-02-18
  • A Deliberate Bit Flipping Coding Scheme for Data-Dependent Two-Dimensional Channels
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-02
    Mohsen Bahrami; Bane Vasić

    In this paper, we present a deliberate bit flipping (DBF) coding scheme for binary two-dimensional (2-D) channels, where specific patterns in channel inputs are the significant cause of errors. The idea is to eliminate a constrained encoder and, instead, embed a constraint into an error correction codeword that is arranged into a 2-D array by deliberately flipping the bits that violate the constraint. The DBF method relies on the error correction capability of the code being used so that it should be able to correct both deliberate errors and channel errors. Therefore, it is crucial to flip minimum number of bits in order not to overburden the error correction decoder. We devise a constrained combinatorial formulation for minimizing the number of flipped bits for a given set of harmful patterns. The generalized belief propagation algorithm is used to find an approximate solution for the problem. We evaluate the performance gain of our proposed approach on a data-dependent 2-D channel, where 2-D isolated-bits patterns are the harmful patterns for the channel. Furthermore, the performance of the DBF method is compared with classical 2-D constrained coding schemes for the 2-D no isolated-bits constraint on a memoryless binary symmetric channel.

    更新日期:2020-02-18
  • Error Performance of NOMA-Based Cognitive Radio Networks With Partial Relay Selection and Interference Power Constraints
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-06-06
    Lina Bariah; Sami Muhaidat; Arafat Al-Dweik

    Non-orthogonal multiple access (NOMA)-based cognitive radio (CR) networks have recently emerged as a promising solution to enhance the spectral efficiency and massive connectivity problems. In this paper, we investigate the error rate performance of relay-assisted NOMA with partial relay selection in an underlay cognitive radio network. In this setup, $K$ relays are used to assist in transmission between secondary NOMA users and a secondary base station (SBS), where the relay (R) with the strongest link with the SBS is selected to amplify-and-forward (AF) its received signals to the secondary receivers. We derive an accurate approximation for the pairwise error probability (PEP) of the secondary users with imperfect successive interference cancellation (SIC). Subsequently, the derived PEP expression is utilized to deduce a union bound, which is considered as an upper bound on the bit error rate (BER). We further formulate an optimization problem to calculate the optimum power coefficients that minimize the derived union bound. Numerical and Monte Carlo simulation results are presented to corroborate the derived analytical expressions and give some useful insights into the error rate performance of each user.

    更新日期:2020-02-18
  • Joint Beamforming Design and Resource Allocation for Terrestrial-Satellite Cooperation System
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-29
    Yuandong Zhang; Liuguo Yin; Chunxiao Jiang; Yi Qian

    In this paper, we investigate a multicast beamforming terrestrial-satellite cooperation system to optimize the communication capacity and quality of service. Different from traditional link-based terrestrial network, we design the terrestrial and satellite beamforming vectors cooperatively based on the required contents of users in order to realize more reasonable resource allocation. Meanwhile, the backhaul links between content provision center and satellite and base stations are limited, and the users always need high quality of service, considering these, our object is maximizing the sum of user minimum ratio under the constraints of resource allocation, backhaul link and quality of service in reality. We first formulate the optimization problem and propose a joint optimization iterative algorithm to design the beamforming vectors of satellite and base stations cooperatively. Then, to obtain the global optimum solution, we propose a Bound-based algorithm and solve the optimization problem by shrinking the upper bound and lower bound of the optimization feasible region. To decrease the complexity, we then design a heuristic scheme to solve the problem. The simulation results show that, our proposed cooperative optimization algorithms have better performance than non-cooperative methods, and the heuristic scheme has little poor performance but has significant advantage in low complexity.

    更新日期:2020-02-18
  • On the Performance of Cell-Free Massive MIMO Relying on Adaptive NOMA/OMA Mode-Switching
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-11
    Manijeh Bashar; Kanapathippillai Cumanan; Alister G. Burr; Hien Quoc Ngo; Lajos Hanzo; Pei Xiao

    The downlink (DL) of a non-orthogonal-multiple-access (NOMA)-based cell-free massive multiple-input multiple-output (MIMO) system is analyzed, where the channel state information (CSI) is estimated using pilots. It is assumed that the users are grouped into multiple clusters. The same pilot sequences are assigned to the users within the same clusters whereas the pilots allocated to all clusters are mutually orthogonal. First, a user’s bandwidth efficiency (BE) is derived based on his/her channel statistics under the assumption of employing successive interference cancellation (SIC) at the users’ end with no DL training. Next, the classic max-min optimization framework is invoked for maximizing the minimum BE of a user under per-access point (AP) power constraints. The max-min user BE of NOMA-based cell-free massive MIMO is compared to that of its orthogonal multiple-access (OMA) counter part, where all users employ orthogonal pilots. Finally, our numerical results are presented and an operating mode switching scheme is proposed based on the average per-user BE of the system, where the mode set is given by Mode = { OMA, NOMA }. Our numerical results confirm that the switching point between the NOMA and OMA modes depends both on the length of the channel’s coherence time and on the total number of users.

    更新日期:2020-02-18
  • MIMO-OFDM-Based Wireless-Powered Relaying Communication With an Energy Recycling Interface
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-11
    Ali Arshad Nasir; Hoang Duong Tuan; Trung Q. Duong; H. Vincent Poor

    This paper considers wireless-powered relaying multiple-input-multiple-output (MIMO) communication, where all four nodes (information source, energy source, relay, and destination) are equipped with multiple antennas. Orthogonal frequency division multiplexing (OFDM) is applied for information processing to compensate the frequency selectivity of communication channels between the information source and the relay and between the relay and the destination as these nodes are assumed to be located far apart from each. The relay is equipped with a full-duplexing interface for harvesting energy not only from the wireless transmission of the dedicated energy source but also from its own transmission while relaying the source information to the destination. The problem of designing the optimal power allocation over OFDM subcarriers and transmit antennas to maximize the overall spectral efficiency is addressed. Due to a very large number of subcarriers, this design problem poses a large-scale nonconvex optimization problem involving a few thousand variables of power allocation, which is very computationally challenging. A novel path-following algorithm is proposed for computation. Based on the developed closed-form calculation of linear computational complexity at each iteration, the proposed algorithm rapidly converges to an optimal solution. Compared to the best existing solvers, the computational complexity of the proposed algorithm is reduced at least 10 5 times, making it very efficient and practical for online computation while existing solvers are ineffective. Numerical results for a practical simulation setting show promising results by achieving high spectral efficiency.

    更新日期:2020-02-18
  • Energy Efficient Wireless Relay Networks With Computational Awareness
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-14
    Bartosz Bossy; Paweł Kryszkiewicz; Hanna Bogucka

    In this paper, we investigate joint subcarrier (SC) allocation, pairing and power loading for optimized energy efficiency (EE) in multiuser, multicell, multicarrier downlink decode-and-forward (DF) relay interference networks with computational awareness, i.e., taking computations-related energy into account. In order to maximize EE of the network, the transmission mode is adapted to instantaneous channel conditions. For the benefit of spectral-efficiency, both direct- and relayed transmission is allowed to use the same SCs simultaneously. Linearly rate-dependent power consumption of signal processing is considered. The formulated optimization problem is the nonconvex fractional mixed binary-integer programming problem, which has NP-hard complexity. Hence, we approximate the problem by the series of equivalent convex problems applying convex relaxation techniques such as a Successive Convex Approximation (SCA). Based on these transformations, we develop an iterative algorithm exploiting the Dinkelbach method to tackle the nonlinear fractional programming problem which maximizes EE of the system. Moreover, in our considerations, the total transmission power constraint and the minimum required rate constraints have been included. Simulation results demonstrate the effectiveness of our solution for future relay networks.

