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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 concerns the uplink of multicell multiuser multiple-input multiple-output (MIMO) systems. To tackle the effect of pilot contamination that is generally viewed as a bottleneck in previous work, this paper presents a superimposed pilot (SP)-aided uplink channel estimation scheme and mathematically characterizes the impact that an SP has on the performance of such a very large MIMO system. It is shown that there are two types of interference components that do not vanish, even when the number of antennas $M$ grows to infinity. The first type, which is referred to as cross-contamination, is due to the correlation between the SP and data among different cells. The second type, which is referred to as self-contamination, is due to the dependence between channel estimation and estimation error. Cross-contamination is, in principle, similar to pilot contamination in a conventional pilot-based multicell MIMO system, whereas self-contamination is unique for the SP-aided scheme. Both theoretical and simulation results demonstrate that the SP-aided scheme can effectively reduce the estimation contamination by increasing the data frame size and, in turn, achieve a significant improvement over the spectral efficiency, in comparison with conventional pilot-based methods. [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]

This paper focuses on precoding design for sum-rate maximization while considering the effects of residual self-interference for multiuser multiple-input–multiple-output (MU-MIMO) full-duplex (FD) systems. The problem formulation leads to a nonconvex matrix-variable optimization problem, where we develop two efficient sum-rate maximization algorithms using sequential convex programming (SCP), namely, the difference of convex functions (DC)-based and the sequential convex approximations for matrix-variable programming (SCAMP) algorithms. In addition, we derive the achievable sum rate under the effect of residual self-interference. Simulation results show that, even in cases of high self-interference and high estimation error, the SCAMP algorithm provides approximately 20%–30% sum-rate improvements over both conventional optimized half-duplex (HD) transmission and the existing state-of-the-art FD algorithm in a wide range of scenarios. Finally, the convergence results indicate that the DC-based algorithm tends to initially give the best performance; however, at convergence, the SCAMP algorithm tends to significantly outperform the other algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we design receivers for filter bank multicarrier-based (FBMC-based) massive MIMO considering practical aspects such as channel estimation and equalization. In particular, we propose a spectrally efficient pilot structure and a channel estimation technique in the uplink to jointly estimate all the users’ channel impulse responses. We mathematically analyze our proposed channel estimator and find the statistics of the channel estimation errors. These statistics are incorporated into our proposed equalizers to deal with the imperfect channel state information (CSI) effect. We revisit the channel equalization problem for FBMC-based massive MIMO, address the shortcomings of the existing equalizers in the literature, and make them more applicable to practical scenarios. The proposed receiver in this paper consists of two stages. In the first stage, a linear combining of the received signals at the base station (BS) antennas provides a coarse channel equalization and removes any multiuser interference. In the second stage, a per subcarrier fractionally spaced equalizer (FSE) takes care of any residual distortion of the channel for the user of interest. We propose an FSE design based on the equivalent channel at the linear combiner output. This enables the applicability of our proposed technique to small and/or distributed antenna setups such as cell-free massive MIMO. Finally, the efficacy of the proposed techniques is corroborated through numerical analysis. [ABSTRACT FROM AUTHOR]

The ease of acquiring hardware-based link quality indicators (LQIs) is an alluring property for fast channel estimation in time- and safety-critical wireless sensor network (WSN) applications, such as closed-loop control and interlocking. The two rudimentary hardware-based channel quality metrics, i.e., received signal strength (RSS) and LQI, are the key constituents of channel estimation and a plethora of other WSN functionalities, from routing to transmit power control. Nevertheless, this paper highlights three deficient aspects of these two indicators: 1) Overall deceptiveness, i.e., the inability to reveal the presence of interference, falsely indicating excellent channel conditions in an unacceptably high fraction of cases; 2) the burstiness of missed detection which compromises the attempts to eliminate the deceptiveness by averaging; and 3) high mutual discrepancy of the two indicators, which is observed in 39%–73% of packets, throughout different scenarios. The ability of RSS and LQI to indicate IEEE 802.11 interference is scrutinized in a variety of scenarios in typical industrial environments using commercial-off-the-shelf hardware and realistic network topologies, giving the findings of this paper high general validity and practical relevance. [ABSTRACT FROM PUBLISHER]

