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This paper considers the downlink of a cognitive radio (CR) network formed by multiple primary and secondary transmitters, where each multiantenna transmitter serves a preknown set of single-antenna users. This paper assumes that the secondary and primary transmitters can simultaneously transmit their data over the same frequency bands to achieve high system spectrum efficiency. This paper considers the downlink balancing problem of maximizing the minimum signal-to-interference-plus-noise ratio (SINR) of the secondary transmitters subject to both the total power constraint of the secondary transmitters and the maximum interference constraint at each primary user due to secondary transmissions. This paper proposes solving the problem using the alternating direction method of multipliers, which leads to a distributed implementation through limited information exchange across the coupled secondary transmitters. This paper additionally proposes a solution that guarantees feasibility at each iteration. Simulation results demonstrate that the proposed solution converges to the centralized solution in a reasonable number of iterations. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays. [ABSTRACT FROM PUBLISHER]

The intelligent radio is a novel emerging paradigm catching on in many practical applications, in order to provide context awareness techniques, able to learn by the environment conditions applying machine learning frameworks. The channel state information (CSI) prediction is one of the main challenges that an intelligent radio has to face with. This paper deals with the CSI prediction in the case of a buffer aided relaying communication scheme with adaptive link selection previously proposed in the literature where a direct source-destination link is not available and with both links affected by an independent fading. In particular, the CSI prediction has been reduced here to a time series prediction problem, performed by involving the usage of the recurrent neural networks. Finally, the validation of the effectiveness of the proposed intelligent radio buffer-aided relaying scheme with adaptive link selection approach has been pursued by presenting performance comparisons with the previously proposed scheme under the assumption of an ideal and actual CSI estimations, respectively. [ABSTRACT FROM AUTHOR]

In concurrent spectrum sharing scenarios between radars and wireless communication systems, one strict approach to protect the radar from undesired interference is locating the base stations outside a guard (or exclusion) zone of the radar. As a result, users inside that zone experience bad communication coverage. This paper uses Reconfigurable Intelligent Surfaces (RISs) to improve the base station coverage of users in the radar exclusion zone. The paper shows, through analysis and simulation, that joint optimization of base station and RIS locations improves the probability of coverage in the exclusion zone over the shared spectrum without disturbing the radar operation. [ABSTRACT FROM AUTHOR]

In this paper, we study the average throughput performance of energy beamforming in a multi-antenna wireless-powered communication network (WPCN). The considered network consists of one hybrid access point (AP) with multiple antennas and a single-antenna user. The user has no constant power supply and, thus, needs to harvest energy from the signals broadcast by the AP in the downlink (DL) before sending its data back to the AP with the harvested energy in the uplink (UL). We derive closed-form expressions of the average throughput and their asymptotic expressions at a high SNR for both delay-limited and delay-tolerant transmission modes. The optimal DL energy harvesting time, which maximizes the system throughput, is then obtained for high SNR. All analytical expressions are validated by numerical simulations. The impact of various parameters, such as the AP transmit power, the energy harvesting time, and the number of antennas, on the system throughput is also investigated. [ABSTRACT FROM AUTHOR]

In traditional spectrum sensing, binary hypothesis testing has been used to detect whether a frequency band is being occupied by the primary user or not. In this correspondence paper, we investigate $M$ -ary hypothesis testing for spectrum sensing to further identify the signal type of the primary user. Linear cooperation among spatially distributed cognitive radios is applied to combine the observation statistics and make a final decision. The problem of data fusion is formulated as minimizing the total probability of misclassification subject to the constraint on the probability of successful classification. To deal with the non-convex problem formulated, we develop two solutions in this paper. In the first solution, we transform the problem into an unconstrained one, and adopt a zooming-based search algorithm to iteratively update multiple continuous variables until convergence. This solution requires searching all possible combinations of variables. To reduce the computation complexity and achieve closed-form analytical expressions, in the second solution, we decompose the original problem into multiple subproblems, each with the objective of minimizing an individual probability of misclassification. These subproblems can lead to closed-form expressions, and the weights are chosen as the best ones that correspond to the minimum total probability of misclassification. The proposed solutions are examined numerically, and the results show that the decomposition-based solution can achieve performance comparable to the zooming-based one but with much less complexity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate device-to-device (D2D) communication networks which are one of the key technologies for next-generation mobile communication networks and many other applications such as unmanned aerial vehicles (UAVs), vehicle-to-vehicle (V2V), and Internet of things (IoT). The overlay D2D communication networks that are considered in our study use dedicated radio resources separate from what cellular networks use and there exists co-channel interference in D2D networks without cross-channel interference between two networks. We propose a new transmission scheme for overlay D2D networks that uses a dueling deep reinforcement learning (DRL) architecture. The DRL is especially effective in environments where actions do not affect subsequent states as in wireless communication networks. The main contribution of this paper is that the proposed architecture is designed to utilize only information that each D2D devices can easily obtain by measuring channels. The proposed scheme thus enables D2D devices to train their own neural networks and to decide autonomously whether to transmit data without any intervention from infrastructures. The performance of the proposed scheme is analyzed in terms of average sum-rates and is compared to three baseline schemes. Simulation results show that the proposed scheme can achieve almost optimal sum-rates with low signal-to-noise (SNR) values without any intervention from infrastructure. [ABSTRACT FROM AUTHOR]

