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This paper studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user. [ABSTRACT FROM PUBLISHER]

The explosive growth of Internet-of-Things (IoT) applications such as smart cities and Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating the rapid development of new techniques for enhancing spectrum utilization needed by new generation wireless communication technologies. Among others, dynamic spectrum access (DSA) is one of the most widely accepted approaches. In this paper, as an enhancement of existing works, we take into consideration of inter-node collaborations in a dynamic spectrum environment. Typically, in such distributed circumstances, intelligent dynamic spectrum access almost invariably relies on self-learning to achieve dynamic spectrum access improvement. Whereas, this paper proposes a DSA scheme based on deep reinforcement learning to enhance spectrum and access efficiency. Unlike traditional Q-learning-based DSA, we introduce the following to enhance the spectrum efficiency in dynamic IoT spectrum environments. First, deep double Q-learning is adopted to perform local self-spectrum-learning for IoT terminals in order to achieve better dynamic access accuracy. Second, to accelerate learning convergence, federated learning (FL) in edge nodes is used to improve the self-learning. Third, multiple secondary users, who do not interfere with each other and have similar operation condition, are clustered for federated learning to enhance the efficiency of deep reinforcement learning. Comparing with the traditional distributed DSA with deep learning, the proposed scheme has faster access convergence speed due to the characteristic of global optimization for federated learning. Based on this, a framework of federated deep reinforcement learning (FDRL) for DSA is proposed. Furthermore, this scheme preserves privacy of IoT users in that FDRL only requires model parameters to be uploaded to edge servers. Simulations are performed to show the effectiveness of theproposed FDRL-based DSA framework. [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]

Fixed Satellite Services (FSS) used to be alone at the C-Band spectrum in most countries. Since the deployment of 5G in many countries (i.e., 3.3–3.6 GHz), FSS is not the exclusive system in the C-Band anymore. In order to minimize the detrimental interference for the FSS to allowable levels, regional exclusion zones of maximum radiated power in 5G base stations (BS) are proposed and evaluated. In this paper, a measurement campaign has been carried out, and an analysis of the interference has been studied. A filtering model, namely Filter to Remove Broadband Interference 5G (FIREBRING), is proposed and analyzed concerning the carrier-to-noise ratio (C/N). Moreover, this paper focuses on the evaluation of the 5G interference into the FSS. The proposed solution deployed an Low-Noise Block (LNB) with a band frequency of 3.7 to 4.2 GHz to test the satellite down-conversion signal at the receiver. The paper offered a complete analysis of the 5G signal, taking into account the implications of out-of-band emissions, potentially LNB saturation into FSS receiver, and the repercussions of the deployment of the 5G BS active antenna systems. With the LNB and down-converter in place, it can be found that the signal interference between 1.450 GHz and 1.550 GHz, is nearly 18 dB. [ABSTRACT FROM AUTHOR]

In this paper, an antenna synthesis process is investigated for Intelligent Transportation System (ITS) application. The wireless communication between Road Side Units (RSUs) and On Board Units (OBUs) located in the vehicles enables smart mobility. However, to support high speed vehicles and high data rates, a wider coverage area by the RSU antennas projected on the highway is required. This is defined by the radiation patterns of the RSU antennas. On a multi-lane highway, interference from the adjacent lanes is a critical issue which determines the communication reliability in terms of Single-to-Interference plus Noise Ratio (SINR). Hence, in this paper, an interference-aware antenna synthesis process is proposed and a planar array is optimized based on the objective function of obtaining a wide coverage area in terms of SINR distribution for a given modulation scheme. The proposed antenna array enhances the reliable communication area and provides improved SINR distribution across the lane for misaligned vehicles from the center of the lane. The results indicate that the proposed antenna array performs better than the existing designs in terms of communication reliability. [ABSTRACT FROM AUTHOR]