    更新日期:2020-02-18
  • An Information Theory of Neuro-Transmission in Multiple-Access Synaptic Channels
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-09-16
    Mladen Veletić; Ilangko Balasingham

    Information theory provides maximum possible information transfer over communication channels, including neural channels recently emerged as remarkable for disruptive nano-networking applications. Information theory was successfully applied to quantify the ability of biological sensory neurons to transfer the information from dynamic stimuli. However, a little of information theory has been subjected to quantify the reliability of neuro-transmission between synaptically coupled neurons. Neuro-transmission, regarded as molecular synaptic communication, relays information between neurons and significantly affects the overall brain processing performance. In this study, we use concepts from information theory to provide the framework based on closed-form expressions that quantify the information rate allowing assessment of neuro-transmission when the parameters are provided for any type of neurons. Considering Poissonian statistics and the rate coding model of neural communication, we show how the information transferred between cortical neurons depend on the molecular, physiological and morphological diversity of cells, the firing rate, and the synaptic wiring. With synaptic redundancy, we infer the ability of an isolated post-synaptic neuron to reliably convey information encoded in the spike train from a pre-synaptic neuron. Estimating information rate between neurons primarily serves in the evaluation of the overall performance of biological neural nano-networks and the development of artificial nano-networks.

    更新日期:2020-02-18
  • Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-17
    Daniel Verenzuela; Emil Björnson; Xiaojie Wang; Maximilian Arnold; Stephan ten Brink

    Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers from data interference that reduces the SE gains. This paper proposes the Massive-MIMO Iterative Channel Estimation and Decoding (MICED) algorithm where partially decoded data is used as side-information to improve the channel estimation and increase SE. We show that users with precise data estimates can help users with poor data estimates to decode. Numerical results with QPSK modulation and LDPC codes show that the MICED algorithm increases the SE and reduces the block-error-rate with RP and SP compared to conventional methods. The MICED algorithm with SP delivers the highest SE and it is especially effective in scenarios with short coherence blocks like high mobility or high frequencies.

    更新日期:2020-02-18
  • Performance Analysis of Quantized Uplink Massive MIMO-OFDM With Oversampling Under Adjacent Channel Interference
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-20
    Ali Bulut Üçüncü; Emil Björnson; Håkan Johansson; Ali Özgür Yılmaz; Erik G. Larsson

    Massive multiple-input multiple-output (MIMO) systems have attracted much attention lately due to the many advantages they provide over single-antenna systems. Owing to the many antennas, low-cost implementation and low power consumption per antenna are desired. To that end, massive MIMO structures with low-resolution analog-to-digital converters (ADC) have been investigated in many studies. However, the effect of a strong interferer in the adjacent band on quantized massive MIMO systems have not been examined yet. In this study, we analyze the performance of uplink massive MIMO with low-resolution ADCs under frequency selective fading with orthogonal frequency division multiplexing (OFDM) in the perfect and imperfect receiver channel state information cases. We derive analytical expressions for the bit error rate and ergodic capacity. We show that the interfering band can be suppressed by increasing the number of antennas or the oversampling rate when a zero-forcing receiver is employed.

    更新日期:2020-02-18
  • Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-20
    Jindan Xu; Wei Xu; Derrick Wing Kwan Ng; A. Lee Swindlehurst

    In this paper, we investigate secure communication over sparse millimeter-wave (mm-Wave) massive multiple-input multiple-output (MIMO) channels by exploiting the spatial sparsity of legitimate user’s channel. We propose a secure communication scheme in which information data is precoded onto dominant angle components of the sparse channel through a limited number of radio-frequency (RF) chains, while artificial noise (AN) is broadcast over the remaining nondominant angles interfering only with the eavesdropper with a high probability. It is shown that the channel sparsity plays a fundamental role analogous to secret keys in achieving secure communication. Hence, by defining two statistical measures of the channel sparsity, we analytically characterize its impact on secrecy rate. In particular, a substantial improvement on secrecy rate can be obtained by the proposed scheme due to the uncertainty, i.e., “entropy”, introduced by the channel sparsity which is unknown to the eavesdropper. It is revealed that sparsity in the power domain can always contribute to the secrecy rate. In contrast, in the angle domain, there exists an optimal level of sparsity that maximizes the secrecy rate. The effectiveness of the proposed scheme and derived results are verified by numerical simulations.

    更新日期:2020-02-18
  • Interference Alignment for One-Hop and Two-Hops MIMO Systems With Uncoordinated Interference
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Siavash Mollaebrahim Ghari; Pouya M. Ghari; Mohammad Sadegh Fazel; Glauber Brante; Muhammad Ali Imran

    Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e. , interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the $l_{2}$ and the Schatten- $p$ norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions.

    更新日期:2020-02-18
  • Secrecy Energy Efficiency Optimization for Multi-User Distributed Massive MIMO Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Jun Xu; Pengcheng Zhu; Jiamin Li; Xiaodong Wang; Xiaohu You

    This paper studies the energy-efficient power allocation problem for physical-layer security in multi-user (MU) distributed massive multiple-input multiple-output (MIMO) systems. A new metric called global average secrecy energy efficiency (GASEE) is proposed to measure the MU secrecy energy efficiency (SEE) with a single eavesdropper (Eve). We first derive closed-form expressions for the signal to interference-plus-noise ratios (SINRs) of legitimate users and the Eve with pilot contamination. Under a power consumption model that incorporates transmit power, backhaul power, remote antenna unit (RAU) circuit and signal processing power, and with transmit power constraints as well as SINR constraints for both users and the Eve, the GASEE maximization problem is formulated as a joint optimization of power allocation, RAU clustering, RAU selection and artificial noise (AN) selection. The formulated problem is a mixed integer nonlinear program (MINLP), which is solved by a double-loop procedure. In the outer loop, the denominator of objective is approximated as a linear function. In the inner loop, an efficient algorithm is proposed to find a near-optimal solution to the approximated problem by solving a sequence of sub-problems. Simulation results demonstrate that the proposed algorithm converges fast and achieves a higher GASEE than some heuristics.

    更新日期:2020-02-18
  • Performance of Multi-Cell Massive MIMO Systems With Interference Decoding
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-26
    Meysam Shahrbaf Motlagh; Subhajit Majhi; Patrick Mitran

    We consider a multi-cell massive MIMO system where a time-division duplex protocol is used to estimate the channel state information via uplink pilots. When maximum ratio combining (MRC) is used at the BSs, the re-use of pilots across cells causes the pilot contamination effect which yields interference components that do not vanish as the number of base-station (BS) antennas $M \rightarrow \infty $ . When treating interference as noise (TIN), this phenomenon limits the performance of multi-cell massive MIMO systems. In this paper, we analyze more advanced schemes based on simultaneous unique decoding (SD) as well as simultaneous non-unique decoding (SND) of the interference that can provide unbounded rate as $M \rightarrow \infty $ . We also establish a worst-case uncorrelated noise technique for multiple-access channels to derive achievable rate expressions for finite $M$ . Furthermore, we study a much simpler subset of SND (called S-SND) which provides a lower bound to SND and achieves unbounded rate as $M \rightarrow \infty $ , and also outperforms SD for finite $M$ . For the special cases of two-cell and three-cell systems, using a maximum symmetric rate allocation policy we compare the performance of different interference decoding schemes with that of TIN. Finally, we numerically illustrate the improved performance of the proposed schemes.

    更新日期:2020-02-18
  • ${N}$ -Continuous Signaling for GFDM
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-11
    Peng Wei; Yue Xiao; Lilin Dan; Lijun Ge; Wei Xiang

    An ${N}$ -continuous generalized frequency division multiplexing (GFDM) transceiver architecture is studied with the objective of striking a balanced trade-off between the bit error rate (BER) and the sidelobe suppression performance. More specifically, in the proposed ${N}$ -continuous GFDM signaling, the basis signals constructed allow one to make the GFDM signal ${N}$ -continuous and attain a compact spectrum as an explicit benefit of sidelobe suppression. We further reveal that compared to conventional ${N}$ -continuous orthogonal frequency division multiplexing (NC-OFDM), ${N}$ -continuous GFDM introduces relatively low interference through evaluating the signal-to-interference ratio (SIR). Secondly, a signal recovery algorithm is presented by constructing a recovery matrix to eliminate the interference. Finally, it is demonstrated that the proposed ${N}$ -continuous GFDM scheme outperforms its ${N}$ -continuous OFDM counterpart in terms of sidelobe suppression, while achieving moderate BER performance degradation as opposed to original OFDM.