This paper considers the problem of user association to small-cell base stations (SBSs) in a heterogeneous and small-cell network (HetSNet). Two optimization problems are investigated, namely, maximizing the set of associated users to the SBSs (the unweighted problem) and maximizing the set of weighted associated users to the SBSs (the weighted problem), under signal-to-interference-plus-noise ratio constraints. Both problems are formulated as linear integer programs. The weighted problem is known to be NP-hard, and in this paper, the unweighted problem is proved to be NP-hard as well. Therefore, this paper develops two heuristic polynomial-time algorithms to solve both problems. The computational complexity of the proposed algorithms is evaluated and is shown to be far more efficient than the complexity of the optimal brute-force (BF) algorithm. Moreover, this paper benchmarks the performance of the proposed algorithms against the BF algorithm, the branch-and-bound CPLEX-based algorithm, and state-of-the-art algorithms, through numerical simulations. The results demonstrate the close-to-optimal performance of the proposed algorithms. They also show that the weighted problem can be solved to provide solutions that are fair between users or to balance the load among SBSs. [ABSTRACT FROM PUBLISHER]

This paper analyzes the performance of the recently proposed quadrature spatial modulation (QSM) multiple-input–multiple-output (MIMO) system over Nakagami- $m$ fading channel. In the analysis, the general distribution of the Nakagami- m$ channel phase is considered. In the literature, performance analysis of spatial modulation (SM) over Nakagami- m$ channel with uniform phase is conducted. However, apart from the very special case of , where Nakagami- $m$ fading corresponds to Rayleigh fading, the phase of the Nakagami- $m$ distribution is not uniformly distributed. It is shown in this paper that the phase of the channel has major impact on the performance of spatial multiplexing MIMO systems such as SM and QSM systems. A general upper bound expression for the average bit error ratio (ABER) performance of QSM is derived, and the impact of different channel parameters is studied. Monte Carlo simulation results are provided to corroborate the exactness of the derived analysis. [ABSTRACT FROM PUBLISHER]

In this corresponence paper, we address the spectrum sensing problem under the non-Gaussian noise scenario characterized by the symmetric alpha stable ($\text{S}\alpha \text{S}$) model. In this paper, a novel spectrum sensing method is proposed using the maximum generalized correntropy, aimed at improving the spectrum sensing performance in low generalized signal-to-noise ratio conditions. To further enhance the robustness of the proposed method, multiple receive antennas are applied to carry out cooperative spectrum sensing. Besides, a modified conjugate gradient algorithm is used to optimize the sparse vector for cooperative spectrum sensing. Finally, simulation results are presented to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers the $\mathscr{L}_{2}$ string stability analysis and controller synthesis for vehicle platooning under jamming attacks and interferences from other communication channels. Jamming attacks and interferences for vehicle platooning systems are modeled as periodic denial of service attacks. Further, the vehicle platooning with denial of service attacks is modeled as a distributed switching system where an average dwell time approach is adopted for the stability analysis. Under the distributed switching system framework, this paper presents a co-design paradigm for the vehicle platooning. The distributed event-triggered method (ETM) and controllers are presented to guarantee $\mathscr{L}_{2}$ string stability, which can ensure that the output cannot be amplified along the vehicle platooning. Sufficient conditions for $\mathscr{L}_{2}$ string stability are then provided to guide the co-design of the ETM and controllers, which can be efficiently obtained by solving LMIs. Simulation results are presented to demonstrate the efficacy of the proposed co-design approach in addressing the denial of service attacks for vehicle platooning systems. [ABSTRACT FROM AUTHOR]

This correspondence paper studies the impact of nonidentically distributed channel estimation error on performance of a scheduled space-time block coding with mean-value power allocation in cognitive-radio multiple-input multiple-output system. Using the derived probability density function, the exact closed-form expressions of the proposed system for outage probability, ergodic capacity, and symbol-error rate (SER) with both $\rm M$ -ary quadrature amplitude modulation and phase shift keying modulation are derived. Using asymptotic analysis, this paper quantifies the diversity order for both outage probability and SER in the presence of nonidentically distributed error. From the analysis results, this paper shows that the diversity order is enhanced by the multiuser diversity as the number of user terminals increases regardless of outage probability and SER, while the spatial diversity is eliminated. [ABSTRACT FROM AUTHOR]

This paper investigates the performance analysis of dual selection (i.e., combining user selection and transmit antenna selection) with maximal ratio combining (MRC) over nonidentical imperfect channel estimation in a multiple-input multiple-output system. This paper derives the exact and approximate cumulative density function and probability density function (PDF) for the dual selection with MRC over nonidentical imperfect channel estimation. Using the distribution, the exact and approximate closed-form expressions of the outage probability are derived with quantification of diversity order. Further, this paper derived the exact ergodic capacity and approximate outage capacity of the the dual selection via Gaussian and Gamma approximations. The numerical results show that the capacity of the dual selection with MRC is enhanced by the number of receive antennas as well as the number of user terminals and sum of channel correlation coefficients, while the order of the receive spatial diversity for outage probability is eliminated by the nonidentical channel estimation error. [ABSTRACT FROM AUTHOR]

Rate-Splitting Multiple Access (RSMA) is an emerging flexible and powerful multiple access for downlink multi-antenna networks. In this paper, we introduce the concept of RSMA into short-packet downlink communications. We design optimal linear precoders that maximize the sum rate with Finite Blocklength (FBL) constraints. The relations between the sum rate and blocklength of RSMA are investigated for a wide range of network loads and user deployments. Numerical results demonstrate that RSMA can achieve the same transmission rate as Non-Orthogonal Multiple Access (NOMA) and Space Division Multiple Access (SDMA) with smaller blocklengths (and therefore lower latency), especially in overloaded multi-antenna networks. Hence, we conclude that RSMA is a promising multiple access for low-latency communications. [ABSTRACT FROM AUTHOR]