In this paper, we propose a reference-modulated permutation index differential chaos shift keying (RM-PI-DCSK) over multipath fading channels. Due to quasi-orthogonal property between different permutated chaotic signals, the proposed scheme can remarkably suppress the inter-sequence interference to recover the desired information. Moreover, the proposed RM-PI-DCSK has one more modulation bit in the reference segment than the conventional permutation index differential chaos shift keying (PI-DCSK). Both the reference signal in the first time-slot and a permuted replica of the reference in the second time-slot are modulated for efficient transmission. The theoretical bit-error-rate (BER) performance and the highly consistent simulation results demonstrate that the proposed RM-PI-DCSK can achieve a performance gain 3 dB over the conventional PI-DCSK at a BER of $10^{-4}$ , and this gain becomes larger in a high-delay-spread channel. In particular, the performance superiority of the RM-PI-DCSK is further demonstrated in a typical ultra-wideband (UWB) channel with narrow-band interference. Therefore, this proposed scheme can be deemed as an efficient transmission alternative for chaotic-based wireless communications, such as in wireless local area network (WLAN) applications and indoor applications of the transmitted-reference UWB. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are widely deployed to enhance the wireless network capacity and to provide communication services to mobile users beyond the infrastructure coverage. Recently, with the help of a promising technology called network virtualization, multiple service providers (SPs) can share the infrastructures and wireless resources owned by the mobile network operators (MNOs). Then, they provide specific services to their mobile users using the resources obtained from MNOs. However, wireless resource sharing among SPs is challenging as each SP wants to maximize their utility/profit selfishly while satisfying the QoS requirement of their mobile users. Therefore, in this paper, we propose joint users association and wireless resource sharing problem in the cell-free UAVs-assisted wireless networks with the objective of maximizing the total network utility of the SPs while ensuring QoS constraints of their mobile users and the resource constraints of the UAVs deployed by MNOs. To solve the proposed mixed-integer non-convex problem, we decompose the proposed problem into two subproblems: users association, and resource sharing problems. Then, a two-sided matching algorithm is deployed in order to solve users association problem. We further deploy the whale optimization and Lagrangian relaxation algorithms to solve the resource sharing problem. Finally, extensive numerical results are provided in order to show the effectiveness of our proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cost-efficient beamforming optimization algorithm for multi-user wireless communication systems associated with the intelligent reflecting surface (IRS). From the baseline successive refinement algorithm, which gives a sub-optimal solution for the power minimization problem under the signal-to-interference-plus-noise-ratio (SINR) constraint at each user, several optimization techniques are proposed to reduce the computation complexity while maintaining the algorithm-level performance. To reduce the number of required multiply-accumulate (MAC) operations, we first simplify the complicated matrix inversion by utilizing the channel hardening effect. We also present the two-phase refinement process for the group-level optimization of phase-shift elements, further relaxing the computation complexity as well as the processing latency. Applying the proposed optimization techniques, as a result, numerical results show that the fully-optimized algorithm can reduce the computational costs by up to 89.4% while showing less than 1 dB power loss, leading to the practical solution for the next-generation IRS-aided communication. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) and coordinated multi-point (CoMP) are two fundamental techniques considered for the fifth generation (5 G) of wireless communications. In this paper, a hybrid satellite-unmanned aerial vehicle (UAV) relay network (HSURN) is proposed where the UAV relays (URs) employ CoMP transmission to serve the terrestrial users (UEs). Furthermore, all UEs associated with the CoMP-URs form a single NOMA cluster. For this model, an optimization problem is formulated subject to the minimum quality of services (QoSs) requirements of the UEs, transmission power budgets and, successive interference cancellation (SIC), to select URs and allocate their transmission powers for the energy efficiency (EE) maximization. With this insight, first, a computationally efficient sub-optimal UR selection scheme is proposed. Then, the powers are allocated to the selected URs via the Lagrange multipliers optimization (LMO) method. Due to the non-convex nature of the considered problem, it is relatively difficult to be solved. Hence, a metaheuristic teaching-learning-based optimization (TLBO) algorithm is employed to achieve an efficient solution. Simulation results are provided to verify the effectiveness of the proposed sub-optimal relay selection scheme and the TLBO-based power allocation method compared to the LMO conventional method. Besides, the obtained results also reveal that the CoMP-NOMA transmission in the proposed scenario significantly improves the spectral efficiency (SE) and outage probability (OP) of the system compared to non-comp NOMA transmission case. [ABSTRACT FROM AUTHOR]

The large spectral bandwidth at millimeter-wave (mmWave) frequencies provides a mean to achieve very high data rates in wireless communication systems. A unique characteristic of mmWave is that mmWave links are very sensitive to blockage and have large propagation path loss, which exhibits low line-of-sight (LoS) probability, unstable connectivity and unreliable communication. This paper studies the influence of the blockage in pedestrian scenario, explains in detail how blockage affects the mmWave propagation characteristics. In particular, we study the behavior of the blockage due to human mobility and how it affects the timescale for outage due to blockage using knife-edge diffraction model (KED). One of the existing solutions to overcome the influence of blockage, is to associate the user equipment (UE) with other available base stations (BSs) by handover (HO) if the serving BS is blocked. In this paper, for a pedestrian scenario, we propose two reinforcement learning (RL) based user association algorithms, which accounts for the past experience of the blockage on the position of the UE. One focuses on the reward to increase the sum LoS probability and is named as blockage-aware user association (BAUA). The other focuses on the reward to balance the trade-off between the throughput and the LoS probability and is named as modified BAUA. We compare the proposed algorithm with the conventional user algorithms such as the maximum throughput based algorithm and the maximum SINR based algorithm. Simulation results show that to increase the sum LoS probability BAUA would be suitable, and to increase the average throughput maximum throughput based method would be suitable. [ABSTRACT FROM AUTHOR]

The heterogeneous fog radio access networks (Fog-RAN), the integration of fog computing, and traditional heterogeneous radio access networks can be implemented through the next-generation wireless communication networks. However, most of the solutions are limited to the spectrum efficiency optimization, and cross-tier interference existing in the fog access points (F-APs) could affect the network performance seriously. In this paper, the user association, resource allocation (including bandwidth and power), and caching deployment are investigated in the heterogeneous Fog-RAN to consider energy efficiency and cross-tier interference mitigation. Specifically, the user association, resource allocation, and caching strategy are formulated as a non-convex optimization problem and then transformed into a convex problem, which can be solved by a proposed algorithm based on the concept of the alternating direction method of multipliers (ADMM). Then an ADMM-based algorithm is proposed to enhance the energy efficiency of the Fog-RAN. Compared with the current solutions, simulation results illustrate the proposed algorithm’s convergence and effectiveness. [ABSTRACT FROM AUTHOR]

This paper studies the integration of the newly-emerged intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA)-based wireless powered communication networks (WPCNs). We consider two WPCNs which communicate with a common hybrid access point (HAP), where there exists two types of devices in each WPCN, namely information receiving device (IRD) and harvest-then-transmit device (HTTD). Downlink communication from the HAP to IRDs, downlink energy transfer (ET) from the HAP to HTTDs, and uplink information transmission (IT) from the HTTDs to the HAP are assisted by two IRSs, one in each WPCN. Under this setup, we propose efficient algorithms to optimize reflection coefficients, beamforming vectors, and resource allocation for the sake of uplink sum-rate maximization, taking into account the minimum rate requirement at the IRDs. Numerical results show the considerable performance gain of the proposed NOMA-based scheme as compared to the conventional orthogonal multiple access (OMA)-based counterpart. [ABSTRACT FROM AUTHOR]