    更新日期:2020-02-18
  • Optimization of Linearized Belief Propagation for Distributed Detection
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-26
    Younes Abdi; Tapani Ristaniemi

    In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a network of distributed agents can be approximated by a linear fusion of all the local log-likelihood ratios. The proposed approach clarifies how the BP algorithm works, simplifies the statistical analysis of its behavior, and enables us to develop a performance optimization framework for the BP-based distributed inference systems. Next, we propose a blind learning-adaptation scheme to optimize the system performance when there is no information available a priori describing the statistical behavior of the wireless environment concerned. In addition, we propose a blind threshold adaptation method to guarantee a certain performance level in a BP-based distributed detection system. To clarify the points discussed, we design a novel linear-BP-based distributed spectrum sensing scheme for cognitive radio networks and illustrate the performance improvement obtained, over an existing BP-based detection method, via computer simulations.

    更新日期:2020-02-18
  • Multicarrier $M$ -Ary Orthogonal Chaotic Vector Shift Keying With Index Modulation for High Data Rate Transmission
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-04
    Xiangming Cai; Weikai Xu; Lin Wang; Géza Kolumbán

    A new multicarrier $M$ -ary orthogonal chaotic vector shift keying with index modulation (MC-MOCVSK-IM) is presented in this paper. In this design, information bits are conveyed not only by the multiple groups of $M$ -ary information bearing signals, but also by the specific indices of the selected reference signals which depend on the incoming mapped bits. Benefiting from the favorable features of multicarrier modulation, $M$ -ary modulation and index modulation, MC-MOCVSK-IM system is capable to offer higher energy efficiency and spectral efficiency at some expense of hardware complexity. In addition, the analytical bit error rate (BER) expressions of MC-MOCVSK-IM system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. The BER performance comparison between MC-MOCVSK-IM system and other non-coherent chaotic communication systems is carried out to highlight the superiority of MC-MOCVSK-IM system in terms of BER performance. Considering the dramatically increased demand for high-data-rate transmission and the harsh environment of future wireless communication, MC-MOCVSK-IM system shows strong robustness and offers competitive solutions for high-data-rate non-coherent chaotic communication systems.

    更新日期:2020-02-18
  • Structure Learning of Sparse GGMs Over Multiple Access Networks
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-02
    Mostafa Tavassolipour; Armin Karamzade; Reza Mirzaeifard; Seyed Abolfazl Motahari; Mohammad-Taghi Manzuri Shalmani

    A central machine is interested in estimating the underlying structure of a sparse Gaussian Graphical Model (GGM) from a dataset distributed across multiple local machines. The local machines can communicate with the central machine through a wireless multiple access channel. In this paper, we are interested in designing effective strategies where reliable learning is feasible under power and bandwidth limitations. Two approaches are proposed: Signs and Uncoded methods. In the Signs method, the local machines quantize their data into binary vectors and an optimal channel coding scheme is used to reliably send the vectors to the central machine where the structure is learned from the received data. In the Uncoded method, data symbols are scaled and transmitted through the channel. The central machine uses the received noisy symbols to recover the structure. Theoretical results show that both methods can recover the structure with high probability for a large enough sample size. Experimental results indicate the superiority of the Signs method over the Uncoded method under several circumstances.

    更新日期:2020-02-18
  • A Group-Based Binary Splitting Algorithm for UHF RFID Anti-Collision Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-07
    Jian Su; Zhengguo Sheng; Alex X. Liu; Yu Han; Yongrui Chen

    Identification efficiency is a key performance metrics to evaluate the ultra high frequency (UHF) based radio frequency identification (RFID) systems. In order to solve the tag collision problem and improve the identification rate in large scale networks, we propose a collision arbitration strategy termed as group-based binary splitting algorithm (GBSA), which is an integration of an efficient tag cardinality estimation method, an optimal grouping strategy and a modified binary splitting. In GBSA, tags are properly divided into multiple subsets according to the tag cardinality estimation and the optimal grouping strategy. In case that multiple tags fall into a same time slot and form a subset, the modified binary splitting strategy will be applied while the rest tags are waiting in the queue and will be identified in the following slots. To evaluate its performance, we first derive the closed-form expression of system throughput for GBSA. Through the theoretical analysis, the optimal grouping factor is further determined. Extensive simulation results supplemented by prototyping tests indicate that the system throughput of our proposed algorithm can reach as much as 0.4835, outperforming the existing anti-collision algorithms for UHF RFID systems.

    更新日期:2020-02-18
  • Minimum Cost Reconfigurable Network Template Design With Guaranteed QoS
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-11
    Xiaoli Xu; Darryl Veitch; Yonghui Li; Branka Vucetic

    Conventional networks are based on layered protocols with intensive cross-layer interactions and complex signal processing at every node, making it difficult to meet the ultra-low latency requirement of mission critical applications in future communication systems. In this paper, we address this issue by proposing the concept of network template , which allows data to flow through it at the transmission symbol level, with minimal node processing. This is achieved by carefully calibrating the inter-connecting links among the nodes and pre-calculating the routing/network coding actions for each node, according to a set of preconfigured flows. In this paper, we focus on the minimum cost network template design to minimize the connections within the template, while ensuring that all the pre-defined configurations are feasible with the guaranteed throughput, latency and reliability. We show that the minimum cost network template design problem is difficult to solve optimally in general. We thus propose an efficient greedy algorithm to find a close-to-optimal solution. Simulation results show that the construction cost of the templates obtained by the proposed algorithm is very close to a lower bound. Furthermore, the construction cost increases only slightly with the number of pre-defined configurations, which confirms the flexibility of the network template design.

    更新日期:2020-02-18
  • Virtual Network Embedding With Guaranteed Connectivity Under Multiple Substrate Link Failures
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-19
    Nashid Shahriar; Reaz Ahmed; Shihabur Rahman Chowdhury; Md Mashrur Alam Khan; Raouf Boutaba; Jeebak Mitra; Feng Zeng

    This paper addresses Co nnectivity-aware Vi rtual N etwork E mbedding ( CoViNE ) problem, which consists in embedding a virtual network (VN) on a substrate network while ensuring VN connectivity (without any bandwidth guarantee) against multiple substrate link failures. CoViNE provides a weaker form of survivability incurring less resource overhead than traditional VN survivability models. To optimally solve CoViNE , we present an Integer Linear Program (ILP), namely CoViNE-opt . CoViNE-opt enumerates an exponential number of edge-cuts in a VN severely limiting its scalability. Therefore, we decompose CoViNE into three sub-problems: i) augmenting a VN with virtual links to provide necessary connectivity, ii) identifying the virtual links that should be embedded disjointly, and iii) computing a VN embedding while satisfying the disjointness constraints. We introduce conflicting set abstraction that allows to address sub-problems (i) and (ii) without enumerating all the edge-cuts of a VN. We propose two novel solutions to CoViNE leveraging conflicting set, namely CoViNE-ILP and CoViNE-fast . CoViNE-ILP uses a heuristic algorithm to address sub-problems (i) and (ii), while an ILP is used for sub-problem (iii). In contrast, CoViNE-fast uses heuristics for solving all three sub-problems. Through simulation, we evaluate the optimality and scalability of our solutions and demonstrate a failure restoration use-case enabled by CoViNE .

    更新日期:2020-02-18
  • Wake-Up Radio Based Access in 5G Under Delay Constraints: Modeling and Optimization
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-19
    Soheil Rostami; Sandra Lagen; Mário Costa; Mikko Valkama; Paolo Dini

    Recently, the concept of wake-up radio based access has been considered as an effective power saving mechanism for 5G mobile devices. In this article, the average power consumption of a wake-up radio enabled mobile device is analyzed and modeled by using a semi-Markov process. Building on this, a delay-constrained optimization problem is then formulated, to maximize the device energy-efficiency under given latency requirements, allowing the optimal parameters of the wake-up scheme to be obtained in closed form. The provided numerical results show that, for a given delay requirement, the proposed solution is able to reduce the power consumption by up to 40% compared with an optimized discontinuous reception (DRX) based reference scheme.