This paper investigates a channel-coded multiuser system operated with orthogonal frequency-division multiplexing (OFDM) and interleaved-division multiple access (IDMA). In general, there are many variations to multiuser systems. Our choice of the combination of OFDM and IDMA is motivated by its ability to achieve multiuser diversity gain in frequency-selective multiple-access channels. To realize OFDM-IDMA, however, two challenges must be addressed. The first challenge is the estimation of multiple channel parameters, particularly how to contain the estimation errors of the channel parameters of the multiple users, considering that the overall estimation errors may increase with the number of users because the estimations of their channel parameters are intertwined with each other. The second challenge is that the transmitters of the multiple users may be driven by different radio-frequency oscillators. The associated frequency asynchrony may cause multiple carrier frequency offsets (CFOs) at the receiver. Compared with a single-user receiver where the single CFO can be compensated away at the receiver prior to channel decoding, a particular difficulty for a multiuser receiver is that it is not possible to compensate away all the multiple CFOs simultaneously. To tackle the two challenges, we put forth an integrated framework to solve the problems of multiuser channel-parameter estimation, CFO compensation, and channel decoding jointly and iteratively. The framework employs the space-alternating generalized expectation-maximization (SAGE) algorithm to decompose the multiuser problem into multiple single-user problems and the expectation-conditional maximization (ECM) algorithm to tackle each of the single-user subproblems. Iterative executions of SAGE and ECM in the framework allow the two aforementioned challenges to be tackled in an optimal manner. Simulation results indicate that, compared with other approaches, our approach can achieve significant bit-error-rate (BER) and mean-square-error (MSE) improvements. [ABSTRACT FROM PUBLISHER]

In multi-user multiple-input–multiple-output (MU-MIMO) systems that employ pilot-symbol aided channel estimation, the pilot-to-data power ratio (PDPR) has a large impact on the system performance. In this paper, we consider the problem of setting the PDPR in multi-cell MU-MIMO systems in the presence of channel estimation errors, intercell interference and pilot contamination. To analyze and address this problem, we first develop a model of the multi-cell MU-MIMO system and derive a closed-form expression for the mean squared error of the uplink received data symbols. Building on this result, we then propose two decentralized PDPR-setting algorithms based on game theoretic approaches that are applicable in multi-cell systems. We find that both algorithms converge to a Nash equilibrium and provide performance improvements over systems that do not properly set the PDPR, while they maintain different levels of fairness. [ABSTRACT FROM AUTHOR]

In this paper, we propose regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We derive secrecy sum rate and asymptotic secrecy sum rate for the proposed scheme. The optimum power allocation for legitimate users and the AN signal are derived in closed form for optimal asymptotic secrecy sum rate. Our analysis shows that to achieve best performance, it is more efficient to degrade the performance of the eavesdropper than improving legitimate users’ rates. We also study the impact of error in channel estimation on the system and derive closed-form SINR and secrecy sum-rate expressions for this case. Simulations show that the secrecy sum rate of RBD precoding outperforms the secrecy sum rate of regularized channel inversion by 0.5 bits/s/Hz. We also show that in the presence of channel estimation error, our approximate closed forms for secrecy sum rate are very closed to the actual secrecy sum rate over a wide range of SNR and channel estimation error values. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the outage performance of a decode-and-forward (DF) relay system with two low-complexity relay selection schemes and interference at the relays and the destination. The schemes are mainly based on the switch-and-examine diversity combining (SEC) and SEC postexamine selection (SECps) techniques in which a relay out of multiple relays is selected to forward the source message to the destination. The selection process is performed such that the signal-to-noise ratio (SNR) of the second hop of the selected relay satisfies a predetermined switching threshold. In this paper, we first derive the probability density function (pdf) of the SNR of the relay selection scheme and the conditional cumulative distribution function (cdf) of the end-to-end (e2e) signal-to-interference-plus-noise ratio (SINR), assuming Rayleigh fading channels. The derived statistics, along with the statistics of first-hop channels of the relays and the direct link, are then used to derive a closed-form expression of the e2e outage probability. Maximal-ratio combining (MRC) is used at the destination to combine the signals from the relay and the direct link. Furthermore, the outage performance is studied at the high-SNR regime where approximate expressions for the outage probability, diversity order, and coding gain are derived and analyzed. Monte Carlo simulations and some numerical examples are provided to illustrate the validity of the derived results and to show the effect of interference and other parameters on the system performance. Main results illustrate that when the interference power is fixed, the system can still achieve some performance gain when more relays are added, particularly at SNR values that are comparable with the switching threshold. Asymptotic results show that at a high SNR, the system with the SEC and SECps relaying schemes achieves a diversity order of 2 and approximately the same coding gain. Finally, findings illustrate that the interference at the destination is more severe on the system performance compared with that at the relays. [ABSTRACT FROM PUBLISHER]

