This letter investigates an overlay cognitive Alamouti’s space-time block code-aided non-orthogonal multiple access (STBC-NOMA) system. Approximate closed-form expressions for the system throughput (ST) and the outage probability (OP) of both the primary and secondary networks under imperfect successive interference cancellation (SIC) are derived over Rayleigh fading channels. Moreover, asymptotic

This letter considers an intelligent reflecting surface(IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy from a power station (PS) in the downlink (DL) and then transmit information using non-orthogonal multiple access (NOMA) to a data sink in the uplink (UL). However, most existing works on WPCNs adopted the simplified linear energy-harvesting model and

This letter addresses adaptive channel estimation for OFDM systems to reduce computational complexity. There are numerous methods suggested for low-complexity channel estimation, but some of them still suffer from a considerable complexity or performance degradation due to the channel energy leakage. We present an adaptive channel estimator based on the channel impulse response (CIR) length estimate

This letter addresses the localization problem of a directional source in non-line-of-sight (NLOS) environments. To estimate both the position and the orientation of the source, we propose an iterative algorithm that skillfully adopts the received-signal-strength (RSS) and time-of-arrival (TOA) measurements. The algorithm is derived by converting the non-convex estimating problem into a generalized

To achieve the joint active and passive beamforming gains in the reconfigurable intelligent surface assisted millimeter wave system, the reflected cascade channel needs to be accurately estimated. Many strategies have been proposed in the literature to solve this issue. However, whether the Cramér-Rao lower bound (CRLB) of such estimation is achievable still remains uncertain. To fill this gap, we

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Provides a listing of current committee members and society officers.

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Distributed congestion control (DCC) improves system performance by lowering channel congestion in vehicular environments with high vehicle density. The 3rd Generation Partnership Project standard defines the related metrics of channel busy ratio (CBR) and introduces possible rate and power control mechanisms to mitigate channel congestion in cellular vehicle-to-everything (C-V2X) sidelink. However

An improved mean squared error (MSE) minimization solution based on eigenvector decomposition approach is conceived for wideband non-orthogonal multiple-access based computation over multi-access channel (NOMA-CoMAC) framework. This work aims at further developing NOMA-CoMAC for next-generation multimodal sensor networks, where a multimodal sensor monitors several environmental parameters such as temperature

A reconfigurable intelligent surface (RIS) consists of massive meta elements, which can improve the performance of future wireless communication systems. Existing RIS-aided channel estimation methods try to estimate the cascaded channel directly, incurring high computational and training overhead especially when the number of elements of RIS is extremely large. In this letter, we propose a cost-efficient

Direction of arrival (DOA) estimation with coprime array is an important topic in array signal processing. In this letter, the coprime array technique is extended to mixed noise (white Gaussian noise and impulsive noise). Since the second order covariance matrix does not exist in presence of mixed noise, the phased fractional low-order moment (PFLOM) is used to replace the data covariance matrix of

This work revolves around lightwave power transfer networks in which we aim to maximize the number of users served while simultaneously minimizing the transmit power. By formulating the problem as a reinforcement learning (RL) problem, we propose the use of the evolution strategies (ES) method as a novel solution. In this context, ES is a heuristic search method inspired from the biological evolution

In this work, we consider reliable transmissions for grant-free random access (GFRA) when machine-type communication (MTC) devices have a message of multiple short data packets to transmit. An existing approach is based on ${K}$ -repetition for reliable transmissions. In order to improve the reliability, a random network coding based scheme is proposed, where each device in GFRA employs random network

In this letter, a novel deep learning-based IoT device transmission interval management scheme for enhanced scalability that reduces the redundancy data measurement in LoRa networks is proposed. For this purpose, a Local LSTM prediction model of each cluster is proposed in which the devices are clustered based on the features of the extracted data using an autoencoder. By adjusting the device transmission

This letter presents a tensor-based joint AoA and ToF estimation method using the channel state information for Wi-Fi systems. Our method can mitigate the estimation error caused by the signal phase offset and noise interference using linear regression and discrete wavelet transform, respectively. Moreover, the Cramér-Rao lower bound for joint AoA and ToF estimation is derived for performance evaluation

