Photon counting is an effective detection technique for weak optical signals in underwater optical wireless communications (UOWC). This paper proposes a new approach for power allocation in an uplink $M$ -ary pulse position modulation (PPM), photo-counting non-orthogonal multiple-access (PhC-NOMA) system. Different from existing techniques in photon-counting systems, the new approach supports consistent

The performance of generalized low-density parity-check (GLDPC) codes under binary and ternary message passing decoding (BMP/TMP) is analyzed from a density evolution (DE) perspective. At the check nodes, two types of local decoders are considered, namely optimum a-posteriori probability (APP) soft-input soft-output decoding, and bounded distance decoding (BDD). The purpose is to shed light on the

This paper investigates the performance of a time-switching (TS) based cooperative non-orthogonal multiple access (NOMA) network consisting of a base station (BS), a near user (NU), a distant user (DU), and a full-duplex (FD) relay. The BS shares a direct link to the NU, while communication to the DU is assisted by a battery-aided energy harvesting FD relay. We consider a static battery energy (SBE)

To enhance the outage performance of downlink non-orthogonal multiple access (NOMA) systems, we investigate opportunistic user pair scheduling (UPS) as well as the joint power allocation and decoding order selection (PA-DOS) for the scheduled user pair. Unlike most existing literature where the UPS and PA-DOS schemes are solely driven by channel conditions, we consider the impact of both the channel

Optimizing the energy efficiency (EE) of wireless networks is one of the key priorities in the design of beyond 5G mobile technologies. In this pursuit, the use of new frequency bands, in combination with advanced multiple access protocols and cooperative communications strategies, has recently shown promising results. To this end, this paper investigates an indoor wireless network that aggregates

The Device-to-Device (D2D) communication underlaying cellular networks has advantages of improving the spectral utilization and throughput. This paper studies mode selection and resource allocation scheme for D2D communications underlaying cellular networks aiming to achieve a tradeoff of throughput and user satisfaction. An offline channel state information model based on geographic location is proposed

With the great success of deep learning (DL) in image classification, speech recognition, and other fields, more and more studies have applied various neural networks (NNs) to wireless resource allocation. Generally speaking, these artificial intelligent (AI) models are trained under some special learning hypotheses, especially that the statistics of the training data are static during the training

U-UV codes were recently proposed as a competent short-to-medium length coding scheme. With well designed component codes, U-UV codes can outperform similar rate cyclic redundancy check (CRC)-polar codes with the successive cancellation (SC) and the SC list (SCL) decoding. In order to improve the coded transmission spectral efficiency, this paper proposes the bit-interleaved coded modulation (BICM)

Cell-free massive multiple-input multiple-output (MIMO) can resolve the inter-cell interference issue in cellular networks through cooperative beamforming of the distributed access points (APs). This paper focuses on an uplink cell-free massive MIMO network and investigates novel methods to train the central processing unit (CPU), the APs, and the users in the network. To reduce the communication burden

As one of the most representative random-access schemes, slotted Aloha has been adopted in various wireless communication networks. A multi-cell Aloha network may easily become unstable as the inter-cell interference grows if the traffic input rates and transmission probabilities of nodes are not properly regulated. Yet how to stabilize a multi-cell Aloha network has remained largely unknown. To address

In this paper, we investigate an energy efficient waveform design for integrated visible light positioning and communication (VLPC) systems by exploiting the relationship between visible light positioning (VLP) and visible light communication (VLC). We propose that the direct current component and the alternating current component of the VLPC signals are utilized for positioning and communication,

Spectrum sensing is a key technique for dynamically detecting available spectrum in cognitive radio networks (CRNs), which can introduce high resource demands such as energy consumption. In this paper, we propose a novel cluster-based cooperative sensing-after-prediction scheme where a learning cluster and a sensing cluster are jointly considered to perform cooperative prediction and sensing efficiently

The application of unmanned aerial vehicles (UAVs) in IoT networks, especially data collection, has received extensive attention. Due to the urgency of the mission and limitation of the network cost, the mission completion time and number of UAVs are research hotspots. Most studies mainly focus on the trajectory optimization of the UAV to shorten the mission completion time. However, under different

Distributed optimization is ubiquitous in emerging applications, such as robust sensor network control, smart grid management, machine learning, resource slicing, and localization. However, the extensive data exchange among local and central nodes may cause a severe communication bottleneck. To overcome this challenge, over-the-air computing (AirComp) is a promising medium access technology, which

This paper studies a downlink secure integrated sensing and communication (ISAC) system, in which a multi-antenna base station (BS) transmits confidential messages to a single-antenna communication user (CU) while performing sensing on targets that may act as suspicious eavesdroppers. To ensure the quality of target sensing while preventing their potential eavesdropping, the BS combines the transmit