In this paper, we consider nonregenerative multipair two-way relaying systems, where a relay node supports $K$ pairs of two-way communications in the presence of imperfect channel state information (CSI). We employ a stochastic approach to model the channel uncertainties and study a robust beamforming design at the relay. It is shown that the proposed beamformer provides a reduction in the computational complexity, as well as good robustness against channel errors, compared with conventional designs. To reduce the estimation overhead at the users, we also suggest an efficient downlink training method to inform the users of the channel-dependent self-interference cancellation (SIC) parameters. With the training method, the additive noise may incur a malfunction of the SIC. To address this issue, we develop an intelligent selection criterion that decides whether the SIC should be adopted or not. Finally, from simulation results, we demonstrate the efficiency of our proposed schemes. [ABSTRACT FROM PUBLISHER]

We study multiuser detection for uplink transmissions using only analog beamformers in a millimeter-wave (mm-wave) communication system under a limited scattering environment in this paper. In particular, the successive interference cancelation (SIC)-based detection at a base station (BS) that is equipped with an antenna array is considered with the outputs of analog beamformers. We employ beam selection from a codebook of analog beams for low-complexity analog beamforming in the SIC-based detection and compressive sensing (CS)-based channel estimation that is suitable for the BS that only has analog beamformers. Through simulation results, we can see that the performance of the joint analog beam selection and SIC-based detection is comparable with the performance of the SIC-based detection (with ideal digital beamforming) at the cost of more antenna elements with lower complexity. [ABSTRACT FROM AUTHOR]

This paper studies user-specific clustering for a downlink cloud radio access network (C-RAN), where a central unit (CU), connected to all base stations (BSs) via limited-capacity backhaul links, coordinates the BSs to form cooperative clusters for every user. By taking into account the training overhead for channel estimation in C-RAN, we design the clustering scheme aimed at maximizing the average net throughput of the network subject to the constraint on backhaul capacity, where a hybrid coordinated multipoint (CoMP) transmission mode is considered. The proposed clustering scheme can be operated in a semi-dynamic manner merely based on large-scale channel information, has low computational complexity, and performs close to the optimal scheme found by exhaustive searching. Under two special cases where the backhaul capacity is very stringent and unlimited, the proposed scheme is then tailored for pure coordinated beamforming (CB) mode and pure joint transmission (JT) mode to further reduce the clustering complexity. Simulation results show that the proposed semi-dynamic clustering schemes are superior to the dynamic clustering scheme due to the reduction of required training overhead. [ABSTRACT FROM AUTHOR]

In the presence of perfect channel state information (CSI), the achievable degrees of freedom (DoF) in wireless interference networks can be linearly scaled up with the number of users. Achievability is based on the idea of interference alignment (IA). However, in the presence of imperfect CSI, the sum rate becomes degraded, and full DoF may no longer be achievable. In this paper, we propose novel least squares (LS)- and minimum mean square error (MMSE)-based IA schemes that adaptively design beamformers by relying on the availability of imperfect CSI and knowledge of the channel estimation error variance in advance. Interestingly and unlike the other robust algorithms, the proposed adaptive schemes do not impose extra computational complexity compared to their nonadaptive counterparts. It is shown that the LS-based IA is able to outperform interference leakage minimization algorithms under both perfect and imperfect CSI. Furthermore, we compare the performance of the proposed MMSE-based IA with maximum signal-to-interference-plus-noise ratio (Max-SINR) algorithm. We show that while under perfect CSI, the MMSE-based IA achieves the same performance as that of Max-SINR, the former outperforms the latter under CSI mismatch. Meanwhile, it is shown that the proposed MMSE-based IA needs less CSI to be available and has less computational complexity compared to Max-SINR. [ABSTRACT FROM PUBLISHER]