Next-generation heterogeneous cellular network (HCN) expects more and more deployment of the base stations and spectrum to achieve data rate in gigabits per second with seamless connectivity. Recently, small cell deployment has proven its effectiveness for increasing the coverage and area spectral efficiency (ASE) of the cellular network. Although, dense small cell deployment also increases the deployment cost and cross-tier interference of the network. This paper suggests switching-based mixed millimeter wave (mmW)/ultra high frequency (UHF) cellular network as a possible solution to overcome these challenges. In mixed mmW/UHF cellular network (named as MMUCN), mmW is used as the main transmission link, and UHF band is utilized as a backup link. In this paper, a theoretical framework is developed using tools from the stochastic geometry to analyze the outage performance, ASE, and deployment cost efficiency (DCE) of the MMUCN, which comprises existing macro base stations and mmW base stations. Optimal mmW base station densities constraints by the outage are calculated, which maximizes the ASE and DCE. Furthermore, a multiobjective optimization problem is formulated to maximize ASE and DCE simultaneously. Numerical results show that MMUCN outperforms UHF-based two-tier cellular network and efficiently mitigates the cross-tier interference of the system. [ABSTRACT FROM AUTHOR]

Due to transmission of train control and dispatch commands, the ultra high reliability is required for railway wireless communication systems (RWCS). However, the quality of service (QoS) of RWCS is affected by external interference and jamming seriously in railway transportation. The external interference and jamming generated from intentional and/or unintentional sources can disturb the transmission of RWCS and be extremely dangerous for the trains’ safety. In this paper, a reconfigurable intelligent surface (RIS) approach is proposed to suppress the interference and jamming in RWCS. By taking the signal-to-interference-plus-noise (SINR) as the QoS metrics, the interference suppression problem with RIS is transformed into a maximizing receiving SINR problem. Two optimum solutions, which one is based on Charnes-Cooper transformation and the other is based on single linear programming, are provided. In order to deploy the RIS in RWCS practically, two low-complexity sub-optimum solutions, which one is to bypass the channel estimation for interference links and the other is to maximize the receiving desired power, are also discussed. The simulations results show that the RIS can be employed in RWCS with considerable anti-interference gain. [ABSTRACT FROM AUTHOR]

Complex building structures constrain indoor wireless communications. The significant dependence between the indoor wireless network performance and the building structures can be considered as an intrinsic property of a building, which means that the building has to be designed to achieve desirable indoor wireless network performance. The power gain (PG) and the interference gain (IG) have been defined as the figures of merit (FoMs) to evaluate the wireless performance of a building. Employing open space as the benchmark, the PG and the IG respectively quantify the effective change of the intended signal power and the undesired power, i.e., the interference and thermal noise power, received in a targeted user equipment (UE) location due to the presence of the building. In this paper, a tractable approach is proposed to obtain the PG and the IG with a partition-based path gain model. It enables the PG and the IG to capture the impact of both building materials and the building layout on indoor wireless network performance. Numerical results show that the analytical models in closed-form expressions facilitate the wireless performance assessment to a given building computational-efficiently. This work is a critical complement to the initial framework of the building wireless performance (BWP) evaluation. The proposed method can be employed in future wireless-friendly building design. [ABSTRACT FROM AUTHOR]

In recent years, wireless communication has experienced a massive shift from a single service (i.e., voice) to an interconnected web of networks. Although many techniques have been developed improving the offered services to mobile users, still the demand for high-quality services cannot be reached. Therefore, this paper proposes a joint non-orthogonal multiple access (NOMA)-enabled optimization framework for small-cell network (SCNet) by utilizing the concepts of multi-objective problem. In particular, the transmit power of base station (BS) in each small-cell simultaneously optimizes to maximize the sum-capacity and total energy efficiency (EE) of SCNet. The multi-objective optimization problem is formulated as non-convex subject to several practical constraints, i.e., individual quality of service requirement, maximum power budget of small-cell BS, and efficient decoding of superimposed signal using successive interference cancellation. Based on the nature of the problem, the optimal solutions are provided using sequential quadratic programming, and Karush-Kuhn-Tucker approaches. The obtained results show significant performance gains over conventional orthogonal multiple access technique in terms of sum-capacity and total EE. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) have been widely applied for classification tasks in wireless communications such as link scheduling, user association and base station (BS) muting. When training a DNN using datasets with highly-skewed class distribution where most data belong to a few majority classes, learning performance for minority classes will degrade since the imbalanced data forces the training process to be biased towards the majority classes. In many wireless problems, multiple decisions for classification are made jointly, say deciding which BSs in a network should be muted to avoid interference. In this paper, we employ DNN to learn an optimal predictive interference coordination policy, and strive to avoid biased learning in such a multi-label multi-class classification problem. The major contribution is proposing a training method to encourage fairness among classes by minimizing the maximal cost of decisions among classes, which is converted into a problem to optimize the weighting factors on the training cost of each class. We provide a gradient descent algorithm to optimize the weighting factors and the model parameters of the DNN by alternative updates. Simulation results show that the training method can improve the learning performance for the minority class and can achieve higher network utility than existing training methods. [ABSTRACT FROM AUTHOR]