In this paper, due to the important value in practical applications, we consider the coded distributed matrix multiplication problem of computing $AA^{\top} $ in a distributed computing system with $N$ worker nodes and a master node, where the input matrices $A$ and $A^{\top} $ are partitioned into $m$ -by- $p$ and $p$ -by- $m$ blocks of equal-size sub-matrices respectively. For effective straggler

Reconfigurable intelligent surface (RIS) is able to enhance the capacity of wireless communication systems with low overhead. Extremely large (XL)-RIS-aided millimeter-wave (mmWave) communication has become a promising key technique for future 6-th Generation (6G) systems. The performance gain brought in by XL-RIS relies on the accurate channel state information (CSI). However, channel estimation requires

Reconfigurable intelligent surface (RIS) has been deemed as one of potential components of future wireless communication systems because it can adaptively manipulate the wireless propagation environment with low-cost passive devices. However, due to the severe double path loss, the traditional passive RIS can provide sufficient gain only when receivers are very close to the RIS. Moreover, RIS cannot

This paper investigates the joint transceiver design for full-duplex (FD) multiple-input multiple-output relay systems where the direct link (DL) and nonlinear successive-interference-cancellation (SIC) detection are considered. The objective is to jointly optimize the source precoder, relay precoder, and receiver such that the resultant symbol-vector error rate (SVER) is minimized. The joint design

The wireless in-band full-duplex (IBFD) technology can in theory double the system capacity over the conventional frequency division duplex (FDD) or time-division duplex (TDD) alternatives. But the strong self-interference of the IBFD can cause excessive quantization noise at the output of the analog-to-digital converters (ADCs), which hampers its real implementation. Fortunately, the reconfigurable

A reduced complexity algorithm is presented for computing the log-likelihood ratios (LLRs) arising in the successive cancellation (SC) decoder for polar codes with large kernels of arbitrary dimension. The proposed algorithm exploits a recursive trellis representation of the codes generated by submatrices of the polarization kernel and enables polar codes based on large kernels to be decoded with lower

Molecular communication (MC) is an emerging field aiming at realizing information exchange via chemical signals between nanomachines in nanonetworks. Information transmission that is energy-efficient and relies on relatively low-complexity transceiver techniques is of practical importance for MC systems. Based on the fact that constellation shaping can improve energy efficiency, in this paper, we propose

Rapid and efficient sensor data acquisition plays a critical role in the decision-making process of each robot in a multi-robot smart factory. This paper investigates the trajectory design of autonomous mobile robots (AMRs) and communication resource allocation problems in industrial Internet of Things. Specifically, by exploiting both power and spatial domains, we adopt non-orthogonal multiple access

An approximated channel model is proposed for direct signaling on the continuous spectrum of a nonlinear frequency division multiplexed (NFDM) communication system, describing the effect of noise and nonlinearity at the receiver. The optimal input distribution that maximizes the mutual information of the proposed approximated channel under the peak amplitude constraint is then studied. We present that

To support extremely high data rates in 6G wireless networks, reconfigurable intelligent surface (RIS)-assisted terahertz (THz) communications have gained much attention in recent years. By manipulating the phase shifts of reflecting elements, the RIS can proactively adjust the wireless propagation environment of THz systems, thereby enhancing the overall throughput significantly. To realize the full

The active intelligent reflecting surface (IRS) can amplify the incident signal besides reflecting, thus alleviating the double-fading effect of the cascaded link. However, if the interference caused by the cascaded link cannot be effectively cancelled, the alleviated effect may result in increased interference among users, thus limiting the performance gain brought by the active IRS. To this end,

The seamless and ubiquitous wireless access is crucial to the immersive experiences in the metaverse. Considering the limited communication and computing resources, how to provide metaverse services with high Quality of Experience (QoE) for users is still challenging. In this paper, an innovative QoE model for metaverse services based on the virtual distance and network effect is proposed. Especially

Symbiotic radio has emerged as a promising technology for spectrum- and energy-efficient wireless communications, where the passive secondary backscatter devices (BDs) reuse not only the spectrum but also the power of the active primary users to transmit their own information. In return, the primary communication links can be enhanced by the additional multipaths created by the BDs. This is known as

Remote first-aid treatment on ambulances is a promising application of 5G. However, there still exist gaps between the capabilities of current 5G networks and the stringent requirements of remote emergency on ambulances. Dual connectivity (DC) is an efficient technology to fill these gaps by integrating 5G millimeter wave (mmWave) with Sub-6GHz networks. In this paper, we investigate a dual-connectivity

Channel fading can have a strong impact on the convergence of over-the-air federated edge learning (OTA-FEEL). This paper develops a new and optimal power control policy to minimize the optimality gap of OTA-FEEL under any independently and identically distributed fading. Specifically, we reveal that the optimal power control policy takes a structure where the variance of the effective channel from