Device-to-device (D2D) communication is developed as a new paradigm to enhance network performance according to LTE and WiMAX advanced standards. The D2D communication may have dedicated spectrum (overlay) or shared spectrum (underlay). However, the allocated dedicated spectrum may not be effectively used in the overlay mode, while interference between the D2D users and cellular users cause impairments in the underlay mode. Can the resource allocation of a D2D system be optimized using the cognitive approach where the D2D users opportunistically access the underutilized radio spectrum? That is the focus of this paper. In this paper, the transmission rate of the D2D users is optimized while simultaneously satisfying five sets of constraints related to power, interference, and data rate, modeling D2D users as cognitive secondary users. Furthermore, a two-stage approach is considered to allocate the radio resources efficiently. A new adaptive subcarrier allocation scheme is designed first, and then, a novel power allocation scheme is developed utilizing geometric water-filling approach that provides optimal solution with low computation complexity for this nonlinear problem. Numerical results show that the proposed approach achieved significant performance enhancement than the existing schemes. [ABSTRACT FROM PUBLISHER]

Cognitive radio networks (CRNs) and millimeter wave (mmWave) communications are two major technologies to enhance the spectrum efficiency (SE). Considering that the SE improvement in the CRNs is limited due to the interference temperature imposed on the primary user (PU), and the severe path loss and high directivity in mmWave communications make it vulnerable to blockage events, we introduce an intelligent reflecting surface (IRS) into mmWave CRNs. Due to the estimation mismatch and the passivity of Eavesdroppers (Eves), perfect channel state information (CSI) of wiretap links is challenging to obtain, which promotes our research on robust secure beamforming (BF) design in the IRS-assisted mmWave CRNs. This paper considers the collaborate scenario of Eves, which allows us to investigate the BF design in the harsh eavesdropping environment. Specifically, by using a uniform linear array (ULA) at the cognitive base station (CBS) and a uniform planar array (UPA) at the IRS, and supposing that imperfect CSIs of angle-of-departures for wiretap links are known, we formulate a constrained problem to maximize the worst-case achievable secrecy rate (ASR) of the secondary user (SU) by jointly designing the transmit BF at the CBS and reflect BF at the IRS. To solve the non-convex problem with coupled variables, an efficient alternating optimization algorithm is proposed. As for the transmit BF at the CBS, we propose a heuristic robust transmit BF algorithm to attain the BF vectors analytically. As for the reflect BF at the IRS, by means of an auxiliary variable, we transform the non-convex problem into a semi-definite programming problem with rank-1 constraint, which is handled with the help of an iterative penalty function, and then obtain the optimal reflect BF through CVX. Finally, simulation results indicate that the ASR performance of our proposed algorithm has a small gap with that of the optimal solution with perfect CSI compared with the other benchmarks. [ABSTRACT FROM AUTHOR]

A major performance limiter in amplify-and-forward (AF) full-duplex (FD) relaying is the high level of residual self-interference (SI) due to the imperfect estimation of the effective self-interfering channel. One primary obstacle that contributes to the ineffectiveness of estimating the effective SI channel is the transceiver's radio-frequency (RF) impairments. In this paper, we consider the effect of in-phase/quadrature imbalance (IQI) on the process of SI cancellation in FD AF transceivers. We model the cumulative SI as a function of IQI, and thoroughly analyze the stability of the performance of the relay by analyzing the different transmission parameters and configurations that guarantee the stability of the system. In particular, depending on the RF impairments of the relay's transceiver, the wireless channel conditions, and the channel estimation accuracy, the relay's maximum amplification factor and transmission power that limit the residual SI power and prevent the system oscillations are analytically derived and verified by Monte-Carlo simulations. Finally, we show that the average SI power is bounded by a sum of scaled Gamma functions. [ABSTRACT FROM AUTHOR]

In this paper, we study the optimal training design for multiple-input multiple-output (MIMO) amplify-and-forward (AF) two-way relay systems in the presence of interference. In order to address the interference issue while accurately estimating the channels, we minimize the total transmit power consumed by two source nodes and a relay subject to the constraint on mean square error (MSE) of the channel estimation, which is a nonconvex problem. To solve this challenging problem, we first derive the optimal structure of the training signals, and then, we convert the original problem into a tractable convex form, from which the optimal training scheme is designed efficiently. We further consider a practical special case, for which the optimal training scheme is designed with a lower complexity and the useful insights into the optimal training design are obtained. Also, to reduce the computational complexity of the optimal training design, we propose an asymptotically optimal training scheme in the high signal-to-interference-plus-noise ratio (SINR) regime with a low complexity. Simulation results demonstrate that the proposed schemes significantly outperform the existing schemes. [ABSTRACT FROM AUTHOR]