Both reconfigurable intelligent surfaces (RISs) and ultra-dense (UD) small-cell (SC) base stations (BSs) are investigated for indoor mmWave wireless coverage enhancement. To explore which deployment strategy is more cost-effective, the costs of deploying both RISs and UD SCs are defined and calculated. Through jointly analyzing coverage probability and network cost in typical indoor environments, we

This letter studies a multi-access edge computing assisted predictive adaptive video streaming scheme for on-road driving scenarios based on deep reinforcement learning (DRL). By judiciously designing the state and the reward, the user movement awareness is integrated into our scheme, which enables it to make proactive decisions that can maximize the long-term quality of experience. To enhance the

Radio frequency fingerprint (RFF) has been utilized to mitigate spoofing attacks in open wireless environments, making use of the inherent characteristics of hardware. However, most existing RFF technologies are data-dependent, e.g., based on preambles or synchronization sequences. In this letter, we propose a novel data-independent RFF extraction scheme, called Least mean square-based Adaptive Filter

This work studies an unmanned aerial vehicle (UAV)-assisted wireless communication system where UAV acts as an aerial base station (BS) and serves multiple ground users simultaneously using rate-splitting multiple access (RSMA). We propose a new architecture called RSMA-UAV that leverages the interplay between rate-splitting (RS) and UAV and shows the effect of RSMA on system performance. Further,

This letter studies an intelligent reflecting surface (IRS)-aided downlink ultra-reliable and low-latency communication (URLLC) system, in which an IRS is dedicatedly deployed to assist a base station (BS) to send individual short-packet messages to multiple users. To enhance the URLLC performance, the users are divided into different groups and the messages for users in each group are encoded into

Automatic modulation classification in the manner of pattern recognition has caught massive attention due to its simplicity in workflow design. Recently, enormous interest has been aroused because of the boosting development of deep learning and numerous network structures, leading to various substantial contributions. However, to the best of our knowledge, current approaches fail to handle two essential

Orthogonal time frequency space (OTFS) modulation is a newly proposed modulation technique for providing a solution to high mobility doubly dispersive channel problems. In several recent research works, it is shown that OTFS has better performance over the existing conventional multicarrier modulations. OTFS modulate information symbols in a two-dimensional (2D) delay-Doppler domain rather than in

Intelligent reflecting surface (IRS) is a promising technology to improve the performance of backscatter communication systems by smartly reconfiguring the multi-reflection channel. To fully exploit the passive beamforming gain of IRS in backscatter communication, channel state information (CSI) is indispensable but more practically challenging to acquire than conventional IRS-assisted systems, since

Fulfilling the diverse communication requirements of heterogeneous users is envisioned to be one of the key challenges in cognitive radio-enabled IoT networks. To this end, we propose a novel scheme focused on multi-tier prioritized and heterogeneous regime of users and reservation-based resources allocation. The proposed scheme manipulates the secondary users’ (SUs’) heterogeneity based on their priorities

Underwater wireless optical communication (UWOC) has attracted considerable attention as a technology with high data rates and low time delays. However, the light scattering in water spreads beam pulse temporally, thereby resulting in time-varying underwater optical channels with inter-symbol interference (ISI) especially when the data rate is very high. To overcome this problem, in this letter, a

This letter studies the information freshness in an industrial Internet of Things (IIoT) network, measured by Age of Information (AoI). We consider a scenario where a sink node collects information update packets from different sensors and then uploads the collected packets to an edge server. This scenario has two main requirements: high information freshness (low AoI) and high reliability (low packet

One-bit analog-to-digital converter (ADC), performing signal sampling as an extreme simple comparator, is an overwhelming technology for spectrum sensing due to its low-cost, low-power consumptions and high sampling rate. In this letter, we propose a novel one-bit sensing approach based on the eigenvalue moment ratio (EMR), which has been proved to be highly efficient for conventional multi-antenna

Intelligent reflecting surface (IRS) is an emerging technology to enhance the spectral and energy efficiency of wireless communications cost-effectively. This letter considers a new multi-IRS aided wireless network where a cascaded line-of-sight (LoS) link is established between the base station (BS) and a remote user by leveraging the multi-hop signal reflection of selected IRSs. As compared to the