Deep integration of wireless power transmission and mobile edge computing (MEC) promotes wireless powered MEC to become a new research hotspot in the field of Internet of Things. In this paper, we focus on the joint optimization problem of online offloading decision and charging resource allocation for minimizing task accomplishing time in dynamic time-varying wireless channel scenarios. The optimal

To efficiently exploit the massive amounts of raw data that are increasingly being generated in mobile edge networks, federated learning (FL) has emerged as a promising distributed learning technique by collaboratively training a shared learning model on edge devices. The number of resource blocks when using traditional orthogonal transmission strategies for FL linearly scales with the number of participating

In optical wireless communications (OWC), hybrid optical orthogonal frequency division multiplexing (O-OFDM) schemes, such as hybrid asymmetrically clipped O-OFDM (HACO-OFDM) and layered asymmetrically clipped O-OFDM (LACO-OFDM), enjoy both high power and spectral efficiency. However, due to the non-orthogonal transmission of signal components induced by the clipping distortion, successive interference

In general, the generator matrix sparsity is a critical factor in determining the encoding complexity of a linear code. Further, certain applications, e.g., distributed crowdsourcing schemes utilizing linear codes, require most or even all the columns of the generator matrix to have some degree of sparsity. In this paper, we leverage polar codes and the well-established channel polarization to design

Deep learning (DL) demonstrates tremendous potential in high-mobility communication systems, especially from the perspective of signal detection. However, most existing DL-based detection methods are data/environment specific and the re-training process is resource intensive. To address these shortcomings, we propose a contrastive learning-based environmentally robust signal detection approach in orthogonal

Intelligent reflecting surface (IRS) has emerged as a cost-efficient technique to improve the wireless network’s capacity and performance. Existing works on IRS have mainly considered IRS being deployed in the environment to dynamically control the wireless channels between the base station (BS) and its served users in favor of their communications. In contrast, we propose in this paper a new integrated

Due to the ability of feature extraction, deep learning (DL)-based methods have been recently applied to channel state information (CSI) compression feedback in massive multiple-input multiple-output (MIMO) systems. Existing DL-based CSI compression methods are usually effective in extracting a certain type of features in the CSI. However, the CSI usually contains two types of propagation features

Taking inspiration from linguistics, the communications theoretical community has recently shown a significant recent interest in pragmatic, or goal-oriented, communication. In this paper, we tackle the problem of pragmatic communication with multiple clients with different, and potentially conflicting, objectives. We capture the goal-oriented aspect through the metric of Value of Information (VoI)

Deep neural networks (DNNs) are emerging as a potential solution to solve NP-hard wireless resource allocation problems. However, in the presence of intricate constraints, e.g., users’ quality-of-service (QoS) constraints, guaranteeing constraint satisfaction becomes a fundamental challenge. In this paper, we propose a novel unsupervised learning framework to solve the classical power control problem

In this paper, a novel three-dimensional (3D) non-stationary massive multiple-input multiple-output (MIMO) channel model for shortwave communication systems is proposed. Three transmission modes, i.e., groundwave, near vertical incident skywave (NVIS), and long-distance skywave are considered to eliminate the blind area and realize the full-coverage for shortwave communication. The ionospheric absorption

Over-the-air computation (OAC) is a promising technology that can achieve rapid model aggregation by utilizing the wireless waveform superposition feature to harness the interference of multiple-access channel for wireless federated learning (FL). However, OAC-based aggregation for OAC faces critical security challenges due to unfavorable and wireless broadcast properties, such as privacy leaks and

In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform planar array (UPA), a multi-antenna base station (BS) is targeted for simultaneously sensing multiple targets in the non-light-of-sight (NLoS) region and communicating with multiple communication

Ternary AIFV codes are almost instantaneous fixed-to-variable length codes, and are constructed based on two code trees. It is known that the redundancy of ternary AIFV codes is no more than one. In this paper, we provide a tighter upper bound on the redundancy of the ternary Huffman codes when the greatest probability of the source $p_{max}$ is known. As a result, the redundancy of the optimal ternary

Molecular Communication via Diffusion (MCvD) is a prominent small-scale technology, which roots from the nature. With solid analytical foundations on channel response and advanced modulation techniques, molecular single-input-single-output (SISO) systems are one of the most studied molecular networks in the literature. However, the literature is yet to provide sufficient analytical channel modeling

This paper analyzes and optimizes the average Age of Information (AAoI) of Frame Slotted ALOHA with Reservation and Data slots (FSA-RD) in a multi-access network, where multiple users transmit their randomly generated status updates to a common access point in a framed manner. Each frame consists of one reservation slot and several data slots. The reservation slot is further split into several mini-slots