The terahertz (THz) waves with enormous bandwidth can be used along with the existing sub-6GHz and millimeter wave (mmWave) bands to achieve the ever evolving ecosystem of applications that need to be supported by the modern wireless networks. This paper investigates a user-centric dynamic base station (BS) clustering design for a hybrid network where THz, mmWave, and sub-6GHz BSs coexist. Invoking the proposed clustering model, the BS cooperation within each band is made possible by considering long term channel variations and all the surrounding BSs within a cluster with tunable size. A typical user is associated with the best BS cluster, from either a sub-6GHz, mmWave or THz tier based on the maximum signal-to-interference-plus-noise-ratio (SINR) criterion or the maximum rate criterion. Using tools from stochastic geometry, we assess the performance of the proposed user-centric hybrid system in terms of SINR and rate coverage performances, while accounting for: band specific propagation models, directional beamfroming, and BSs random locations. The accuracy of the analytical results is validated with Monte-Carlo simulations. The obtained results recognize a clear coverage/rate trade-off where a high fraction of THz BSs improves the rate significantly but may degrade the coverage performance. Thus, with carefully planned networks, enabling user-centric BS cooperation for hybrid wireless systems can achieve ultra-high rates while maintaining sufficient coverage in sixth-generation (6G) networks. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a multiple access technique for supporting massive number of devices with high spectral efficiency. Simultaneous wireless information and power transfer (SWIPT) is an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in networks employing cooperative NOMA (CNOMA) is investigated with imperfect channel state information (CSI). Performance of the CNOMA network with SWIPT is investigated in a multi-tier downlink scenario with macro-base stations (MBSs) and femto-base stations (FBSs). The distribution of MBSs and FBSs follow Poisson point process model. Unlike solution in the existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating node/user employs EH using interference from the adjacent base stations. Expressions for outage probability and throughput are derived at the user pair (comprising a cell-center user and a cell-edge user) served using NOMA. Comparison of the proposed EH system with the existing solutions is highlighted. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a non-data-aided (NDA) method to estimate the noise variance for orthogonal frequency division multiplexing (OFDM) system in frequency-selective channels. The proposed method is developed based on the signal correlation introduced by the use of the cyclic prefix (CP) and uses the difference between two discrete Fourier transform (DFT) outputs in the CP interval to estimate the noise variance. Analytical result shows that the obtained noise variance is an unbiased estimate in a quasi-static fading channel. Simulation results show that, even in the case in which the maximum delay spread is equal to the CP length and the channel is not quasi-static, the proposed method still works well. [ABSTRACT FROM PUBLISHER]

We consider a two-way half-duplex relaying system where multiple pairs of single-antenna users exchange information assisted by a multiple-antenna relay. Taking into account the practical constraint of imperfect channel knowledge, we study the achievable sum spectral efficiency (SE) of the amplify-and-forward protocol, assuming that the relay employs maximum ratio processing. We derive a closed-form expression for the sum SE for arbitrary system parameters and a large-scale approximation for the sum SE when the number of relay antennas $M$ becomes sufficiently large. In addition, we study how the transmit power reduces with $M$ to maintain a desired SE. Our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to $1/M^\alpha$ , $1/M^\beta$ , and $1/M^\gamma$ for certain combinations of $\alpha$ , $\beta$ , and $\gamma$ , respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum SE, novel power allocation schemes are designed to further improve the sum SE. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) has emerged as a promising supplement to existing radio frequency-based communication systems. Recently, the use of massive light emitting diodes (LED) and photodetector (PD) arrays have been proposed to increase the capacity of the overall VLC link. At the receiver, the signals received by the PD arrays are combined to enhance the achievable data rates. However, successful combining and subsequent detection depends on accurate channel estimation. In this paper, we consider a typical massive multiple input multiple output VLC scenario with maximal ratio combining, and derive an asymptotic analytical expression for the probability density function (p.d.f) of the residual additive distortion for mobile users. Since the minimum error entropy (MEE)-based learning paradigm outperforms the traditional Bussgang approaches due to the incorporation of order statistics, we derive an MEE-based channel estimator using the analytical expression for the p.d.f of the additive distortion. Simulations are carried out for various LED array-sizes, and under various LED transmit half angles. Furthermore, using the analytically derived p.d.f, the proposed MEE-criterion-based channel estimator achieves lower bit error rate, and faster convergence, as compared to existing minimum mean square error based channel estimator. [ABSTRACT FROM AUTHOR]