With low-cost energy consumption, the reconfigurable intelligent surface (RIS) technique is a potential solution to the real-time data processing for intelligent transportation systems (ITSs). In this paper, an intelligent transmissive surface is introduced into the vehicular communications, enabling vehicle-to-infrastructure (V2I) signals to penetrate the intelligent RIS to access the base station (BS) on the opposite side of the vehicle. Considering that the vehicle-to-vehicle (V2V) communication reuses the spectrum spanned for V2I link, we investigate the ergodic capacity optimization problem for the vehicle performing V2I communications with the assistance of RIS, while meeting the low-latency and high-reliability requirements of the V2V link. The RIS transmission coefficients and power allocation of vehicles are jointly optimized, for the management of the desired and undesired vehicular communication links. Moreover, the expression of optimal phase shifts is derived in a closed-form, which reveals that the performance gain brought by RIS is proportional to the number of intelligent elements, while inversely proportional to the distance from vehicle-to-BS, in a quadratic form. Moreover, in the case of discrete phase shifts, an intelligent algorithm is proposed for the beamforming design at RIS. Afterwards, with the objective to maximize the ergodic capacity of the V2I link, the optimal power allocation is also proposed. Simulation results confirm the accuracy of the proposed resource allocation strategy, and that the system performance in terms of the ergodic V2I capacity can be significantly improved by the RIS. [ABSTRACT FROM AUTHOR]

The new Fifth generation (5G) of wireless communications and beyond 5G (B5G) networks are required to provide connectivity for massive number of devices at high speed and low latency. Within this context, non-orthogonal multiple access (NOMA) has been involved and emerged in recent research since it is considered as an enabling technology for 5G and B5G networks. NOMA allows several users to share the same resources of time and frequency, making it an excellent candidate to provide impressively large connectivity with high spectral efficiency. In this paper, we study the performance of NOMA systems assuming independent but not necessarily to be identical $N$ -Nakagami-m multipath fading channels. This channel model subsumes the double Nakagami-m, which was investigated in the context of intervehicular communications and keyhole multiple input multiple output systems, as special cases. To this end, we derive exact analytical and asymptotic expressions for the probability density function of the overall signal to noise ratio, system capacity, and the pairwise error probability (PEP) for each user. Numerical results are also provided herein to show the effects of fading parameters and number of users on the capacity and the PEP of each user. [ABSTRACT FROM AUTHOR]

Carrier sense multiple access with collision notification (CSMA/CN) is a typical representation of physical-layer (PHY)/medium access control (MAC) co-designs, where the MAC control frames are implemented or detected using PHY techniques. With CSMA/CN, the sender detects an unsuccessful transmission, with the aid of a collision notification (CN) from the receiver. In this paper, we first theoretically study the crucial impact of the CN attributes (namely, the detection threshold and the length) on system throughput in a wireless local area network (WLAN). We identify that the false-alarm probability of CN (more generally, the control frames in PHY/MAC co-designs) is a dominating metric that influences system performance. This paper will help developers select optimal CN attributes to balance various factors influencing CN detection performance. Extensive simulation results verify that our performance model is very accurate. [ABSTRACT FROM PUBLISHER]

Cooperative communication exploits spatial diversity via relay node antennas to increase data rates in wireless networks. Relay node selection, therefore, plays a critical role in system performance. This paper examines the problem of relay node selection in cooperative networks, in which one relay node can be used by multiple source–destination transmission pairs, and all transmission pairs share the same set of relay nodes. Centralized approaches may exhibit higher complexity when the number of source nodes is increased. This paper gives source nodes self-optimizing and self-learning abilities and enables them to autonomously select relay nodes. A fully distributed approach, called a “Decentralized Learning-based Relay Assignment” (DLRA) algorithm, is proposed to achieve this goal. DLRA uses a reinforcement learning technique called stochastic learning automata, with each source node attaining the self-learning ability to find an appropriate relay node according to environmental feedback. This paper shows the convergency, optimality, and performance of DLRA via mathematical analysis and evaluates the performance of DLRA in two different network systems: a cooperative ad hoc network and a Long-Term Evolution (LTE)-Advanced relay network. The experimental results present several properties of DLRA: the effectiveness of DLRA in cooperative communication systems, the significant improvements made by DLRA in fairness, and the capacity of each node in LTE-Advanced systems. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a reference-free artificial noise (AN) waveform design and cancellation scheme for single-input-single-output (SISO) wireless secure transmission. First, a system structure with the aid of AN is presented, where we provide a specific method extracting the sign information of each symbol from the desired signal (DS) to form AN at the transmitter. Then, we notice that the legitimate receiver enable to reconstruct the AN from the received signal by almost the same method as the transmitter without AN reference, which reduces the system complexity in practice. Subsequently, the AN cancellation performance and the secrecy capacity at the receiver are analyzed, and their upper bounds are also derived. Finally, simulation results confirm that the proposed reference-free AN design and cancellation scheme can effectively suppress the AN at legitimate receiver, while degrades the signal to noise ratio (SNR) at eavesdropper seriously, which provides impressive secure performance in terms of secrecy capacity. [ABSTRACT FROM AUTHOR]

Target detection is an important problem in multiple-input multiple-output (MIMO) radar. Many existing target detection algorithms were proposed without taking into consideration the quantization error caused by analog-to-digital converters (ADCs). This paper addresses the problem of target detection for MIMO radar with one-bit ADCs and derives a Rao’s test-based detector. The proposed method has several appealing features: 1) it is a closed-form detector; 2) it allows us to handle sign measurements straightforwardly; 3) there are closed-form approximations of the detector’s distributions, which allow us to theoretically evaluate its performance. Moreover, the closed-form distributions allow us to study the performance degradation due to the one-bit ADCs, yielding an approximate 2 dB loss in the low-signal-to-noise-ratio (SNR) regime compared to $\infty$ -bit ADCs. Simulation results are included to showcase the advantage of the proposed detector and validate the accuracy of the theoretical results. [ABSTRACT FROM AUTHOR]