This letter investigates the minimum-delay data aggregation scheduling problem for wireless powered Internet of Things (WPIoT). Unlike traditional Internet of Things (IoT), WPIoT devices should harvest enough energy before data transmission or reception. Hence, many existing solutions for traditional IoT cannot be directly applied to WPIoT. In this letter, we propose a delay-efficient algorithm by

In this letter, a multi-user cooperative computing framework is applied to enable mobile users to utilize available computing resources from other neighboring users via direct communication links. An incentive scheme based on Bertrand game is proposed for the user to determine who and how to cooperate. We model the resource demand users as buyers who aim to use minimal payments to maximize energy savings

This letter investigates the secure transmission in a multi-user massive MIMO system over Ricean fading channel in the presence of a multi-antenna eavesdropper. In order to reduce the system complexity and the channel estimation overhead, a low-complexity beamforming (BF) scheme using only the specular component is presented. Moreover, the generation of artificial noise (AN) is employed at the base

Traditional studies on Instantly Decodable Network Coding (IDNC) focus on optimizing IDNC metrics, i.e., completion time or decoding delay, in broadcast scenarios in which all user-devices (UDs) want the same files. The problem of joint optimization over two interdependent parameters, i.e., transmitting user-devices (UDs) and IDNC was traditionally tackled by finding the set of feasible cooperation

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In this letter, we propose a deep learning-based spreading sequence design and active user detection (AUD) to support massive machine-type communications (mMTC) where a large number of devices access the base station using non-orthogonal spreading sequences. To design the whole communications system minimizing AUD error, we employ an end-to-end deep neural network (DNN) where the spreading network

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This letter studies one-to-many capacity allocation pairings in multi-beam high throughput satellite networks employing smart gateway diversity. The minimization of total network’s capacity losses and rate matching metrics are examined. To approach the aforementioned binary optimization problems, a two-step heuristic scheme is proposed. Firstly a continuous pairing solution is given based on difference

The Internet of Things (IoT) framework requires a massive number of connection thus demanding spectral efficient solutions such as Non-Orthogonal Multiple Access (NOMA). However, the main drawback of NOMA with successive interference canceler (SIC)-based detectors is the error floor in the uplink. In this letter, a reliable multi-user detection in uplink IoT NOMA is guaranteed by a Joint Maximum-Likelihood

This letter studies a multi-user intelligent reflecting surface (IRS)-assisted wireless powered communication networks (WPCN) system. Specifically, a multi-antenna energy station (ES) transmits energy signal to multiple single-antenna users assisted by an IRS. Then users use the harvested energy to transmit respective data to a single-antenna information station (IS) assisted by another IRS. Under

Sums of Weibull variates arise in several communications fields, such as optical, mobile, and radar systems. However, due to the intricate task of evaluating the Weibull sums, only a few works deal with the exact sum statistics. Some of these works provide solutions in terms of nested infinite sums-products, approximate solutions, or in terms of especial functions that, unfortunately, have not yet

We study over-the-air model aggregation in federated edge learning (FEEL) systems, where channel state information at the transmitters (CSIT) is assumed to be unavailable. We leverage the reconfigurable intelligent surface (RIS) technology to align the cascaded channel coefficients for CSIT-free model aggregation. To this end, we jointly optimize the RIS and the receiver by minimizing the aggregation

Recent investigations of Internet of Things network traffic suggest the failure of traditionally used Poisson process-based models. The paper substantiates this finding by performing statistical analysis of packets inter-arrival time in publicly available datasets of IoT-based sensor data traffic. It is observed that gamma distribution fits well to the inter-arrival time of packets. Motivated by this

Phase wrapping is a major problem in direction-of-arrival (DOA) estimation using phase-difference observations. For an antenna pair with an inter-antenna spacing greater than half of the wavelength ( $\lambda /2$ ) of the signal, phase wrapping occurs at certain DOA angles leading to phase-difference ambiguities. Existing phase unwrapping methods exploit either frequency or spatial diversity. These