    更新日期:2020-02-18
  • A Continuum Model for Route Optimization in Large-Scale Inhomogeneous Multi-Hop Wireless Networks
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-22
    Dene A. Hedges; Justin P. Coon; Gaojie Chen

    Multi-hop route optimization in large-scale inhomogeneous networks is typically NP-hard, for most problem formulations, requiring the application of heuristics which, despite their relatively low processing complexity, find sub-optimal solutions. Where optimal solutions can be determined by Lagrangian based constrained optimization techniques for example, the processing complexity typically scales like $O(N^{3})$ , $N$ being the number of relays employed. Here, we propose an alternative approach to route optimization by considering the limit of infinite relay node density to develop a continuum model, which yields an optimized equivalent continuous relay path. The model is carefully constructed to maintain a constant connection density even though the node density scales without bound. This leads to a formulation for minimizing the end-to-end outage probability that can be solved using methods from the calculus of variations. With the continuum model, we show that the processing complexity scales linearly with the number of points that sample the continuous path, which can be lower than the number of relay nodes in a large scale network. We demonstrate the effectiveness of this new approach and its potential by considering a network subjected to point sources of interference.

    更新日期:2020-02-18
  • Double Coded Caching in Ultra Dense Networks: Caching and Multicast Scheduling via Deep Reinforcement Learning
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Zhengming Zhang; Hongyang Chen; Meng Hua; Chunguo Li; Yongming Huang; Luxi Yang

    Proposed by Maddah-Ali and Niesen, a coded caching scheme has been verified to alleviate the load of networks efficiently. Recently, a new technique called placement delivery array (PDA) was proposed to characterize the coded caching scheme. In this paper, we consider a caching system in the scope of ultra dense networks (UDNs). Each base station (BS) has a finite cache and stores some contents. We propose an efficient coded content caching scheme called double coded caching to make the transmission robust to in-and-out wireless network quality. Then the dynamic caching and multicast scheduling are considered to jointly minimize the average delay and power of the content-centric wireless networks. This stochastic optimization problem can be formulated as a Markov decision process (MDP) with unknown transition probabilities and large state space. We propose a deep reinforcement learning approach to deal with the decision problem. Our algorithm uses a variational auto-encoder (VAE) neural network to approximate the state sufficiently, and uses a weighted double Q-learning scheme to reduce variance and overestimation of the Q function. Numerical results demonstrate that the proposed double coded caching scheme increases the probability of the successful transmission, and the caching and scheduling policy can effectively reduce the delay and the power consumption.

    更新日期:2020-02-18
  • Online Content Popularity Prediction and Learning in Wireless Edge Caching
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-26
    Navneet Garg; Mathini Sellathurai; Vimal Bhatia; B. N. Bharath; Tharmalingam Ratnarajah

    Caching popular contents in advance is an important technique to achieve low latency and reduce the backhaul costs in future wireless communications. Considering a network with base stations distributed as a Poisson point process, optimal content placement caching probabilities are obtained to maximize the average success probability (ASP) for a known content popularity (CP) profile, which in practice is time-varying and unknown in advance. In this paper, we first propose two online prediction (OP) methods for forecasting CP viz., popularity prediction model (PPM) and Grassmannian prediction model (GPM), where the unconstrained coefficients for linear prediction are obtained by solving constrained non-negative least squares. To reduce the higher computational complexity per online round, two online learning (OL) approaches viz., weighted-follow-the-leader and weighted-follow-the-regularized-leader are proposed, inspired by the OP models. In OP, ASP difference (i.e, the gap between the ASP achieved by prediction and that by known content popularity) is bounded, while in OL, sub-linear MSE regret and linear ASP regret bounds are obtained. With MovieLens dataset, simulations verify that OP methods are better for MSE and ASP difference minimization, while the OL approaches perform well for the minimization of the MSE and ASP regrets.

    更新日期:2020-02-18
  • Sub-Carrier Loading Strategies for DCO-OFDM LED Communication
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-14
    Shokoufeh Mardanikorani; Xiong Deng; Jean-Paul M. G. Linnartz

    LEDs, particularly those used for Visible Light Communications (VLC), have a limited bandwidth, while above their 3 dB bandwidth, the roll-off is relatively gentle. If the modulation bandwidth would be limited to the 3 dB LED bandwidth, the achievable rate would be unacceptably constrained. Hence, effective communication systems need to optimize the use of bandwidth significantly above this 3 dB point. Orthogonal Frequency Division Multiplexing (OFDM) is a popular method to fine-tune the amount of power and constellation as a function of the channel response over different frequencies. Various power and bit loading strategies have been proposed and simulated in literature, but their performance was not captured in expressions. This manuscript derives these for optimal waterfilling, uniform and pre-emphasized power loading for the LED channel, that severely attenuates high frequencies. We also investigate the influence of practical discrete constellations and verify our new results experimentally. Interestingly, simple uniform loading only falls less than 1~2% short of the throughput achieved by waterfilling, but when we restrict OFDM to discrete QAM constellation sizes, the penalty for uniform loading is 1.5 dB. Inspired by the good performance of uniform power loading, we propose an algorithm to find the best discrete bit loading for uniform power within an optimized band. As pre-emphasis is nonetheless attractive because a flattened channel does not need adaptive sub-carrier loading, we quantify its penalty. This can be modest provided that the system can adapt its transmit bandwidth, thereby adaptively switching upper sub-carriers to zero power.

    更新日期:2020-02-18
  • Context-Aware TDD Configuration and Resource Allocation for Mobile Edge Computing
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-11
    Pengtao Zhao; Hui Tian; Kwang-Cheng Chen; Shaoshuai Fan; Gaofeng Nie

    Mobile edge computing (MEC) supporting localized context awareness creates a new technological frontier for 5G and beyond. Due to very asymmetric traffic related to MEC and the time division duplexing (TDD) system, we efficiently exploit the networking and computing functionalities for TDD orthogonal frequency division multiple access (TDD-OFDMA) technology supporting multiple services. The primary technical challenge of TDD-OFDMA systems lies in dynamic configuring based on the unknown characteristics of future traffic, i.e., the information lag. Therefore, a model-free online TDD configuration scheme is proposed based on context analysis and multi-armed bandit (MAB) optimization. The characteristics of future traffic are predicted by the context-aware MEC computing, so that TDD configuration is novelly modeled as a contextual MAB problem. Solving MAB by the contextual upper-confidence-bound, TDD configuration can be dynamically adjusted according to network traffic. To simultaneously reduce the energy consumption and makespan of mobile devices (MDs), a greedy resource allocation (GRA) embedded in the TDD configuration is further developed to select MDs and allocate resources. GRA algorithm decomposes the complex multi-factor coupling non-convex problem into a series of convex sub-problems, thereby asymptotically obtaining the selection and allocation with polynomial time complexity. Simulations justify significant performance gain in mobile networking and MEC.

    更新日期:2020-02-18
  • Sparse Bayesian Learning-Aided Joint Sparse Channel Estimation and ML Sequence Detection in Space-Time Trellis Coded MIMO-OFDM Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-13
    Amrita Mishra; Aditya K. Jagannatham; Lajos Hanzo

    Sparse Bayesian learning (SBL)-based approximately sparse channel estimation schemes are conceived for space-time trellis coded (STTC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems relying on trellis-based encoding and decoding over the data subcarriers. First, a pilot-aided channel estimation scheme is developed employing the multiple response extension of SBL (MSBL) framework. Subsequently, a novel data-aided joint channel estimation and data decoding framework relying on optimal maximum likelihood sequence detection (MLSD) is intrinsically amalgamated with our powerful EM-based MSBL algorithm. Explicitly, an MSBL-based MIMO channel estimate is gleaned in the E-step followed by a novel modified path-metric-based Viterbi decoder in the M-step. Our theoretical analysis characterizes the performance of the proposed schemes in terms of the associated frame error rate (FER) upper bounds by explicitly considering the effect of estimation errors along with evaluating the product measure of the STTC under consideration. Finally, our simulation results are complemented by the Bayesian Cramér-Rao bound (BCRB), the associated complexity analysis and the performance of the proposed schemes for validating the theoretical bounds.