This study is motivated by the fact that localization in millimeter wave(mmWave) Vehicle-to-Vehicle communication becomes a more critical problem because both the terminals of the communication link are in motion. The positional awareness merely based on GPS or local sensors has an error margin of around 10 meters, which can worsen in uncertain real-time conditions such as road topology and highway traffic. The paper analyses the relation between vehicle dynamics, beamforming, and beam alignment for highly directive antennas. When the subsystem models presented in this paper are taken into consideration, the joint vehicle dynamics-beamforming approach will optimize the link connectivity and SNR. The vehicle dynamics model is designed to be more realistic considering the non-linear acceleration based on the throttle-brake jerks due to induced noises. The Unscented Kalman Filter based prediction subsystem predicts the alignment values even during non-linear acceleration and jerks. The feasibility of antenna design for the beamforming strategies is supported by the requirements of phase shifters and the number of elements. [ABSTRACT FROM AUTHOR]

This paper presents a non-orthogonal multiple access (NOMA)-assisted full-duplex (FD) cooperative spectrum sharing protocol to achieve full-rate at a cell-edge primary user, where the secondary receiver helps the primary network relay the information to the cell-edge primary user. Unlike other FD cooperative schemes, the FD relay in the proposed system is not transmitting while receiving symbols from the primary transmitter. Hence, the proposed scheme can achieve full-rate at a primary user without degrading its outage performance. Further, it guarantees every alternate time-slots to the secondary network for accessing the licensed spectrum by employing a secondary receiver as a cooperative relay. In this paper, we derive the analytical expression for the outage probability and ergodic capacity. Moreover, we validate the derived expression through simulation and asymptotic results. The numerical and simulation results substantiate that the proposed scheme significantly outperforms other existing protocols. [ABSTRACT FROM AUTHOR]

This paper presents a comparative performance analysis of multiuser multirelay two-way and one-way amplify-and-forward relaying systems employing opportunistic transmission in the presence of channel estimation error and hardware impairments over Rayleigh fading channels. Considering such a practical scenario, we first deduce instantaneous end-to-end signal-to-noise-plus-distortion-and-error ratios at the end-user terminals. Then, we derive exact closed-form expressions of outage probability (OP) and expected spectral efficiency for both the systems. Further, we obtain simple asymptotic expressions at the high signal-to-noise ratio (SNR) regime, which facilitate the characterization of achievable diversity order of the systems. Thereafter, we validate our derived analytical expressions with the simulation results, which are sufficiently tight across the entire range of SNRs. Eventually, we optimize power allocation in order to minimize OP of the systems. Numerical results reveal the improvement in system outage when power allocation is in accordance with its optimal value. Findings of the paper suggest that full diversity order can be achieved only when the radio frequency front-end hardware is assumed to be perfect, while in practice the imperfections in hardware are inevitable and will reduce system diversity. Moreover, we demonstrate the influence of key parameters on the performance of the systems. [ABSTRACT FROM AUTHOR]

We consider the problem of multiantenna source detection with dimension reduction in distributed wireless networks. Traditional strategies typically collect and perform raw data at the fusion center. In moderate-to-large-scale networks, however, the schemes create the bottleneck of computation and communication for high-dimensional data. The goal of this paper is to design a distributed algorithm in multiple-antenna wireless networks to project the raw data into the low-dimensional data to reduce the communication and computation burden while maintaining high detection performance. In this paper, a pseudosketching matrix is constructed to transform the raw data of each multiple-antenna node into the low-dimensional data. Furthermore, it is transformed into the vector by using the subspace method. By gathering the data vectors of all nodes at the fusion center, the eigenvalue-based detection methods, such as the generalized likelihood ratio test (GLRT), can be applied directly to determine if the source signal exists or not. Moreover, using the concentration inequalities of subgamma random variables, the theoretical analysis is derived to support the claim that the proposed algorithm has high detection performance. The simulations are presented to demonstrate the effectiveness of our proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper discusses a practical design of nonlinearity preprocessors to be used in a receiver for mitigating performance degradation in an impulsive noise environment. A simple method is proposed for a blanker and a soft limiter to calculate a blanking and a clipping threshold, respectively. In addition, to evaluate the bit error performance of a receiver with the proposed nonlinearity preprocessors, this paper introduces an approach using a periodic pulse train function and Fourier series. When a nonlinearity preprocessor is used, since the output samples show a truncated probability density function, it is generally difficult to evaluate the bit error performance of a receiver. Analytical and simulation results show that the thresholds computed by the proposed method are near optimal in terms of efficacy function and that the error performance of the proposed nonlinearity preprocessors matches well with that of the ideal design of nonlinearity preprocessors with optimal thresholds. [ABSTRACT FROM PUBLISHER]

The technical challenges, e.g. the mobility management and the offloading process, hinder the conventional cellular systems to meet the huge data traffic requirements of the next generation mobile communications. The traditional system (e.g dual-connectivity (DC)) has been proposed to improve the mobility management, however, it will inherit the big trade-off in the offloading process between the energy consumption for the small cell (SC) discovery (SCD) process and the efficiency of utilizing the system resources (e.g. frequency and signaling). In this paper, we present a framework to model the potential offloading opportunities as well as the offloading loss when a typical user equipment (UE) performs the inter-frequency (IRF) scan periodically. The proposed framework also studies the impact of the SCD on the energy efficiency. To improve the system performance and reduce the power consumption at the UEs, a new scheme, trio-connectivity (TC), is proposed in this paper to tackle the aforementioned challenges. The TC includes three planes: control-plane (C-plane), user-plane (U-plane) and indication-plane (I-plane). The I-plane works as an indicator to help the UE to identify and discover the SCs in the system prior to offloading. The role of the I-plane is to keep the SCD on one frequency channel regardless of the number of frequency channels in the system. In the proposed offloading mechanism, some of the energy consumption is transferred from the UE to the network. By using the proposed framework, UE energy efficiency and system energy efficiency as well as the total energy consumption are derived as performance metrics to compare between the TC and the DC. The results show that the TC can outperform the DC in dense cellular systems. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) assisted non-orthogonal multiple access (NOMA) transmission can effectively improve the energy/spectrum efficiency in wireless networks. This paper designs a low-complexity scheme to achieve the balanced tradeoff between the sum-rate and power consumption in a RIS-assisted NOMA system, which can be measured by energy efficiency. To solve the formulated problem effectively, the original non-convex problem is first decomposed into two subproblems, i.e., beamforming optimization and phase shift optimization. Alternating optimization is proposed to solve these two subproblems iteratively. In particular, successive convex approximation (SCA) is utilized to convert the non-convex constraints to convex ones. The provided simulation results demonstrate that the proposed scheme can achieve superior performance on energy efficiency compared to the random phase shifts and orthogonal multiple access (OMA) schemes. [ABSTRACT FROM AUTHOR]