This paper proposes a channel estimation scheme for the filter-bank multicarrier systems with quadrature amplitude modulation (FBMC-QAM). Under frequency selective channels, the adjacent data symbols cause interference to the pilot symbols in FBMC-QAM systems and degrade the performance of the channel estimation. To handle this problem, we analyze the interference of the pilot symbols in an oversampled frequency domain before the receiver filtering process. Exploiting the interference analysis, we propose a pilot symbol configuration and condition of filter coefficients to cancel the inter-carrier interference. Moreover, we apply a time domain data symbol precoding to eliminate inter-symbol interference. The simulation results show that the proposed scheme outperforms conventional channel estimation schemes. [ABSTRACT FROM AUTHOR]

In this correspondence paper, we design a massive nonorthogonal multiple access (NOMA) scheme with delay provisioning for cellular internet-of-things. In the context of massive access, the severe interuser interference decreases the quality of the received signal, such that it is a nontrivial task to provide a delay provisioning for heterogeneous wireless services. To solve this challenge, we propose a massive NOMA scheme to meet the delay requirements of a large number of users by exploiting the properties of rateless codes. Especially, we present a power allocation algorithm to minimize the power consumption while achieving delay-constrained massive access. Finally, simulation results validate the effectiveness of the proposed scheme. [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]

In this paper, a robust transmit power control scheme is proposed for multi-channel underlay device-to-device (D2D) communications with imperfect channel state information (CSI). The transmit power of the D2D user equipment (DUE) on each channel is optimized to maximize the average spectral efficiency (SE) whilst maintaining the quality-of-service (QoS) of the cellular user equipment (CUE) in the presence of errors in the CSI. To this end, we propose a novel deep neural network (DNN) structure and training methodology, in which artificially distorted CSI is used to compensate for the effect of imperfect CSI, such that a robust transmit power control strategy against channel error can be derived. Our simulation results show that even when the CSI is inaccurate, in our proposed scheme the degradation of the average SE can be kept low whilst maintaining negligible QoS violation, thereby confirming its effectiveness and robustness. [ABSTRACT FROM AUTHOR]

This paper proposes an amplify-and-forward-based massive multiple-input–multiple-output full-duplex relaying (AF-MM-FDR) protocol, where multiple source–destination pairs communicate simultaneously with a common full-duplex relay. A zero-forcing (ZF)-based relay transceiver design with semiblind gain control is presented, considering the problem of relay oscillation. The asymptotic expression of end-to-end signal-to-interference-plus-noise power (SINR) is derived under the general power scaling scheme. The scaling behaviors of echo interference (EI) and effective channel estimation error are determined. Scaling results show that the deployment of very large antenna arrays at the relay has the potential to eliminate the effect of EI due to the full-duplex operation, if the power scaling scheme is selected properly. Moreover, based on the asymptotic analysis, a low-complexity power control scheme is proposed to optimize the spectral efficiency of AF-MM-FDR. Simulation results show that the proposed power control scheme improves the spectral–energy efficiency tradeoff of AF-MM-FDR significantly. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel scattered pilot method for channel estimation in filter-bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) systems. We refer to this as the coded auxiliary pilot (CAP) method. It builds on the idea of using a few auxiliary pilot (AP) symbols to eliminate the imaginary interference on each scattered pilot. At the same time, to keep the spectral efficiency of transmission high, the AP symbols are coded to also carry information symbols. Theoretical analysis and numerical results show that the CAP method can maintain high spectral efficiency and high power efficiency, while achieving complete imaginary interference cancelation. Taking the spectral and power efficiency, the imaginary interference cancelation performance, and the coding/decoding complexity into consideration, the CAP method with two to four AP symbols is identified as a good compromised choice for practice. [ABSTRACT FROM AUTHOR]