    更新日期:2020-02-18
  • Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-28
    Sumudu Samarakoon; Mehdi Bennis; Walid Saad; Mérouane Debbah

    In this paper, the problem of joint power and resource allocation (JPRA) for ultra-reliable low-latency communication (URLLC) in vehicular networks is studied. Therein, the network-wide power consumption of vehicular users (VUEs) is minimized subject to high reliability in terms of probabilistic queuing delays. Using extreme value theory (EVT), a new reliability measure is defined to characterize extreme events pertaining to vehicles’ queue lengths exceeding a predefined threshold. To learn these extreme events, assuming they are independently and identically distributed over VUEs, a novel distributed approach based on federated learning (FL) is proposed to estimate the tail distribution of the queue lengths. Considering the communication delays incurred by FL over wireless links, Lyapunov optimization is used to derive the JPRA policies enabling URLLC for each VUE in a distributed manner. The proposed solution is then validated via extensive simulations using a Manhattan mobility model. Simulation results show that FL enables the proposed method to estimate the tail distribution of queues with an accuracy that is close to a centralized solution with up to 79% reductions in the amount of exchanged data. Furthermore, the proposed method yields up to 60% reductions of VUEs with large queue lengths, while reducing the average power consumption by two folds, compared to an average queue-based baseline.

    更新日期:2020-02-18
  • Multi-Target Position and Velocity Estimation Using OFDM Communication Signals
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-02
    Yinchuan Li; Xiaodong Wang; Zegang Ding

    In this paper, we consider a passive radar system that estimates the positions and velocities of multiple moving targets by using OFDM signals transmitted by a totally un-coordinated and un-synchronizated illuminator and multiple receivers. It is assumed that data demodulation is performed separately based on the direct-path signal, and the error-prone estimated data symbols are made available to the passive radar receivers, which estimate the positions and velocities of the targets in two stages. First, we formulate a problem of joint estimation of the delay-Doppler of reflectors and the demodulation errors, by exploiting two types of sparsities of the system, namely, the numbers of reflectors (i.e., targets and clutters) and demodulation errors are both small. This problem is non-convex and a conjugate gradient descent method is proposed to solve it. Then in the second stage we determine the positions and velocities of targets based on the estimated delay-Doppler in the first stage. For the second stage, two methods are proposed: the first is based on numerically solving a set of nonlinear equations, while the second is based on the neural network, which is more efficient. The performance of the proposed algorithms is evaluated through extensive simulations.

    更新日期:2020-02-18
  • Channel Aware Sparse Transmission for Ultra Low-Latency Communications in TDD Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Wonjun Kim; Hyoungju Ji; Byonghyo Shim

    Major goal of ultra reliable and low latency communication (URLLC) is to reduce the latency down to a millisecond (ms) level while ensuring reliability of the transmission. Since the current uplink transmission scheme requires a complicated handshaking procedure to initiate the transmission, to meet this stringent latency requirement is a challenge in wireless system design. In particular, in the time division duplexing (TDD) systems, supporting the URLLC is difficult since the mobile device has to wait until the transmit direction is switched to the uplink. In this paper, we propose a new approach to support a low latency access in TDD systems, called channel aware sparse transmission (CAST). Key idea of the proposed scheme is to encode a grant signal in a form of sparse vector. This together with the fact that the sensing mechanism preserves the energy of the sparse vector allows us to use the compressed sensing (CS) technique in CAST decoding. From the performance analysis and numerical evaluations, we demonstrate that the proposed CAST scheme achieves a significant reduction in access latency over the 4G LTE-TDD and 5G NR-TDD systems.

    更新日期:2020-02-18
  • Distributed Zero-Forcing Amplify-and-Forward Beamforming for WSN Operation in Interfered and Highly Scattered Environments
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-03-20
    Slim Zaidi; Oussama Ben Smida; Sofiène Affes; Shahrokh Valaee

    In this paper, amplify-and-forward beamforming (AFB) is considered to establish a communication, through wireless sensor networks (WSNs) of $K$ sensor nodes, from a source to a receiver in the presence of both scattering and interference. All sources send their data to the WSN during the first time slot, while the nodes forward a properly weighted version of their received signals during the second slot. These weights are properly selected to maximize the desired power while completely canceling the interference signals. We show, however, that they depend on information locally unavailable at each node, making the zero-forcing beamformer (ZFB) unsuitable for WSNs, due to the prohibitive data exchange overhead and the power depletion it would require. To address this issue, we exploit the asymptotic expression at large $K$ of the ZFB weights that is locally computable at every node and, further, well-approximates their original counterparts. The performance of the resulting new distributed ZFB (DZFB) version is analyzed and compared with the conventional ZFB and two other distributed AFB benchmarks: the monochromatic (i.e., single-ray) AFB whose design neglects the presence of scattering and the bichromatic AFB which relies on an efficient two-ray channel approximation valid only for low angular spread (AS). We show that the proposed DZFB outperforms its monochromatic and bichromate counterparts while incurring much less overhead and power depletion than ZFB. We show also that it is able to provide optimal performance even in highly scattered environments as in the latter.

    更新日期:2020-02-18
  • Multi-Cell Interference Management Scheme for Next-Generation Cellular Networks
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-12-11
    Xueyuan Zhao; Dario Pompili

    Inter-cell interference is a major issue for next-generation wireless cellular networks, due to the increased user mobility, high user density, and backhaul bandwidth constraint. In this work, a unified approach is proposed to address these challenges. The proposal firstly performs a per-cell signal spreading by Zadoff-Chu (ZC) sequence, then the spread signal is precoded by a modified coordinated beamforming scheme. The proposal is robust to Doppler caused by user mobility, supports a high co-channel user capacity for ultra-dense networks, and requires only limited backhaul signaling exchange between basestations thus being suitable for massive MIMO deployment. The advantages of the proposal are firstly analyzed in theory, then evaluation results are presented to validate the proposal for MIMO and massive MIMO setups. It is found that the proposed scheme consistently outperforms the traditional scheme under various scenarios. The practical issues related to synchronization in coordinated beamforming are discussed.

    更新日期:2020-02-18
  • Mutual Successive Interference Cancellation Strategies in NOMA for Enhancing the Spectral Efficiency of CoMP Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-07
    Antoine Kilzi; Joumana Farah; Charbel Abdel Nour; Catherine Douillard

    The densification of mobile networks should enable the fifth generation (5G) mobile networks to cope with the ever increasing demand for higher rate traffic, reduced latency, and improved reliability. The large scale deployment of small cells and distributed antenna systems in heterogeneous environments will require more elaborate interference mitigating techniques to increase spectral efficiency and to help unlock the expected performance leaps from the new network topologies. Coordinated multi-point (CoMP) is the most advanced framework for interference management enabling the cooperation between base stations to mitigate inter-cell interference and boost cell-edge user performance. In this paper, we study the combination of CoMP with mutual SIC, an interference cancellation technique based on power-domain non-orthogonal multiple access (NOMA) that enables multiplexed users to simultaneously cancel their corresponding interfering signals. A highly efficient inter-cell interference cancellation scheme is then devised, that can encompass several deployment configurations and coordination techniques. The obtained results prove the superiority of this approach compared to conventional NOMA-CoMP systems.

    更新日期:2020-02-18
  • G-MultiSphere: Generalizing Massively Parallel Detection for Non-Orthogonal Signal Transmissions
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-28
    Chathura Jayawardena; Konstantinos Nikitopoulos

    The increasing demand for connectivity and throughput, despite the spectrum limitations, has triggered a paradigm shift towards non-orthogonal signal transmissions. However, the complexity requirements of near-optimal detection methods for such systems becomes impractical, due to the large number of mutually interfering streams and to the rank-deficient or ill-determined nature of the corresponding interference matrix. This work introduces g-MultiSphere; a generic massively parallel and near-optimal sphere-decoding-based approach that, in contrast to prior work, applies to both well- and ill-determined non-orthogonal systems. We show that g-MultiSphere is the first approach that can support large uplink multi-user MIMO systems with numbers of concurrently transmitting users that exceed the number of receive antennas by a factor of two or more, while attaining throughput gains of up to 60% and with reduced complexity requirements in comparison to known approaches. By eliminating the need for sparse signal transmissions for non-orthogonal multiple access (NOMA) schemes, g-MultiSphere can support more users than existing systems with better detection performance and practical complexity requirements. In comparison to state-of-the-art detectors for NOMA schemes and non-orthogonal signal waveforms (e.g., SEFDM) g-MultiSphere can be up to an order of magnitude less complex, and can provide throughput gains of up to 60%.