As the number of antennas increases, the massive multiple-input multiple-output (MIMO) system can precisely point to user equipments (UEs) with narrow beams. Accurate and timely channel state information (CSI) feedback is crucial to keep UEs in service. Mobile UEs, however, may suffer from the narrow beam nature of the massive MIMO system since UEs can move out of the beam coverage. When intelligent reflecting surface (IRS) is applied to the massive MIMO system, the adjustment of the IRS cannot be frequent as the IRS is controlled remotely by the base station (BS). Limiting the number of CSI feedback and the number of both BS and IRS adjustments significantly reduces the overhead of transmission and computation to the system. In this paper, we consider the UEs’ mobility adaptation problem in an IRS assisted multiuser massive MIMO downlink system with infrequent CSI feedback. We propose a beam control method that adapts to UEs’ mobility. The problem is constructed as a sum rate problem where both the BS and IRS are taken into account to jointly optimize the beamforming matrices. Simulation results show that our proposed algorithm can converge quickly and provide satisfactory performance for mobile UEs. At the same time, our proposed algorithm reduces the frequency of updating the beamforming matrices effectively both at the BS and at the IRS. [ABSTRACT FROM AUTHOR]

At millimeter-wave (mm-wave) frequencies, narrow beamwidth and inaccurate channel estimation result in beam alignment errors, which degrade the achievable signal-to-noise ratio (SNR) and rate. The extent of beam misalignment depends on the various link parameters, however, prior works ignored such a dependence and considered oversimplified array patterns. This paper formulates beam alignment errors for the uniform linear array at the base station as a function of the link parameters by using the Cramér Rao lower bound of angle-of-arrival estimates and proposes a tractable array pattern approximation to better reflect the effects of such alignment errors. Utilizing stochastic geometry and the statistics of the Student’s t-distribution, a novel and robust analytical technique is developed to obtain the downlink SNR and rate coverage probabilities due to beam misalignment, assuming a single antenna at the user. We show that beam alignment errors significantly affect the achievable SNR and rate for non line-of-sight (NLOS)/distant users whereas the effect is negligible for LOS/nearby users. It is also illustrated that the effects of alignment errors cannot be mitigated only by increasing the number of antennas. We also show that our proposed array pattern approximation better captures the effects of beam alignment errors as compared to the widely used flat-top pattern. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) control information delivery is a critical communication with stringent requirements in terms of reliability and latency. In this context, link adaptation plays an essential role in the fulfillment of the required performance in terms of decode error probability and delay. Link adaptation is usually based on channel quality indicator (CQI) feedback information from the user equipment that should represent the current state of the channel. However, measurement, scheduling and processing delays introduce a CQI aging effect, that is a mismatch between the current channel state and its CQI representation. Using outdated CQI values may lead to the selection of a wrong modulation and coding scheme, with a detrimental effect on performance. This is particularly relevant in ultra reliable and low latency communications (URLLC), where the control of the reliability can be negatively impacted, and it is more evident when the channel is fast varying as the case of UAVs. This paper analyzes the effects of CQI aging on URLLCs, considering transmissions under the finite blocklength regime, that characterizes such communications type. A deep learning approach is investigated to predict the next CQI from the knowledge of past reports, and performance in terms of decode error probability and throughput is given. The results show the benefit of CQI proposed prediction mechanism also in comparison with previously proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, we give performance analysis in an unmanned-aerial-vehicle (UAV) assisted ground short-packet communication system, which adopts a UAV as a wireless relay to accomplish ultra-reliable and low-latency communications (URLLC) between a base station and a user equipment (UE). Both large-scale fading, which is modeled as the free space path loss or the classic 3-Dimensional channel, and small-scale fading, which follows Nakagami- $m$ distribution, are considered in our system model. We first derive the closed-form expressions for the average overall block error ratio (BLER) at the UE by adopting Gasssian-Legendre quadrature (GLQ) method. Then, under the reliability and latency constraints at the UE, we apply both bisection search and one-dimensional search algorithms to jointly optimize blocklength, transmit power and UAV flying height for maximizing the energy-efficiency (EE) of UAV. Finally, Monte-Carlo simulations are provided to verify our analytical results. [ABSTRACT FROM AUTHOR]

Relays have been deployed to provide connectivity to heavily blocked and isolated radio environments, but suffer from severe data rate losses due to the half-duplex nature of relays. This paper exploits non-orthogonal multiple access (NOMA) to enhance the sum-rate of two heavily blocked users to and from a base station (BS) via two-way relays (TWRs). By carefully arranging the NOMA transmissions, only two time slots are needed to complete a round of two-way transmissions between the BS and the two users. Unlike existing works where users associated with the same relay form a NOMA pair, the two users are connected to two different relays in the proposed scheme, due to the blockage. We analyze the sum-rate of the proposed NOMA-based TWR scheme with two popular relaying modes, namely, amplify-and-forward (AF) and decode-and-forward (DF) relaying, and derive closed-form expressions for the sum-rate upper bounds of the scheme. We also analyze the asymptotic sum-rate of the NOMA-based TWR schemes in high signal-to-noise ratio (SNR) regions. Simulations verify the analysis, and show that the proposed schemes outperform existing TDMA-based alternatives and a NOMA-based benchmark scheme. It is shown that the sum-rate of the schemes is independent of the transmit power of the BS in the high SNR regions, given the transmit powers of the relays and users. [ABSTRACT FROM AUTHOR]