In this paper, we consider time-domain vector perturbation (TDVP) in a large-system limit when channel state information (CSI) is imperfect due to pilot contamination, and we derive the system's achievable sum rate per cell. We use random matrix methods to avoid time-consuming Monte Carlo simulations. Numerical results show that, in general, linear precoding ensures a higher sum rate than TDVP in the massive multiple-input–multiple-output (MIMO) regime. [ABSTRACT FROM AUTHOR]

For large-scale antenna array multiple-input multiple-output (MIMO) systems, a typical solution often put forward for uplink detection consists in applying low-complexity linear receivers such as zero-forcing (ZF) and minimum mean-square error (MMSE) combiners. In this paper, the performance of uplink MMSE detection has been analyzed in the context of a multi-cell multiuser MIMO system. An approximate expression for the signal-to-interference-plus-noise ratio (SINR) is proposed, which is in simple form and becomes exact in the low SNR regime. This approximate SINR applies to systems where the base station (BS) has the statistical information of the out-of-cell interfering signals, and systems where the BS ignores the presence of such interfering signals. This approximate SINR is tight for arbitrary user powers, arbitrary number of antennas at the base station, and arbitrary channel correlation matrix associated with any particular user. Approximate expressions for capacity and bit-error rate/symbol-error rate have also been derived. Particularly, it can be proven that, when the MMSE receiver ignores the presence of out-of-cell interfering signals, the performance gap between ZF and MMSE vanishes in the high SNR regime. [ABSTRACT FROM AUTHOR]

This paper proposes a flexible pilot assignment method to jointly optimize the uplink and downlink data transmission in multi-cell Massive multiple input multiple output (MIMO) systems with correlated Rayleigh fading channels. By utilizing a closed-form expression of the ergodic spectral efficiency (SE) achieved with maximum ratio processing, we formulate an optimization problem for maximizing the minimum weighted sum of the uplink and downlink SEs subject to the transmit powers and pilot assignment sets. This combinatiorial optimization problem is solved by two sequential algorithms: a heuristic pilot assignment is first proposed to obtain a good pilot reuse set and the data power control is then implemented. Numerical results manifest that the proposed algorithm converges fast to a better minimum sum SE per user than the algorithms in previous works. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel algorithm to optimize the energy efficiency (EE) of orthogonal frequency-division multiplexing (OFDM)-based cognitive radio systems under channel uncertainties. We formulate an optimization problem that guarantees a minimum required rate and a specified power budget for the secondary user (SU) while restricting the interference to primary users (PUs) in a statistical manner. The optimization problem is nonconvex, and it is transformed to an equivalent problem using the concept of fractional programming. Unlike all related works in the literature, we consider the effect of imperfect channel-state information (CSI) on the links between the SU transmitter and receiver pairs, and we additionally consider the effect of limited sensing capabilities of the SU. Since the interference constraints are met statistically, the SU transmitter does not require perfect CSI feedback from the PUs' receivers. Simulation results show that the EE deteriorates as the channel estimation error increases. Comparisons with relevant works from the literature show that the interference thresholds at the PUs' receivers can be severely exceeded and that the EE is slightly deteriorated if the SU does not account for spectrum sensing errors. [ABSTRACT FROM PUBLISHER]

Linear decoding of space–frequency block codes (SFBCs) based on the Alamouti structure with orthogonal frequency-division multiplexing (OFDM) requires the channel to be constant across two consecutive tones. However, time-dispersive multipath fading channels exhibit frequency-selective behavior wherein the channel across two tones will vary. This paper provides analytical tools for evaluating the performance of SFBCs with OFDM in frequency-selective channels. The analysis uses the average signal-to-interference-plus-noise ratio (SINR) as a sufficient statistic to describe the performance of SFBCs in frequency-selective channels. A unified formula is derived to characterize the channel correlation between two consecutive tones for various frequency-selective channels. A closed-form solution of the average SINR is obtained, which takes into account imperfect channel estimation and frequency selectivity. An interpolation method of the channel estimate is proposed, which is shown to improve the bit-error-rate performance by 3 dB at a high SNR. The accuracy of the theoretical analyses is verified by numerical simulations under multipath channels such as the International Telecommunications Union (ITU) pedestrian and vehicular models. [ABSTRACT FROM PUBLISHER]