In heterogeneous multi-cell networks (HetNets), inter-and intra-cell interference are critical issues impairing the performance. In this paper, the frequency-hopping (FH) technique based on an attractive FH sequence (FHS) set with two-level Hamming correlations is exploited in such networks. Motivating from the idea of no-and low-hit-zone FHS sets, a construction algorithm of the new FHS set is proposed by utilizing the interleaving technique. Then, the performance metric of such FHS set in terms of Hamming correlation properties are derived, which are verified by an example. Compared with classic FHS sets (patterns), the proposed FHS set offers a zero Hamming cross-correlation for intra-cell users, and a low Hamming cross-correlation for inter-cell users (i.e., multi-level quality-of-services). The intra-and inter-interference in multi-cell HetNets can be significantly reduced by the proposed sequence-based FH technique. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) underlay cellular communication plays an important role in the fifth-generation (5G) and beyond communications and its security issues attract a lot of attention. Physical layer security, which explores channel characteristics to protect wireless communications, is very attractive due to its low latency. This paper focuses on secrecy capacity maximization in V2V underlay cellular communications, where the secrecy capacity of vehicular user equipments (VUEs) is optimized first, followed by sum proportional fairness function optimization for both VUEs and cellular user equipments (CUEs). The optimization problems can be solved in two sub-problems, e.g., power and subcarrier allocation problems. The power allocation can be done with the first strategy using a one-dimensional searching algorithm, whereas a genetic algorithm (GA) is used to solve the second optimization problem. In addition, as VUEs share uplink resources with CUEs, the co-channel interference exists and the subcarrier allocation sub-problem is a 3D search problem, which is solved by a two-step iterative Hungarian algorithm (IHA). Finally, simulations are performed to validate the performance of the proposed schemes. [ABSTRACT FROM AUTHOR]

This paper studies multi-agent deep reinforcement learning (MADRL) based resource allocation methods for multi-cell wireless powered communication networks (WPCNs) where multiple hybrid access points (H-APs) wirelessly charge energy-limited users to collect data from them. We design a distributed reinforcement learning strategy where H-APs individually determine time and power allocation variables. Unlike traditional centralized optimization algorithms which require global information collected at a central unit, the proposed MADRL technique models an H-AP as an agent producing its action based only on its own locally observable states. Numerical results verify that the proposed approach can achieve comparable performance of the centralized algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a non-orthogonal multiple access (NOMA) network with simultaneous wireless information, and power transfer (SWIPT) based battery-assisted energy harvesting (EH) full-duplex relay (FDR). In each signalling interval, the base-station communicates directly to a near user (NU), and through an EH FDR to a far user (FU). Considering the power-splitting (PS) protocol with a non-linear EH model, we derive closed-form expressions for the NU, and FU outage probabilities. We also demonstrate how the battery energy, and PS parameter can be chosen to maximize the FU throughput while ensuring a desired NU throughput when there is imperfect interference cancellation at the NU. Computer simulation results validate the accuracy of the derived expressions, and demonstrate that augmenting the harvested energy with a small quantum of the relay's battery energy can considerably improve the FU performance. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) has been widely considered as a promising technology in the next generation wireless communication systems. Various beam-based directional transmission techniques have been proposed to compensate high pathloss caused by mmWave properties. However, mobility effect of users potentially causes severe inter-beam interferences, which has not been fully-investigated in existing studies. In this paper, we have analyzed different types of mobility-aware beam interference models. Additionally, the theoretical SINR is derived based on channel statistics and the trajectories of users. We propose a mobility-aware subband and beam resource allocation (MSBA) scheme for the mmWave subband-beam massive multi-input multi-output (SB-MMIMO) systems. The proposed MSBA benefits from reduced computation complexity for maximizing system throughput constrained by quality-of-service (QoS) demands of users. The first phase of MSBA scheme is responsible for resource block assignment; while the second phase allocates beamwidth and beam directions according to the analytical derivations. Numerical results show that the proposed MSBA scheme can effectively achieve the highest system throughput and the lowest complexity compared to existing schemes in open literatures. [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]

The main focus of this paper is on multistream multiantenna (multiple-input multiple-output) communications in large-scale heterogeneous random networks. Previous work in this area mainly studies the outage probability from the perspective of a given stream, which is inaccurate as it generally overlooks possible interference-driven cross stream signal-to-interference correlation in each communication link. To tackle this issue, in this paper, we focus on a link-level performance evaluation by characterizing the complementary cumulative distribution function (CCDF) of random mutual information (RMI) under heterogeneous interference. We focus on the scenarios that no coordination among transmitters is persuaded, and the receivers do not attempt to cancel out part of interuser interference. Assume that channel state information is known at both the transmitter and receiver of each communication pair, Rayleigh fading, that the singular value decomposition (SVD) is applied to construct pre-coding/post-coding filters for single-user detection, and that transmitted signals of antennas are i.i.d. Gaussian. We first provide accurate expression for the achievable data rate (ADR) of each link, and show that, regardless of the interference power, when transceivers are equipped with equal number of antennas it grows sublinearly with the number of antennas. We then approximate RMI via Gaussian distribution that its mean is the ADR and its variance is derived based on network's parameters. It is seen that the Gaussian approximation is credible even when two streams of data are transmitted. This paper provides various insights regarding the impact of system parameters, including density of transmitters, path-loss exponent, and the number of antennas, on the ADR and CCDF of RMI. We finally spot tremendous benefits of the SVD scheme over other prominent multiplexing systems, including maximum ratio combining, zero-forcing, and diagonal BLAST superstructure with minimum mean square error receivers. [ABSTRACT FROM PUBLISHER]