Using a well-known wiretap model, for the first time in this paper, closed-form solutions are achieved for wireless secrecy under dual correlated Rician fading. A novel wireless secrecy and end-to-end (e2e) system analysis employing decode-and-forward (DF) opportunistic relays and an adaptive encoder with on/off transmission are reported. A signal-to-noise ratio (SNR) distribution of dual correlated Rician fading is first obtained as a function of four nested infinite summations, which (i) converges for a finite number of terms, and (ii) is employed to compute secrecy outage probability for a passive wiretapper. Using two-dimensional Laplace transform of the SNR distribution of dual correlated Rician fading, an e2e system analysis is then given by deriving compact expressions for e2e SNR distributions, and e2e ergodic capacity. Relationships between important parameters are elaborated and explained. An asymptotic analysis and proof for infinite summation convergence are also given. It is shown that there is a trade-off between transmission quality and security via line-of-sight power. Simulation results are shown to match theoretical prediction, which validates this work. [ABSTRACT FROM AUTHOR]

This paper presents the secrecy performance of a user and antenna selection at transmitter (i.e., combined scheme) over channel estimation inaccuracy in wiretap channels with multiple antennas. This paper develops the precise formulations of the combined system for the secrecy outage probability and the probability of the non-zero secrecy capacity. This work develops the diversity order for the secrecy outage probability in the presence and absence of channel inaccuracy at the combined system and eavesdropper. This work provides various numerical evaluations, showing that, the diversity order of the combined system is changed only by combined system‘s channel inaccuracy not by eavesdropper's channel inaccuracy. Also, the channel inaccuracy of the eavesdropper acts on the signal to noise ratio (SNR) gain of the combined system. [ABSTRACT FROM AUTHOR]

This paper proposes a channel code for vector perturbation (VP) precoded transmission in multiuser downlink and examines its achievable sum-rate performance. In particular, we first find the most suitable outer convolutional code (CC) for VP precoded transmission under bit-interleaved coded modulation with iterative decoding (BICM-ID) by applying a semi-analytic technique based on extrinsic information transfer charts. We then study the achievable sum rate of the proposed BICM-ID-based VP precoded system, and we compare it with the sum capacity of the dirty paper coding (DPC) scheme. Our investigation shows that under perfect channel state information (CSI), the sum rate of the proposed system grows linearly over the number of users, which is the same growth of the DPC. Under quantized CSI and finite-rate feedback, a linear increase in feedback overhead per user is necessary to maintain such a linear sum-rate growth. [ABSTRACT FROM PUBLISHER]

This paper studies the performance of two traditional schedulers, namely, proportional fair (PF) and round robin (RR), in the context of relay-enhanced Long-Term Evolution Advanced (LTE-A) networks. These two schedulers are natural candidates for implementation in relay nodes (RNs), and following the results obtained in single-hop networks, mobile operators could be tempted to adopt PF because of the good tradeoff it offers between cell capacity and fairness. Based on a statistical throughput evaluation model, we show that this is not necessarily the right option. The number of RNs, their locations in the cell, and backhaul link quality have a decisive influence on scheduler choice. In some scenarios, it is even not desirable to deploy relays as they degrade the network performance compared with the no-relay case. For the purpose of performance evaluation, we develop a realistic and computationally tractable statistical network model that takes into account fast fading, multiple interferers, cell range expansion bias, backhaul link quality, and traffic load. We also propose optimization of the radio frame structure and a suboptimal RN placement scheme to fairly compare RR and PF. [ABSTRACT FROM AUTHOR]

In this paper, we consider a single-relay-based decode-and-forward (DF) cooperative multiple-input multiple-output (MIMO) system in which the source, the relay, and the destination are equipped with Ns, Nr, and Nd antennas, respectively. We propose a joint antenna and path selection scheme, which jointly selects the single-transmit and single-receive antenna pairs, along with the selection of either a direct path that consists of source–destination channels or a cooperative path that consists of source–relay and relay–destination channels. The proposed selection scheme is based on the maximization of minimum of maximums (max-min-max) criterion of instantaneous signal-to-noise ratio (SNR). The analysis in this paper is based on the assumptions that all the channels follow independent Rayleigh fading. A closed-form expression of the symbol error rate (SER) for the proposed scheme in a cooperative MIMO system with M-ary phase-shift keying is derived. We extract the analytical diversity order from the derived SER and show that the proposed selection scheme achieves the diversity order of N_{s}N_{d}+N_{r}\mathrm{min}(N_{s},N_{d}) in the considered cooperative MIMO system. Closed-form expressions of bandwidth efficiency (BE) and ergodic capacity (C_{t})$ are derived for the proposed scheme. An optimized selection parameter from the specific set of values is numerically evaluated by maximizing a heuristic utility function (C_{t}\times \mbox{BE}/\mbox{SER}). By using the already-gathered information about the maximum instantaneous SNR of every hop, a power adaptation scheme that maximizes the instantaneous SNR in the cooperative path is proposed and analyzed. The proposed power adaptation scheme, which is applied only in the event of selection of a cooperative path, outperforms the uniform-power-distribution-based DF cooperative MIMO system. [ABSTRACT FROM AUTHOR]