Jamming attacks to hinder communication capabilities are becoming a critical aspect of wireless networks. A challenging issue is the detection of reactive jammers that perform spectrum sensing and attack the network only when legitimate communication is in progress. In this scenario, we introduce a novel framework for reactive jamming detection using a patrol of radio-frequency (RF) sensors external

Information-theoretic secure (ITS) authentication is an essential part of a quantum key distribution (QKD) system. In the QKD network, the authentication scheme based on the ITS QKD keys pre-shared by the QKD system. However, such a scheme is subject to the limitation that consumes a significant amount of authentication keys when the scale and communication requirements of QKD networks grow. To address

Despite the extreme error-correction performance, the amount of computation of sequential decoding of the polarization-adjusted convolutional (PAC) codes is random. In sequential decoding of convolutional codes, the cutoff rate denotes the region between rates whose average computational complexity of decoding is finite and those which is infinite. In this paper, by benefiting from the polarization

Ultra-reliable short-packet communication is a major challenge in future wireless networks with critical applications. To achieve ultra-reliable communications beyond 99.999%, this paper envisions a new interaction-based communication paradigm that exploits feedback from the receiver. We present AttentionCode, a new class of feedback codes leveraging deep learning (DL) technologies. The underpinnings

An orthogonal affine-precoded superimposed pilot (AP-SIP)-based architecture is developed for the cyclic prefix (CP)-aided single input single output (SISO) and multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) systems relying on arbitrary transmitter-receiver (Tx-Rx) pulse shaping. The data and pilot symbol matrices are affine-precoded and superimposed in the delay Doppler

We propose a non-uniform joint pilot design and channel estimation (JPDCE) scheme in closed-loop orthogonal frequency-division multiplexing (OFDM) systems. Specifically, the encoder of the proposed JPDCE scheme is composed of two sub-networks which are used for pilot location assignment and pilot power allocation, respectively. To ensure accurate learning of the pilots, the OFDM block consisting of

Dynamic index coding is a practical generalization of conventional index coding that deals with real dynamic traffic streams. We identify the code-constrained capacity region of a dynamic index coding problem with a complete bi-directional side information graph and introduce the performance metric of dynamic index coding gain to measure how dynamic index coding reduces the required data transmissions

In this manuscript, an innovative method for the detection and the estimation of multiple targets in a radar system employing orthogonal frequency division multiplexing is illustrated. The core of this method is represented by a novel algorithm for detecting multiple superimposed two-dimensional complex tones in the presence of noise and estimating their parameters. This algorithm is based on a maximum

Reverse analysis of the intercepted signal to reconstruct the communication scheme used by the transmitter is a key problem in the non-cooperative context. In this paper, we propose a new algorithm for the joint blind reconstruction of the cyclic codes and self-synchronous scramblers directly using soft-decision sequences. First, we derive the conclusion that if the parity polynomial of the factor

In conventional approach, the bit error probability (BEP) expressions of $M$ -ary phase-shift keying (MPSK) signals over additive white Gaussian noise (AWGN) channel are derived by averaging error probabilities for all bits of MPSK symbol. The closed-form BEP expressions of MPSK signals over AWGN channel can also be derived by using the weighted conditional symbol error probability (SEP) expressions

In this paper, we propose a robust max-min fairness transmission design for intelligent reflecting surface (IRS)-aided wireless network in the presence of user location uncertainty. In particular, the non-isotropic reflection property for the IRS element is considered. We investigate the joint design of the active transmit beamformer at the base station (BS) and the passive phase shift matrix along

This paper investigates double RIS-assisted MIMO communication systems over Rician fading channels with finite scatterers, spatial correlation, and the existence of a double-scattering link between the transceiver. First, the statistical information is driven in closed form for the aggregated channels, unveiling various influences of the system and environment on the average channel power gains. Next

The rapid proliferation of smart devices and Internet of Things (IoT) applications have brought significantly increased demands for concurrent sensing, localization and communication services. To achieve multiple functions concurrently, new unified wireless systems including integrated localization and communication (ILAC) and integrated sensing and communication (ISAC) are facing the fundamental challenge

In conventional dual-function radar-communication (DFRC) systems, the radar and communication channels are routinely estimated at fixed time intervals based on their worst-case operation scenarios. Such situation-agnostic repeated estimations cause significant training overhead and dramatically degrade the system performance, especially for applications with dynamic sensing/communication demands and

Space-air-ground integrated networks (SAGIN) have become a research hotspot facing the next generation of communications. The theoretical analysis for non-terrestrial networks (NTN) is significant before applying them in practical scenarios, but the existing works failed to provide a general analysis approach for NTN. Against this background, multiple satellites and civil aircrafts (CAs) are modeled