Vector perturbation (VP) is a nonlinear precoding technique that achieves near-capacity performance in multiuser multiple-input multiple-output systems at the expense of large complexity due to the search for the optimum perturbation vector. In this paper, we present the hybrid Tomlinson–Harashima VP (TH-VP) algorithm, a novel zero-forcing precoding scheme, which combines TH precoding to remove interuser interference, and VP precoding to equalize each user's multiple spatial streams. We show that the two nonlinear techniques can be integrated in a single optimization and that the proposed algorithm has lower computational requirements than any other. The performance of TH-VP is analyzed and simulation results show that TH-VP outperforms conventional zero-forcing VP and approaches the performance of dirty paper coding. [ABSTRACT FROM AUTHOR]

The level crossing rate (LCR) is an important second-order statistical quantity that characterizes the rate of occurrence of fading time intervals. In this paper, we investigate the LCR of multiantenna flat-fading channels in the presence of additive white Gaussian noise and cochannel interferers with unequal received powers and Doppler shifts. We first present a unified approach to derive the exact LCR of the signal-to-interference-noise ratio at a receiver, where maximum ratio combining is deployed over spatially correlated or uncorrelated systems. Through the exact LCR derivation, we identify an accurate approach to obtain a simplified approximate LCR expression in the spatially uncorrelated system case. Benefits of the LCR expressions derived in the paper are demonstrated in two important applications: 1) the packet error rate is evaluated through the finite-state Markov channel model; and 2) the optimum packet length to maximize the throughput of the system with the stop-and-wait automatic repeat request protocol is derived. The analytical results are validated by simulations. [ABSTRACT FROM PUBLISHER]

Convergence and density evolution of a low-complexity iterative multiple-input multiple-output detection based on belief propagation over a ring-type pairwise graph are presented for binary data. The detection algorithm to be considered is effectively a forward–backward recursion and was originally proposed by Yoon and Chae in a work published in 2014, in which link-level performance, computational complexity, and convergence for Gaussian input were analyzed in detail. This paper presents the convergence proof and the density evolution framework for binary input to give an asymptotic performance in terms of average signal-to-interference-plus-noise ratio and bit error rate (BER) without channel coding. The BER curve obtained via density evolution shows a good match with the simulation results for uncoded BER in the paper by Yoon and Chae verifying the effectiveness of the analysis provided and the performance of the detection algorithm. [ABSTRACT FROM AUTHOR]

Recent studies show that the statistical channel state information (SCSI) helps to largely increase the capacity of communication systems when the instantaneous perfect CSI is unavailable. In this paper, we consider multiuser multiple-input-single-output broadcast channels where the transmitter has the knowledge of SCSI. The major issue of concern in our paper is to improve the average group-rate of the whole system by scheduling users over different time slots. With SCSI at the transmitter side, we are able to precode signals and, hence, compute the theoretical achievable group-rate of arbitrary user groups. Based on the group-rates, we propose tier-2 Munkres user scheduling algorithm (T2-MUSA) that leads to higher average group-rate than existing algorithms with generally better fairness. The optimality of the proposed algorithm in energy-fair user scheduling space is proved and we derive a lower bound of a special case to verify the validity of our simulations. In addition, many conventional user scheduling algorithms maintain queue stability by solving a weighted sum-rate (WSR) problem, using queue lengths to represent weight coefficients. Inspired by T2-MUSA, we propose a QoS-based MUSA (QB-MUSA) aimed at stabilizing queue lengths and maximizing throughput. In results, we show that QB-MUSA exhibits higher throughput than the conventional WSR-based algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a green spectrum and infrastructure leasing framework for sharing unused TV spectrum, in which the ownership of the network infrastructure and spectrum are decoupled, and each can be leased as a service on demand. An incumbent TV spectrum owner (TSO) can lease a share of the infrastructure from a network infrastructure owner (NIO) with a pay-per-use model, to provide new services to its end users. On the other hand, a TSO can rent a portion of its unused spectrum to the NIO for revenue such that the NIO can obtain access to the spectrum to serve its customers. This proposed framework achieves green communications through both resource sharing and energy saving. Our paper aims to analyze the interplay between TSO and NIO, and create a win–win situation to provide sufficient incentives for them to cooperate on this green communications. A multistage Stackelberg game is formulated, where TSO and NIO sequentially determine the total bandwidth supply for sharing, the infrastructure leasing price, the amount of infrastructure to lease, the spectrum leasing price, and the amount of spectrum to lease to maximize their utilities. The best strategies that will be taken by the TSO and NIO under various deployment scenarios are analyzed. Evaluation results show that the proposed green spectrum and infrastructure leasing framework is a promising scheme under which both TSO and NIO can benefit, and their utilities can be maximized in terms of user data throughput and revenue/payment, which provides sufficient incentives for them to cooperate. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a heterogenous network in which low-power indoor femtocells are deployed in the coverage area of the existing macrobase station (MBS). This paper proposes a novel coordinated random beamforming and user-scheduling strategy to improve the throughput of users served by the femtocell access point (FAP) while satisfying the quality-of-service (QoS) requirements of users served by both MBS and FAP. The strategy, termed as QoS-aware coordinated scheduling (QACS), requires limited coordination between the MBS and FAP, i.e., only the indexes of the qualified beams are shared. Exact statistical analysis for the ergodic achievable rate of both FAP and MBS with the proposed strategy are presented. Scheduling fairness is also addressed for the proposed QACS. [ABSTRACT FROM PUBLISHER]