This paper studies a cognitive radio network (CRN), in which a multiple-input single-output (MISO) secondary transmitter (SU-Tx) aims to send confidential messages to its receiver (SU-Rx) in the presence of unknown eavesdroppers, while having to control its generated interference to the primary users (PUs) under a given threshold. Because the eavesdroppers are unknown, this paper considers the artificial noise (AN) approach or masked beamforming to provide the information secrecy. The objective of this paper is to maximize the power of AN in order to degrade the eavesdroppers, subject to the signal-to-interference-plus-noise ratio (SINR) constraint at the SU-Rx, as well as the interference temperature limits (ITLs) for the PUs. In the case of perfect channel state information (CSI), we reveal that the optimal strategy for the information-bearing signal is beamforming. Imperfect CSI cases of bounded and stochastic uncertainties are investigated. In the case of ellipsoid-bounded errors, we derive the equivalent forms for the SINR and ITL constraints and then transform the optimization problem into a form of semidefinite programming (SDP). For the case of probabilistic CSI uncertainties, we propose an outage-constrained robust formulation where the CSI errors are Gaussian distributed. With the aid of two kinds of Bernstein-type inequalities, we reexpress the probabilistic constraints into deterministic forms, which results in a safe approximate solution. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a cloud radio access networks (C-RANs) in which base stations (BSs) are uniformly distributed inside a disk. The outage probability and the ergodic rate achieved by these C-RANs are analyzed, where stochastic geometry is used to capture the randomness of BS locations. Compared with existing studies to C-RANs, more accurate analytical results are developed by applying the Gauss–Chebyshev integration, as confirmed by our simulation results. [ABSTRACT FROM PUBLISHER]

In this paper, we analyse a secure transmission scheme using rateless codes (RC) in a delay constrained system. By using RC, secrecy is achieved if the legitimate receiver can accumulate required number of packets before an eavesdropper does. To achieve this, we employ transmit antenna selection (TAS) at the base station to improve the main channel and, artificial noise (AN) is generated by the use of a cooperative jammer to degrade the eavesdropper's channel. Quality of violation probability (QVP) which consists of both the delay violation probability and the intercept probability is used as a performance metric. A closed-form expression for QVP is derived. We show that using TAS for reducing QVP is effective only at lower signal to noise ratio (SNR). We also observe that on increasing number of antennas at the source ($N_{A}$) while using TAS along with AN, QVP decreases for delay sensitive services, whereas, in case of delay tolerant applications, increasing $N_{A}$ is effective at low SNR. [ABSTRACT FROM AUTHOR]

This paper addresses the spectrum sensing problem in an orthogonal frequency-division multiplexing (OFDM) system based on machine learning. To adapt to signal-to-noise ratio (SNR) variations, we first formulate the sensing problem into a novel SNR-related multi-class classification problem. Then, we train a naive Bayes classifier (NBC), and propose a class-reduction assisted prediction method to reduce spectrum sensing time. We derive the performance bounds by translating the Bayes error rate into spectrum sensing error rate. Compared with the conventional methods, the proposed method is shown by simulation to achieve higher spectrum sensing accuracy, in particular at critical areas of low SNRs. It offers a potential solution to the hidden node problem. [ABSTRACT FROM AUTHOR]

In this paper, the throughput maximization of millimeter-wave (mm-Wave) ultradense networks (UDN) using dynamic spectrum sharing (DSS) is considered. Most of the existing works only allow temporal-domain access and admit at most one user at each time slot, resulting in significant underutilization of spectrum resource, which will be less attractive to mm-wave UDN applications. A generalized temporal-spatial sharing scheme is proposed in this paper for UDN by exploiting the location information of incumbent devices, where multiple users are allowed to access each channel simultaneously via spatial separations. For distributed applications, the global information exchange among secondary users (SU) tends to be impractical, given the unaffordable signaling overhead and latency. Thus, a noncooperative game with fine-grained two-dimensional reuse is formulated, which leads to a more efficient access strategy. It is then proved to be an ordinary potential game (OPG), which guarantees the existence of the strategy Nash equilibrium (NE). Finally, an improved decentralized reinforcement learning algorithm is designed, with which SUs can learn from wireless environments and adapt toward an NE point, relying on the individual observation and the historical action reward (rather than the global information exchanging). The convergence efficiency of the new scheme is also rigorously proved. Numerical simulations are provided to validate the performances of the proposed schemes. [ABSTRACT FROM AUTHOR]

The next generation of mobile communication has progressed toward the deployment of small cells to meet the growing demands of increased capacity and QoS as compared to the conventional method, where all the computations were performed by the base station (BS)'s only. To reduce burden at the BS side, small cells deployment has been stressed upon, thus resulting in the formation of ultradense networks (UDN) having high concentration of small cells (e.g., picocell, femtocell, hotspots) and as a counter effect of which distance between two small cells is reduced to a greater extent. With such a close association of cells in UDN, the probability of frequent handovers also increases abruptly. As a result, the chances for attacker to spoof the bandwidth also increases many folds. In this paper, we have analyzed SNR, signal-to-interference-plus-noise ratio, and channel quality information channel parameters, such that the position of moving users at which handover is initiated in picocell deployment of UDN can be traced out successfully or region where the probability of attackers presence is high. Through this paper, we have tried to introduce the attacking scenario for the high mobility conditions in UDN. [ABSTRACT FROM AUTHOR]

In this paper, we present unified performance analysis framework of distributed transmit beamforming (DTB) with residual phase errors which arise from various sources such as imperfect synchronization and channel feedback quantization. More specifically, we derive statistics of the receive signal-to-noise ratio of DTB in Rayleigh and Rician fading channels in the presence of residual phase errors. In the case of residual phase errors caused by channel feedback quantization, we show that the distribution of residual phase errors can be modeled by uniform distribution in Rayleigh fading channels and Gaussian distribution in Rician fading channels. Also, our results reveal that a small number of bits are sufficient for quantized feedback to achieve comparable performance to DTB with perfect channel feedback. Finally, capitalizing on the derived statistics, we present closed-form expressions for the outage probability and the ergodic capacity of DTB with quantized channel feedback. [ABSTRACT FROM AUTHOR]