    更新日期:2020-02-18
  • Effective Capacity of $L_p$ -Norm Diversity Receivers Over Generalized Fading Channels Under Adaptive Transmission Schemes
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-29
    K. Denia Kanellopoulou; Kostas P. Peppas; P. Takis Mathiopoulos

    This paper presents novel moment generating function (MGF)- and characteristic function (CHF)-based frameworks for the EC performance analysis of a generic $L_{p}$ -norm diversity combining scheme under adaptive transmission policies. The considered system operates over generalized fading channels, a maximum delay constraint and under various channel state information (CSI) conditions. Depending upon the operational CSI, four policies are studied, namely: i) Constant power with optimal rate adaptation (ORA); ii) Optimal power and rate adaptation (OPRA); iii) Channel inversion with fixed rate (CIFR); and iv) Truncated CIFR (TIFR). The $L_{p}$ -norm diversity is a generic diversity structure which includes as special cases various well-known diversity schemes, such as equal gain combining (EGC), maximal ratio combining (MRC) and amplify-and-forward (AF) relaying. Under the ORA and OPRA policies, we derive single integral expressions for evaluating the EC of $L_{p}$ -norm diversity reception directly from the MGF or the incomplete MGF of the Signal-to-Noise-Ratio (SNR) at the receiver, respectively. For the EC performance evaluation of the EGC and AF relaying systems operating under the OPRA policy, a CHF-based approach, which is computationally more efficient as compared to the MGF-based approach, is further presented. It is shown that the EC for the CIFR and TIFR policies can be directly evaluated from the MGF or the CHF of the SNR at the receiver, respectively. For the ORA policy, a novel analytical approach for the asymptotic EC performance analysis is also developed and evaluated, revealing how important system operation parameters affect the overall system performance. The mathematical formalism is validated with selected numerical and equivalent simulation performance evaluation results, thus confirming the correctness of the proposed analytical methodology.

    更新日期:2020-02-18
  • Throughput Maximization for UAV-Aided Backscatter Communication Networks
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-14
    Meng Hua; Luxi Yang; Chunguo Li; Qingqing Wu; A. Lee Swindlehurst

    This paper investigates unmanned aerial vehicle (UAV)-aided backscatter communication (BackCom) networks, where the UAV is leveraged to help the backscatter device (BD) forward signals to the receiver. Based on the presence or absence of a direct link between BD and receiver, two protocols, namely transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR) protocol, are proposed to utilize the UAV to assist the BD. In particular, we formulate the system throughput maximization problems for the two protocols by jointly optimizing the time allocation, reflection coefficient and UAV trajectory. Different static/dynamic circuit power consumption models for the two protocols are analyzed. The resulting optimization problems are shown to be non-convex, which are challenging to solve. We first consider the dynamic circuit power consumption model, and decompose the original problems into three sub-problems, namely time allocation optimization with fixed UAV trajectory and reflection coefficient, reflection coefficient optimization with fixed UAV trajectory and time allocation, and UAV trajectory optimization with fixed reflection coefficient and time allocation. Then, an efficient iterative algorithm is proposed for both protocols by leveraging the block coordinate descent method and successive convex approximation (SCA) techniques. In addition, for the static circuit power consumption model, we obtain the optimal time allocation with a given reflection coefficient and UAV trajectory and the optimal reflection coefficient with low computational complexity by using the Lagrangian dual method. Simulation results show that the proposed protocols are able to achieve significant throughput gains over the compared benchmarks.

    更新日期:2020-02-18
  • Uplink Precoding Optimization for NOMA Cellular-Connected UAV Networks
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-19
    Xiaowei Pang; Guan Gui; Nan Zhao; Weile Zhang; Yunfei Chen; Zhiguo Ding; Fumiyuki Adachi

    Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV’s co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

    更新日期:2020-02-18
  • Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-25
    Samad Ali; Hossein Asgharimoghaddam; Nandana Rajatheva; Walid Saad; Jussi Haapola

    Ensuring an effective coexistence of conventional broadband cellular users with machine type communications (MTCs) is challenging due to the interference from MTCs to cellular users. This interference challenge stems from the fact that the acquisition of channel state information (CSI) from machine type devices (MTD) to cellular base stations (BS) is infeasible due to the small packet nature of MTC traffic. In this paper, a novel approach based on the concept of opportunistic spatial orthogonalization (OSO) is proposed for interference management between MTC and conventional cellular communications. In particular, a cellular system is considered with a multi-antenna BS in which a receive beamformer is designed to maximize the rate of a cellular user, and, a machine type aggregator (MTA) that receives data from a large set of MTDs. The BS and MTA share the same uplink resources, and, therefore, MTD transmissions create interference on the BS. However, if there is a large number of MTDs to chose from for transmission at each given time for each beamformer, one MTD can be selected such that it causes almost no interference on the BS. A comprehensive analytical study of the characteristics of such an interference from several MTDs on the same beamformer is carried out. It is proven that, for each beamformer, an MTD exists such that the interference on the BS is negligible. To further investigate such interference, the distribution of the signal-to-interference-plus-noise ratio (SINR) of the cellular user is derived, and, subsequently, the distribution of the outage probability is presented. However, the optimal implementation of OSO requires the CSI of all the links in the BS, which is not practical for MTC. To solve this problem, an online learning method based on the concept of contextual multi-armed bandits (MAB) learning is proposed. The receive beamformer is used as the context of the contextual MAB setting and Thompson sampling: a well-known method of solving contextual MAB problems is proposed. Since the number of contexts in this setting can be unlimited, approximating the posterior distributions of Thompson sampling is required. Two function approximation methods, a) linear full posterior sampling, and, b) neural networks are proposed for optimal selection of MTD for transmission for the given beamformer. Simulation results show that is possible to implement OSO with no CSI from MTDs to the BS. Linear full posterior sampling achieves almost 90% of the optimal allocation when the CSI from all the MTDs to the BS is known.

    更新日期:2020-02-18
  • Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-26
    Weidong Mei; Rui Zhang

    The line-of-sight (LoS) dominant air-ground channels have posed critical interference issues in cellular-connected unmanned aerial vehicle (UAV) communications. In this paper, we propose a new base station (BS) cooperative beamforming (CB) technique for the cellular downlink to mitigate the strong interference caused by the co-channel terrestrial transmissions to the UAV. Besides the conventional CB by cooperatively transmitting the UAV’s message, the serving BSs of the UAV exploit a novel CB-based interference transmission scheme to effectively suppress the terrestrial interference to the UAV. Specifically, the co-channel terrestrial users’ messages are shared with the UAV’s serving BSs and transmitted via CB so as to cancel their resultant interference at the UAV’s receiver. To optimally balance between the CB gains for UAV signal enhancement and terrestrial interference cancellation, we formulate a new problem to maximize the UAV’s receive signal-to-interference-plus-noise ratio (SINR) by jointly optimizing the power allocations at all of its serving BSs for transmitting the UAV’s and co-channel terrestrial users’ messages. First, we derive the closed-form optimal solution to this problem in the special case of one serving BS for the UAV and draw useful insights. Then, we propose an algorithm to solve the problem optimally in the general case. As the optimal solution requires centralized implementation with exorbitant message/channel information exchanges among the BSs, we further propose a distributed algorithm that is amenable to practical implementation, based on a new divide-and-conquer approach, whereby each co-channel BS divides its perceived interference to the UAV into multiple portions, each to be canceled by a different serving BS of the UAV with its best effort. Numerical results show that the proposed centralized and distributed CB schemes with interference transmission and cancellation (ITC) can both significantly improve the UAV’s downlink performance as compared to the conventional CB without applying ITC.