Automatic modulation classification (AMC) is of crucial importance for realizing wireless intelligence communications. Many deep learning based models especially convolution neural networks (CNNs) have been proposed for AMC. However, the computation cost is very high, which makes them inappropriate for beyond the fifth generation wireless communication networks that have stringent requirements on the

In this letter, we propose a near-optimal low-complexity frequency-domain (FD) harmonic receiver for visible light communication based unipolar frequency-shift keying (U-FSK). The time-domain (TD) maximum-likelihood (ML) receiver for U-FSK is computationally complex, while the sub-optimal receiver increases the noise variance. The proposed harmonic receiver determines the transmitted frequency from

Multi-carrier non-orthogonal multiple access (MC-NOMA) system has been considered as a promising candidate in future wireless networks. In a MC-NOMA system, the available bandwidth of transmission is divided into several sub-bands, such that multiple users in each sub-band are served based on power-domain NOMA. Unlike the equal sub-band allocations, we propose a sum-rate maximization technique that

In this letter, a connected dominating set based on-demand routing (CDS-OR) mechanism is proposed for wireless ad hoc networks. We argue that there exists a trade-off between CDS size and the amount of information exchanged for CDS formation in a fully distributed ad hoc network. Smaller CDS size is beneficial and essential in minimizing the routing cost, but the amount of information exchanged (via

This letter proposes a novel design of reconfigurable intelligent surface (RIS) to enhance the physical layer security (PLS) in the RIS-aided non-orthogonal multiple access (NOMA) network. Under the design of the RIS, the problem of increasing the number of RIS elements damaging the secrecy performance is solved. Besides, it also ensures that the networks can use traditional channel coding schemes

Deep learning is considered one of promising tools to develop intelligent wireless techniques in the fifth-generation (5G) wireless communication systems. However, existing researches are conducted based on the channel datasets in fourth-generation (4G) wireless communications systems. Also, some 5G nonstandard channel dataset generators are proposed for frontier technology research. However, these

We introduce Distance-Based Scheduling (DBS), a new technique for user selection in downlink multi-user communications with extra-large (XL) antenna arrays. DBS categorizes users according to their equivalent distance to the antenna array. Such categorization effectively accounts for inter-user interference while largely reducing the computational burden. Results show that ( ${i}$ ) DBS achieves the

5G micro infrastructure comprising micro and picocells would play a pivotal role in densifying the network to provide ample coverage. However, a disproportional association of mobile devices with these small cells would cause hotspots and load imbalance. In such a network, a few micro or picocells suffer from network congestion. While many others are underutilized, experience lower throughput, and

This letter proposes a novel interference mitigation technique for spectral coexistence between large-scale non-geostationary orbit (NGSO) satellite systems by optimizing satellite antenna beam pointing. Firstly, a dynamic exclusion zone of NGSO satellite antenna beam pointing is defined. Secondly, we transfer frequency compatibility problem between NGSO systems into a constrained nonlinear multivariate

Modulation identification, a major task of intelligent receivers, is of vital importance for applications in military and civilian fields. In this work, we develop and analyze a blind modulation identification algorithm for two-path successive relaying systems. Analytical expressions for the correlation functions adopted as the basis of the proposed algorithm are derived, and the computational cost

We consider an ambient backscatter communication (AmBC) system aided by an intelligent reflecting surface (IRS). The optimization of the IRS to assist AmBC is extremely difficult when there is no prior channel knowledge, for which no design solutions are currently available. We utilize a deep reinforcement learning-based framework to jointly optimize the IRS and reader beamforming, with no knowledge

This letter investigates a wireless communication system deploying distributed reconfigurable intelligent surfaces (RISs). Existing works have assumed that perfect timing synchronization is available among all the cooperative RISs. For practical considerations, we first study cooperative reflection design for multi-RIS-aided communication systems taking into account timing synchronization errors. We

Coordinated Beamforming (CB) is an effective technique to maximize weighted sum rate (WSR) targeting at on-demand network capacity. However, the channel state information (CSI) of the base stations (BSs) far away can’t be measured accurately, which will lead to the invalidation of the traditional WSR-maximization beamformer design and eventually result in capacity decrease. This letter proposes a tractable