In this study, we investigate the operation of a user-number threshold-based base station (BS) on/off control, in which the BS turns off when the number of users is less than a specific threshold value. This paper presents a space-based analysis of the BS on/off control system to which a stochastic geometric approach is applied. In particular, we derive the approximated closed-form expression of the coverage probability of a homogeneous network (HomNet) with the user-number threshold-based BS on/off control. Moreover, the optimal user-number threshold for maximizing coverage probability is analytically derived. In addition to HomNet, we also derive the approximated closed-form expression of the coverage probability and the optimal user-number thresholds for a heterogeneous network (HetNet). The results show that HetNet, the analysis of which seems intractable, can be analyzed in the form of a linear combination of HomNets with weighted densities. In addition, the optimal user-number threshold of each tier is obtained independently from other tiers. The modeling and analysis presented in this paper are not only limited to the case of user-number threshold-based on/off control, but also applicable to other novel on/off controls with minor modifications. Finally, by comparing the analytical results with the simulated results, the theoretical contributions of this study are validated. [ABSTRACT FROM AUTHOR]

This paper proposes a novel bit loading algorithm to multicarrier non-orthogonal multiple access (NOMA) systems to maximize the system total throughput while satisfying the users’ individual quality of service (QoS) constraints. Although bit loading is generally a non-deterministic polynomial-time (NP)-hard problem, even for orthogonal multiple access (OMA), the mutual interference between the users, and the dependence of power coefficients and modulation orders are additional challenges that add substantial complexity to the optimization problem. Therefore, in this paper, we propose an efficient bit loading algorithm for multicarrier NOMA systems and compare the complexity and throughput with a corresponding OMA system. The obtained results show that for the case of NOMA, bit loading provides an additional degree of freedom that allows non-uniform spectrum sharing among the users. In particular scenarios, the system may experience hybrid modes of operation, where the system switches between NOMA and OMA. The obtained numerical results show that NOMA can outperform OMA by 100% in terms of spectral efficiency, for a two-user scenario. The complexity of the loading process for NOMA is noticeably higher than OMA, which is due to the high complexity associated with the bit error rate (BER) computation in the case of NOMA. [ABSTRACT FROM AUTHOR]

In the existing millimeter-wave (mmWave) wireless positioning systems, the method based on sparse Bayesian learning (SBL) uses the channel sparsity to estimate the parameters required for positioning, such as angle of arrival (AOA) and time delay, but most existing SBL solutions only consider the angle sparsity. In this paper, we consider the joint sparsity of the angle domain and time delay domain to propose an improved SBL algorithm by using a new two-dimensional adaptive grid refinement method in the SBL framework. This algorithm solves the grid mismatch problem caused by the fixed grid in the traditional SBL method, and reduces the algorithm complexity of the off-grid SBL (OGSBL) algorithm. We also obtain the Cramér-Rao bound (CRB) of AOA, time delay and position estimation based on the mmWave multipath signals to analyze the estimation errors. Simulation results show that the performance of the proposed algorithm is better than existing algorithms and can approach CRB. [ABSTRACT FROM AUTHOR]

In this paper, we focus on the design and analysis of the Analog Fountain Code (AFC) for short packet communications. We first propose a density evolution (DE) based framework, which tracks the evolution of the probability density function of the messages exchanged between variable and check nodes of AFC in the belief propagation decoder. Using the proposed DE framework, we formulate an optimisation problem to find the optimal AFC code parameters, including the weight-set, which minimises the bit error rate at a given signal-to-noise ratio (SNR). Our results show the superiority of our AFC code design compared to existing designs of AFC in the literature and thus the validity of the proposed DE framework in the asymptotically long block length regime. We then focus on selecting the precoder to improve the performance of AFC at short block lengths. Simulation results show that lower precode rates obtain better realised rates over a wide SNR range for short information block lengths. We also discuss the complexity of the AFC decoder and propose a threshold-based decoder to reduce the complexity. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of decoding in large-scale multiple-input–multiple-output (MIMO) systems. In this case, the optimal maximum-likelihood (ML) detector becomes impractical due to an exponential increase in the complexity with the signal and the constellation dimensions. This paper introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with finite constellation and model it as a system with sparse signal sources. We propose an ML relaxed detector that minimizes the Euclidean distance with the received signal while preserving a constant \ell1 -norm of the decoded signal. We also show that the detection problem is equivalent to a convex optimization problem, which is solvable in polynomial time. Two applications are proposed, and simulation results illustrate the efficiency of the proposed detector. [ABSTRACT FROM PUBLISHER]

In this paper, we design a novel estimate-and-forward (EF) protocol in multiple-access relay channels (MARCs) where two correlated sources transmit their information to the common destination with the help of a relay. With the application of network coding (NC) at the relay, the network-coded soft symbols contain redundant information due to the correlated sources, which can be compressed before being forwarded. Specifically, we first derive the value of the network-coded soft symbol by considering the correlation of the two sources. Due to this correlation, the majority of soft symbol values are close to one. Then, we convert network-coded soft symbol vector into a sparse vector, which is suitable for compression by using the compressive sensing (CS). Next, we analyze the performance of the proposed EF protocol by comparing the soft symbol value and received signal-to-noise ratio (SNR) with the conventional EF protocol. Simulations show that our protocol can achieve the same bit error rate (BER) as the conventional EF protocol with proper compression rates, and it consumes much less transmission time due to the compression. [ABSTRACT FROM PUBLISHER]