    更新日期:2020-02-18
  • Specific Absorption Rate-Aware Beamforming in MISO Downlink SWIPT Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-28
    Juping Zhang; Gan Zheng; Ioannis Krikidis; Rui Zhang

    This paper investigates the optimal transmit beamforming design of simultaneous wireless information and power transfer (SWIPT) in the multiuser multiple-input-single-output (MISO) downlink with specific absorption rate (SAR) constraints. We consider the power splitting technique for SWIPT, where each receiver divides the received signal into two parts: one for information decoding and the other for energy harvesting with a practical non-linear rectification model. The problem of interest is to maximize as much as possible the received signal-to-interference-plus-noise ratio (SINR) and the energy harvested for all receivers, while satisfying the transmit power and the SAR constraints by optimizing the transmit beamforming at the transmitter and the power splitting ratios at different receivers. The optimal beamforming and power splitting solutions are obtained with the aid of semidefinite programming and bisection search. Low-complexity fixed beamforming and hybrid beamforming techniques are also studied. Furthermore, we study the effect of imperfect channel information and radiation matrices, and design robust beamforming to guarantee the worst-case performance. Simulation results demonstrate that our proposed algorithms can effectively deal with the radio exposure constraints and significantly outperform the conventional transmission scheme with power backoff.

    更新日期:2020-02-18
  • Linear Codes From Perfect Nonlinear Functions Over Finite Fields
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-14
    Yanan Wu; Nian Li; Xiangyong Zeng

    In this paper, a class of $p$ -ary 3-weight linear codes and a class of binary 2-weight linear codes are proposed respectively by virtue of the properties of the perfect nonlinear functions over $\mathbb {F}_{p^{m}}$ and $(m,s)$ -bent functions from $\mathbb {F}_{2^{m}}$ to $\mathbb {F}_{2^{s}}$ , where $p$ is an odd prime and $m, s$ are positive integers. The weight distributions are completely determined by the sign of the Walsh transform of weakly regular bent functions and the size of the preimage of the employed $(m,s)$ -bent functions at the zero point, respectively. As a special case, a class of optimal linear codes meeting Griesmer bound is obtained from our construction.

    更新日期:2020-01-17
  • An Explicit Construction of Optimal Streaming Codes for Channels With Burst and Arbitrary Erasures
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-09-27
    Damian Dudzicz; Silas L. Fong; Ashish Khisti

    This paper presents a new construction of error correcting codes which achieves optimal recovery of a streaming source over a packet erasure channel. The channel model considered is the sliding-window erasure model, with burst and arbitrary losses, introduced by Badr et al. We present a simple construction, when the rate of the code is at least 1/2, which achieves optimal error correction in this setup. Our proposed construction is explicit and systematic. It uses off-the-shelf maximum distance separable (MDS) codes and maximum rank distance (MRD) Gabidulin block codes as constituent codes and combines them in a simple manner. This is in contrast to other recent works, where the construction involves a careful design of the generator or parity check matrix from first principles. The field size requirement which depends on the constituent MDS and MRD codes is also analyzed.

    更新日期:2020-01-17
  • AI Coding: Learning to Construct Error Correction Codes
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-04
    Lingchen Huang; Huazi Zhang; Rong Li; Yiqun Ge; Jun Wang

    In this paper, we investigate an artificial-intelligence (AI) driven approach to design error correction codes (ECC). Classic error-correction code design based upon coding-theoretic principles typically strives to optimize some performance-related code property such as minimum Hamming distance, decoding threshold, or subchannel reliability ordering. In contrast, AI-driven approaches, such as reinforcement learning (RL) and genetic algorithms, rely primarily on optimization methods to learn the parameters of an optimal code within a certain code family. We employ a constructor-evaluator framework, in which the code constructor can be realized by various AI algorithms and the code evaluator provides code performance metric measurements. The code constructor keeps improving the code construction to maximize code performance that is evaluated by the code evaluator. As examples, we focus on RL and genetic algorithms to construct linear block codes and polar codes. The results show that comparable code performance can be achieved with respect to the existing codes. It is noteworthy that our method can provide superior performances to classic constructions in certain cases (e.g., list decoding for polar codes).

    更新日期:2020-01-17
  • Construction of Multiple-Burst-Correction Codes in Transform Domain and Its Relation to LDPC Codes
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-18
    Liyuan Song; Qin Huang; Zulin Wang

    This paper analyzes and explicitly constructs quasi-cyclic (QC) codes for correcting multiple bursts via matrix transformations. Our analysis demonstrates that the multiple-burst-correction capability of QC codes is determined by sub-matrices in the diagonal of their transformed parity-check matrices. By well designing these sub-matrices, the proposed QC codes are able to achieve optimal or asymptotically optimal multiple-burst-correction capability. Moreover, it proves that these codes can be QC low-density parity-check (QC-LDPC) codes, if the diagonal sub-matrices of their transformed parity-check matrices are Hadamard powers of base matrices. Analysis and simulation results show that our QC-LDPC codes perform well over not only random symbol error/erasure channels, but also burst channels.

    更新日期:2020-01-17
  • Rate-Loss Mitigation of SC-LDPC Codes Without Performance Degradation
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-07
    Hee-Youl Kwak; Dae-Young Yun; Jong-Seon No

    In research on spatially-coupled low-density parity-check (SC-LDPC) codes, rate-loss of SC-LDPC codes is one of the main issues to be addressed. One way to mitigate the rate-loss is to attach additional variable nodes with an irregular degree distribution, where the degree distribution is optimized with a constraint that the belief propagation (BP) threshold should not be degraded by attaching variable nodes. However, it is observed that the degree distribution obtained with the BP threshold constraint induces degradation of the finite-length performance. In order to address the problem, we propose new optimization methods to attach additional variable nodes while minimizing performance degradation. The proposed optimization methods are based on several design techniques including the scaling law, local threshold, expected graph evolution, differential evolution algorithms, the use of a protograph structure, and puncturing codewords. Using the optimized structure for additional variable nodes, the rate-loss of SC-LDPC codes can be reduced by more than 53% without sacrificing the finite-length performance. It is also shown that the rate-loss mitigation can be translated into a performance improvement if the proposed and the conventional SC-LDPC codes are compared at the same code rate.

    更新日期:2020-01-17
  • Pilot Assisted Adaptive Thresholding for Sneak-Path Mitigation in Resistive Memories With Failed Selection Devices
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-18
    Zehui Chen; Clayton Schoeny; Lara Dolecek

    Resistive random-access memory (ReRAM) with the crossbar structure is one promising candidate to be used as a next generation non-volatile memory device. In a crossbar ReRAM, in which a memristor is positioned on each row-column intersection, the sneak-path problem is one of the main challenges for a reliable readout. The sneak-path problem can be solved with additional selection devices. When some selection devices fail short, the sneak-path problem re-occurs. The re-occurred sneak-path problem is addressed in this paper. The re-occurred sneak-path event can be described combinatorially and its adverse effect can be modeled as a parallel interference. Based on a simple pilot construction, we probabilistically characterize the inter-cell dependency of the re-occurred sneak-path events. Utilizing this dependency, we propose adaptive thresholding schemes for resistive memory readout using side information provided by pilot cells. This estimation theoretic approach effectively reduces the bit-error rate while maintaining low redundancy overhead and low complexity.

    更新日期:2020-01-17
  • Generalized FFT-Based One-Bit Quantization System for Wideband Spectrum Sensing
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-10
    Abdelmohsen Ali; Walaa Hamouda

    In this paper, we maximize the benefits from the ultra low power wideband sensing approach based on FFT-based 1-bit quantization by addressing the practical limitations to this method. Unlike the conventional architecture that assumes a fully synchronized and coordinated Primary User (PU) network, the proposed system relaxes these limitations by providing an analytical framework for an uncoordinated asynchronous FFT-based 1-bit quantization system. For this system, we analytically derive the sub-band power which is the main parameter for the closed-form expressions representing the false alarm and detection probabilities. Further, improving the system performance through cooperative sensing is considered. While respecting the decision fusion cooperation, the optimum threshold for the generalized FFT-based 1-bit quantization system is derived such that the aggregate error rate is minimized. In addition to its significant power and complexity reduction, the presented analysis expands the use of the FFT-based 1-bit quantization wideband sensing approach in practical deployments. The sensing performance and the analytical results are assessed through comparisons with respective results from computer simulations.