In this paper, a full-duplex unmanned aerial vehicle-(UAV) base station is used to provide wireless communication to an area lacking a conventional terrestrial infrastructure, and its efficient deployment is investigated. More concretely, the UAV positioning and resource allocation problems are solved with the aim of minimizing the transmit power of the UAV, while serving users with their rate requirements and accounting for the backhaul limitation of the UAV. To this end, a complete solution for the optimal 3D position of the UAV, the bandwidth assignment and the transmit power distribution in the access and backhaul links is proposed that accounts for both the backhaul interference and the self-interference. When the UAV power budget is insufficient to fulfill rate requirements, non-orthogonal multiple access (NOMA) pairing is conducted to enhance system performance. Simulation results show that, when using the proposed approach, both the achieved sum rate and the percentage of satisfied users are significantly increased, when compared to a strategy that uses separate frequency bands in the access and backhaul links, as well as to a previously proposed method. [ABSTRACT FROM AUTHOR]

Deploying a large number of distributed access points (AP)s to serve a smaller number of users is one of the promising network architectures for future wireless communication systems. Such network architecture can be operated as a distributed massive multiple-input multiple-output (MIMO) system or as a small-cell (SC) system to satisfy the anticipated high rate requirements for beyond-5G networks. However, in a practical scenario with non-ideal hardware components and high-velocity users, the network experiences an inevitable performance degradation. This paper aims at analyzing the network performance under the operation of distributed massive MIMO and SC systems, taking into account the impairments of real and dynamic systems. Considering multiple-antennas APs, we derive novel closed-form expressions for the downlink (DL) spectral efficiency of both systems. We reveal that limiting the number of served users per AP in distributed massive MIMO systems leads to a corresponding loss in the performance, especially under max-min power control. Besides, despite the SC system provides the largest per-user average DL rate under the deployment of ideal APs, distributed massive MIMO systems become superior in the presence of non-ideal APs. Notably, while increasing the number of deployed non-ideal APs can reduce the introduced loss in distributed massive MIMO systems, this leads to an extra performance loss in SC systems. Finally, we show that the presence of high-velocity users is more harsh in SC systems. In addition, our results show that the SC system operation is more suitable for low-velocity users, however, it is better to operate networks with high velocities users under the distributed massive MIMO systems operation. [ABSTRACT FROM AUTHOR]

In this paper, we study the secure transmission in multiple access wiretap channels when the instantaneous channel state information (CSI) of the wiretap channels is unknown by the legitimate users. We propose a two-phase jamming-assisted secure transmission scheme based on the randomness and independence of wireless channels. In this scheme, we appropriately design artificial noise in two transmission phases and make sure that the eavesdropper's channel is degraded by the artificial noise but the legitimate user's channel is free of the artificial noise. We analyze the capacity of the legitimate channel after using successive interference cancellation (SIC), and demonstrate that the eavesdropping capacity has an upper bound. Furthermore, we prove that a positive secrecy rate can be achieved and the achievable secrecy rate can be maximized by allocating appropriate power to the private information and the artificial noise. [ABSTRACT FROM AUTHOR]

Due to the advantages of high mobility, high maneuverability and high probability of line of sight (LoS) transmission, unmanned aerial vehicles (UAVs) have attracted much interest in assisting wireless communication systems. This paper considers a set of ground users cannot receive service from the base station because of a sudden base station malfunction, a UAV is deployed in the air to work as a relay to establish communication links between uncovered users and the neighboring base station. We are going to optimize the UAV relay deployment, aiming to maximize the capacity of the relay network. Considering the channel model and exact positions of ground users are priori unknown, the problem of deployment optimization can't be solved directly because of lacking parameters. Thus, considering multiple detecting UAVs are available and only one is available, model-free online deployment approaches are respectively proposed to solve this challenging problem. The optimal relay deployment is acquired via online learning and iteration without the knowledge of channel model and exact positions of the users but with the real-time measurement of relay capacity, thus the proposed model-free deployment approaches can be adaptive to the practical communication environment compared to the model-based optimization. Simulation results show that with the proposed model-free deployment approaches, relay network capacities are close to the optimum. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new concept of a knowledge management framework to enable a self-optimizing and self-learning for wireless system operation in real time. The framework encapsulates both environment and intelligent agent to reach optimal operation through sensing, perception, reasoning, and learning in a truly autonomous fashion. The agent derives adequate knowledge from previous actions improving the quality of future decisions. Domain experience was provided to guide the agent while exploring and exploiting the set of possible actions in the environment. Thus, it guarantees low-cost learning and achieves a near-optimal network configuration addressing the non-deterministic polynomial-time hardness problem of joint channel and location optimization in a wireless system. Extensive simulations are run to validate its fast convergence, high throughput, and resilience to dynamic interference conditions. We deploy the framework on off-the-shelf wireless devices to propose autonomous self-optimization with knowledge management. [ABSTRACT FROM AUTHOR]

This paper investigates an integrated wireless communication system including non-orthogonal multiple access, full-duplex relaying, and energy harvesting techniques (named as EH-FD-NOMA). In this scheme, an energy-limited full-duplex relay harvests energy from a source at the first stage. Then, the relay detects the superimposed signal from the source and transmits the decoded signal to destination. Closed-form outage probabilities and ergodic rates at the relay and destination are derived. Numerical results verify the analytical results and show the superior performance of the EH-FD-NOMA if compared to its counterparts. [ABSTRACT FROM AUTHOR]

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]