    更新日期:2020-01-17
  • Cooperative Tracking by Multi-Agent Systems Using Signals of Opportunity
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-09-30
    Yunlong Wang; Ying Wu; Yuan Shen

    The omnipresent signals of opportunity (SOOP) enable an effective way for passive target tracking using multiple agents. However, cooperative target tracking via non-cooperative SOOP is challenging since the positions of agents are not precisely known. In this paper, we determine the performance bounds of cooperative tracking using SOOP by multiple asynchronous agents equipped with antenna arrays. The Fisher information matrix of joint target and agent positions can be decomposed as the sum of the information from SOOP and self-localization networks, where the correlation of signals introduces an additional Fisher information component and the multipath effect is characterized by path-overlap coefficients. We demonstrate how the location information coupling between the target and agents affects localization accuracy and how the cooperation among agents improves tracking performance. Moreover, the angular information is shown to mitigate multipath and asynchronous effects by spatiotemporal separation and time-independent measurements, respectively. Then we propose a distributed hybrid belief propagation based algorithm for cooperative tracking and network synchronization via likelihood consensus. Finally, numerical results validate our theoretical analysis and the performance of the proposed algorithm.

    更新日期:2020-01-17
  • The Capacity of Memoryless Channels With Sampled Cyclostationary Gaussian Noise
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-07
    Nir Shlezinger; Emeka Abakasanga; Ron Dabora; Yonina C. Eldar

    Non-orthogonal communications play an important role in future digital communication architectures. In such scenarios, the received signal is corrupted by an interfering communications signal, which is much stronger than the thermal noise, and is often modeled as a cyclostationary process in continuous-time. To facilitate digital processing, the receiver typically samples the received signal synchronously with the symbol rate of the information signal . If the period of the statistics of the interference is synchronized with that of the information signal, then the sampled interference is modeled as a discrete-time (DT) cyclostationary random process. However, in the common interference scenario, the period of the statistics of the interference is not necessarily synchronized with that of the information signal. In such cases, the DT interference may be modeled as an almost cyclostationary random process. In this work we characterize the capacity of DT memoryless additive noise channels in which the noise arises from a sampled cyclostationary Gaussian process. For the case of synchronous sampling, capacity can be obtained in closed form. When sampling is not synchronized with the symbol rate of the interference, the resulting channel is not information stable, thus classic information-theoretic tools are not applicable. Using information spectrum methods, we prove that capacity can be obtained as the limit of a sequence of capacities of channels with additive cyclostationary Gaussian noise. Our results allow to characterize the effects of changes in the sampling rate and sampling time offset on the capacity of the resulting DT channel. In particular, it is demonstrated that minor variations in the sampling period, such that the resulting noise switches from being synchronously-sampled to being asynchronously-sampled, can substantially change the capacity.

    更新日期:2020-01-17
  • Centralized Caching and Delivery of Correlated Contents Over Gaussian Broadcast Channels
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-11-04
    Qianqian Yang; Parisa Hassanzadeh; Deniz Gündüz; Elza Erkip

    Content delivery in a multi-user cache-aided broadcast network is studied, where a server holding a database of correlated contents communicates with the users over a Gaussian broadcast channel (BC). The minimum transmission power required to satisfy all possible demand combinations is studied, when the users are equipped with caches of equal size. Two centralized caching schemes are proposed, both of which not only utilize the user’s local caches, but also exploit the correlation among the contents in the database. The first scheme implements uncoded cache placement and delivers coded contents to users using superposition coding. The second scheme, which is proposed for small cache sizes, places coded contents in users’ caches and jointly encodes the cached contents of users and the messages targeted at them. The performance of the proposed schemes, which provide upper bounds on the required transmit power for a given cache capacity, is characterized. The scheme based on coded placement improves upon the first one for small cache sizes, and under certain conditions meets the uncoded placement lower bound. A lower bound on the required transmit power is also presented assuming uncoded cache placement. Our results indicate that exploiting the correlations among the contents in a cache-aided Gaussian BC can provide significant energy savings.

    更新日期:2020-01-17
  • Performance Analysis of Device-to-Device Aided Multicasting in General Network Topologies
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-10
    Thomas Varela Santana; Richard Combes; Mari Kobayashi

    We consider a Device-to-Device (D2D) aided multicast channel, where a base station (BS) wishes to convey a common message to many receivers and these receivers cooperate with each other. We analyze the performance of a two-phase cooperative multicasting scheme requiring only statistical channel knowledge at the BS. Our analysis reveals that, as the number of receivers K grows, the two-phase scheme guarantees an average multicast rate of $\frac {1 }{ 2} \log _{2}(1 + \beta \ln \text {K})$ with high probability for any $\beta < \beta ^\star $ where $\beta ^\star $ depends on the network topology. This scheme undergoes a phase transition at threshold $\beta ^\star \ln \text {K}$ where transmissions are successful/unsuccessful with high probability when the Signal to Noise Ratio (SNR) is above/below this threshold. We also analyze the multicast outage rate when a target joint decoding probability is fixed. Finally, we propose two enhanced schemes by optimally allocating the time resource between two phases and combining received signals from two phases. 1 1 A part of the results presented in the current manuscript has been presented at the IEEE International Symposium on Information Theory 2018 [1]. The results are published in Chapter 3 of the P.h.D. Thesis of the first author [2].

    更新日期:2020-01-17
  • Analysis of Non-Orthogonal Sequences for Grant-Free RA With Massive MIMO
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-29
    Jie Ding; Daiming Qu; Jinho Choi

    Massive MIMO based grant-free random access (mGFRA) is a promising RA technique for massive access with low signaling overhead. However, due to a limited orthogonal preamble size, preamble collision is a key factor that constrains the success probability of mGFRA. In this paper, we examine the potential of applying non-orthogonal preambles to mitigate the issue, where two typical non-orthogonal sequences, i.e., Gaussian distribution sequences and Zadoff-Chu (ZC) sequences, are taken into account. Asymptotic behaviors of the success probabilities with the non-orthogonal preamble sequences are analyzed and compared using derived closed-forms. Through the analysis we reveal that ZC sequences outperform Gaussian ones. However, though non-orthogonal sequences are able to reduce or even alleviate the preamble collision, they do not necessarily provide better performance than the orthogonal counterpart. In addition, regarding orthogonal sequences as a single-root case of ZC sequences, we show that there exists an optimal number of ZC roots that maximizes the success probability for mGFRA, which is low-bounded by orthogonal baseline. Simulation results evaluate the performance of non-orthogonal sequences in mGFRA under various practical system parameters, and validate our analysis.

    更新日期:2020-01-17
  • Uplink Sum-Rate and Power Scaling Laws for Multi-User Massive MIMO-FBMC Systems
    IEEE Trans. Commun. (IF 5.690) Pub Date : 2019-10-29
    Prem Singh; Himanshu B. Mishra; Aditya K. Jagannatham; K. Vasudevan; Lajos Hanzo

    This paper analyses the performance of filter bank multicarrier (FBMC) signaling in conjunction with offset quadrature amplitude modulation (OQAM) in multi-user (MU) massive multiple-input multiple-output (MIMO) systems. Initially, closed form expressions are derived for tight lower bounds corresponding to the achievable uplink sum-rates for FBMC-based single-cell MU massive MIMO systems relying on maximum ratio combining (MRC), zero forcing (ZF) and minimum mean square error (MMSE) receiver processing with/without perfect channel state information (CSI) at the base station (BS). This is achieved by exploiting the statistical properties of the intrinsic interference that is characteristic of FBMC systems. Analytical results are also developed for power scaling in the uplink of MU massive MIMO-FBMC systems. The above analysis of the achievable sum-rates and corresponding power scaling laws is subsequently extended to multi-cell scenarios considering both perfect as well as imperfect CSI, and the effect of pilot contamination. The delay-spread-induced performance erosion imposed on the linear processing aided BS receiver is numerically quantified by simulations. Numerical results are presented to demonstrate the close match between our analysis and simulations, and to illustrate and compare the performance of FBMC and traditional orthogonal frequency division multiplexing (OFDM)-based MU massive MIMO systems.

    更新日期:2020-01-17
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