This paper investigates low-complexity joint interference avoidance and desired link improvement for single-channel allocation in multiuser multiantenna access points (APs) for open-access small cells. It is considered that an active user is equipped with an antenna array that can be used to suppress interference sources but not to provide spatial diversity. On the other hand, the operation of APs can be coordinated to meet design requirements, where each of which can unconditionally utilize assigned physical channels. Moreover, each AP is equipped with uncorrelated antennas that can be reused simultaneously to serve many active users. The analysis provides new approaches to exploit physical channels, transmit antennas, and APs to mitigate interference, while providing the best possible link gain to an active user through the most suitable interference-free channel. The event of concurrent service requests placed by active users on a specific interference-free channel is discussed for either interference avoidance through identifying unshared channels or desired link improvement via multiuser scheduling. The applicability of the approaches to balance downlink loads is explained, and practical scenarios due to imperfect identification of interference-free channels and/or the scheduled user are thoroughly investigated. The developed results are applicable for any statistical and geometric models of the allocated channel to an active user, as well as channel conditions of interference users. They can be used to study various performance measures. Numerical and simulation results are presented to explain some outcomes of this paper. [ABSTRACT FROM PUBLISHER]

In this paper, secure communication aided by a multiantenna cooperative jammer is investigated. Under very practical but adverse assumptions, i.e., no instantaneous jammer–eavesdropper channel state information (CSI) and imperfect instantaneous jammer–receiver CSI, the residual interference from the jammer to the legitimate receiver appears, even with spatial beamforming. Then, this paper analyzes the impact of imperfect CSI on the function of cooperative jamming and derives closed-form expressions of multiple secrecy performance metrics, including ergodic secrecy rate, secrecy outage capacity, and interception probability. Interestingly, it is found that two antennas at the jammer is always optimal. Furthermore, some insights are obtained through asymptotic analysis, e.g., the secrecy performance is saturated as the source transmit power increases, the ergodic secrecy rate is a linear function of CSI feedback bits in the region of high transmit power at the source/jammer, and interception probability is independent of transmit power at the source and is a decreasing function of transmit power at the jammer. Finally, theoretical claims are validated by simulation results. [ABSTRACT FROM PUBLISHER]

This paper studies the cooperative device-to-device (D2D) transmissions in cellular networks, where two D2D users communicate bidirectionally with each other and simultaneously serve as relays to assist the two-way transmissions between two cellular users. For this scenario, both cellular and D2D links share the same spectrum, thus creating mutual interference. In addition to that, a security problem also exists since the cellular users want to keep their messages secret from the D2D users and vice versa. To address these two issues, a security-embedded interference avoidance scheme is proposed in this paper. By exploiting the constellation rotation technique, the proposed scheme can create interference-free links for both D2D and cellular communications, thereby significantly improving the system error performance. Moreover, our scheme also provides an inherent secrecy protection at the physical layer, which makes the information exchange between cellular users and that between D2D users confidential from each other. [ABSTRACT FROM PUBLISHER]

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]

Security and privacy have become increasingly critical demands in wireless networks, which, however, are particularly susceptible to eavesdropping attacks due to the broadcast nature of radio signals. This paper considers the problem of secure communication in the multiuser downlink with a passive eavesdropper (Eve), whose channel state information (CSI) is unavailable. The transmitter simultaneously transmits concurrent information signals to the users and artificial noise (AN) to Eve. We first assume that all users' CSI is perfectly known by the transmitter and derive a closed-form expression for the ergodic secrecy sum rate (SSR) in the large-system limit. We then use it as an objective function to optimize the power allocation between information signals and the AN. It shows that more power needs to be used for AN when Eve has more antennas and when the system serves fewer users. We also extend the analysis to the imperfect-CSI scenario, where the SSR saturates at high transmit power, and it is better to create more AN than to increase the signal strength when the channel estimation error is large. We derive a scale law of feedback bits (for frequency-division duplexing (FDD) systems) to maintain a constant rate offset compared with the perfect-CSI case and the optimal length of training sequence (for time-division duplexing (TDD) systems) to maximize the effective SSR. It shows that more feedback bits and longer training sequences are required to deal with the eavesdropping problem. Closed-form expressions derived in this paper can reduce the complexity of system analysis and design. [ABSTRACT FROM PUBLISHER]

The advancement of integrated millimeter-wave products opens the possibility of leveraging communications in 60-GHz band to meet the unprecedented traffic demand in WLAN. Despite the vast bandwidth available, millimeter-wave signals suffer from high attenuation and weak diffraction ability. Therefore, wireless communication at 60 GHz is characterized by the inherent directivity and susceptibility to blockage. Multiple Access Point (AP) architecture is proposed for 60-GHz WLAN to enhance spatial reuse and survive blockage. In the presence of multiple APs in the network, this paper addresses the important problem of user-AP association and resource allocation. We study three schemes of different complexity and investigate how to maximize user throughput with joint consideration of AP assignment and transmission scheduling. To solve the formulated problem, we propose a branch-and-cut-based solution procedure. We perform a detailed comparative analysis of the three schemes and advocate to use one-shot AP assignment-based scheduling scheme due to its simplicity and good performance. To deal with real-time traffic and human blockage, we propose an online algorithm to implement the one-shot AP assignment-based scheme to avoid frequent service disruption. Our results show that the proposed online algorithm is competitive when compared with the optimal offline algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we explore the different per-user bandwidths available for each tier of heterogeneous networks (HetNets) and the corresponding downlink range expansion (RE, a key measure to boost small cell association). Based on the practical case of tier-specific path loss exponents, we derive the local delay of HetNets under the random discontinuous transmission scheme (DTX, employed to manage the interference and reduce energy consumption). Using such a new expression for local delay, we then analyze the corresponding energy efficiency (EE). These delay and EE expressions reveal that there exists an optimal value for both the RE bias factor and for the DTX mute probability. A closed-form optimum solution for the RE bias factor is also derived for the low-rate regime. [ABSTRACT FROM AUTHOR]

Sparse code multiple access (SCMA) is one type of non-orthogonal multiple access techniques for the fifth-generation wireless communication networks. Existing multiuser detection algorithms for SCMA uplink systems are based on the assumption that signals are in synchronization. However, asynchrony cannot be neglected due to the propagation delays in practical environments. In this paper, we present three detection algorithms for uplink asynchronous SCMA systems, namely belief propagation message passing algorithm, belief propagation with equal gain combining message passing algorithm, and partial phase-coherent algorithms. Simulation results show that our proposed asynchronous detection algorithms are able to offer descent bit error rate performances, with only a small performances loss compared to the synchronous case. Moreover, our proposed algorithms converge well in the uplink asynchronous SCMA systems. [ABSTRACT FROM AUTHOR]

Spectral efficiency analysis in presence of correlated desired and interfering signals is very important in densely deployed access points scenarios of modern generation wireless networks. However, most works available in literature either address the effect of correlated interfering signals or include interferer activity. Further, available literature has also addressed the effect of large-scale fading (shadowing and distance-dependent path loss) only however, they have fallen short of including the composite effect of line-of-sight and nonline-of-sight multipath small-scale fading. The correlation of desired signals with interfering signals because of shadowing has also not been considered in existing literature either. In this paper, we present a comprehensive analytical signal to interference power ratio evaluation framework addressing all the above-mentioned important propagation effects in a holistic manner. In this analysis, we extend and apply the moment generating function-matching method to such systems to achieve high accuracy. We compare the analytical results against realistic channel model based extensive Monte-Carlo simulation for millimeter Wave and sub-6 GHz in both indoor and outdoor scenarios. The performance of the model is depicted in terms of mean, $\alpha \%$ outage spectral efficiency, and Kullback–Leibler divergence and Kolmogorov–Smirnov distance. [ABSTRACT FROM AUTHOR]

In this paper, a general two-way relay (TWR) transmission method is proposed under per-antenna power constraints by combining space-time line codes (STLCs) with transmit power allocation for two source nodes. We introduce a general STLC-based encoding scheme for a decode-and-forward TWR and derive the detection signal-to-interference-plus-noise ratio (SINR) values at two source nodes. An optimal encoder structure with power allocation is proposed in terms of maximizing the minimum SINRs, and it is verified that the optimal encoder is identical to the superposition of two conventional STLCs. An iterative method is proposed to find the optimal power allocation for detection at two source nodes. Moreover, a low-complexity suboptimal encoder is proposed for practical implementation. Numerical simulations present that the proposed STLC-based transmission method outperforms a conventional eigen-beamforming scheme with nulling and an STLC-based scheme with equal power allocation, in terms of the average bit error rate of source nodes, regardless of the distribution of source nodes, the number of TWR antennas, and the transmit power. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communications underlaying cellular networks have been recognized as a promising technology to improve the system capacity and spectral efficiency of 5G networks. In this paper, we investigate the problem of designing the joint uplink subcarrier assignment and power allocation scheme to optimize the sum data rate of D2D pairs, under a general “many-to-many” scenario in which a subcarrier could be shared by multiple D2D pairs and a D2D pair could also reuse multiple subcarriers. In particular, the optimization problem is to maximize the sum data rate of all D2D pairs under the constraints of minimum data rate requirements of cellular user equipments (CUEs). The formulated problem falls into a mixed integer nonlinear programming, which is generally NP-hard. To solve the problem, we decompose it into two subproblems: the subcarrier assignment subproblem and the power allocation subproblem. More specifically, we first propose an effective algorithm to assign subcarriers for both D2D pairs and CUEs under the assumption that the transmit power of each user is equally allocated among all the subcarriers. After that, we apply the successive convex approximation approach to transform the nonconvex power allocation problem into a sequence of convex problems, based on which an effective power allocation algorithm is designed. Simulations validate that the proposed scheme can significantly improve the achievable sum data rate of D2D pairs, compared with the other existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the anti-jamming channel selection problem for interference mitigation (IM) based dense wireless networks in dynamic environment, in which the active user set is variable due to their specific traffic demands. We jointly consider the mutual interference among users and external jamming in IM-based dense wireless networks, and propose a generalized maximum protocol interference and jamming model to accurately capture the mutual interference and external jamming. Then, the anti-jamming channel selection problem is formulated as an anti-jamming dynamic game, and subsequently it is proved to be an exact potential game, which has at least one pure strategy Nash equilibrium (NE). Based on the stochastic learning theory, a distributed anti-jamming channel selection algorithm (DACSA) is proposed to find the NE solution. Moreover, the simulation results are presented to demonstrate the effectiveness of the proposed DACSA algorithm. [ABSTRACT FROM AUTHOR]

Modern models for public safety networks (PSN) utilize commercial user equipment (UE) and exclusively rely on cellular architecture. This paper introduces a heterogeneous PSN mechanism where multiple wireless protocols are used to establish resilient communications. Specifically, each UE acts as a learning automaton and using a reinforcement-learning approach selects the most appropriate operation protocol, in terms of environment/topology needs, protocol specifications, and PSN battery-life extension. In addition, we follow a UE coalition formation approach, using a Chinese restaurant process that considers UEs’ communication interest, physical distance, and energy availability. Finally, each UE's optimal transmission power is obtained using the formulation of a utility-based power control problem as a non-cooperative, distributed game among UEs, which converges to a unique Nash equilibrium. The performance of the proposed approach is evaluated using modeling and simulation under several scenarios; also, its superiority is demonstrated. [ABSTRACT FROM AUTHOR]