Coordinated multipoint (CoMP) transmission can provide high spectral efficiency for cellular systems if perfect channels are available. In limited feedback systems, except for channel direction, signal-to-noise-plus-interference ratio (SINR) is necessary to assist in user scheduling and adaptive transmission. When the methods to estimate SINR in single-cell systems is applied to CoMP systems, the performance will significantly degrade. In this paper, we estimate the SINR for downlink CoMP systems. We start by showing that the quantization error vector is no longer isotropic when quantizing CoMP channels. This implies that the vector has an inherent structure. We proceed to formulate an optimization problem to find the quantization error vector that maximizes the multiuser interference power under the structure constraint. This way, we can exploit the nonisotropic nature of the quantization error vector and avoid overestimating the SINR. Simulation results show that the proposed method provides high throughput and low outage probability with negligible extra feedback overhead. [ABSTRACT FROM PUBLISHER]

The radio channel assignment (RCA) in wireless networks is an optimization problem that is often found NP-complete. For networks of practical sizes, various heuristic algorithms are used to solve it. However, there are two major issues: finding a globally optimized solution without relying on specific interference models and estimating the computational complexity of general heuristic algorithms. In this paper, we propose a new simulated annealing (SA)-based RCA (SRCA) algorithm to find the globally optimized channel assignment in a distributed way but with bounded computational complexity. We propose using effective channel utilization (ECU) as the evaluation vector, whereas the objective function is to maximize the total ECU in a neighborhood. The ECU can be easily calculated by an access point (AP). The impact of interference is included in the ECU. We propose a hybrid method for estimating the algorithm's computational scale (CS), i.e., the number of channel reallocations until the network reaches a convergence state, by combining analytical and experimental methods. The resulting algorithm is a dynamic and distributed algorithm. Our extensive simulation results have demonstrated that it quickly achieves 99% of the global maximum with a chance over 95%, whereas its complexity is linear with the number of routers in the network. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel receiver design for orthogonal frequency division multiplexing (OFDM) transmission over time-varying channels, where the receiver employs a turbo message passing (TMP) framework for a joint channel estimation and the data detection. We show that the proposed TMP-based receiver is able to make more efficient use of the prior information about the channel and the data for intercarrier interference cancellation than the existing iterative receivers. The proposed TMP algorithm can be further combined with a soft-input soft-output decoder for the joint channel estimation, data detection, and decoding. Numerical results are presented to demonstrate the performance superiority of our proposed TMP-based OFDM receiver. [ABSTRACT FROM AUTHOR]

Differential orthogonal frequency division multiplexing (OFDM) is practically attractive for underwater acoustic communications since it has the potential to obviate channel estimation. However, similar to coherent OFDM, it may suffer from severe inter-carrier interference over time-varying channels. To alleviate the induced performance degradation, we adopt the newly emerging partial fast Fourier transform (FFT) demodulation technique in this paper and propose an eigendecomposition-based algorithm to compute the combining weights. Compared to existing adaptive methods, the new algorithm can avoid error propagation and eliminate the need for parameter tuning. Moreover, it guarantees global optimality under the narrowband Doppler assumption, with the optimal weight vector of partial FFT demodulation achieved by the eigenvector associated with the smallest eigenvalue of the pilot detection error matrix. Finally, the algorithm can also be extended straightforwardly to perform subband-wise computation to counteract wideband Doppler effects. [ABSTRACT FROM AUTHOR]

This paper is concerned with the sum-rate maximization problem in multiple-input multiple-output interference channels. We design the transmit covariance matrix, associated with each transmitter to maximize the sum-rate of the network when the number of data symbols is unknown. The design problem is nonconvex and then hard to be solved. We devise a semidistributed design methodology according to majorization–minimization technique to deal with the optimization problem. This leads us to a convex quadratically constrained quadratic program at each iteration with a semiclosed form solution. The proposed method is computationally efficient and converges to stationary points of the problem. The fact that the method is based on a distributed processing framework along with relatively low computational burden ( $\mathcal{O}(\max \lbrace M,N\rbrace ^{2.3})$ per iteration with $M$ and $N$ being the number of antennas at the transmitter and receiver, respectively) for the user terminals can make it a potential candidate for practical implementations. Finally, we extend the proposed method for the case with channel estimation errors. Simulation results verify the efficiency of the proposed method, and in a typical scenario we have around 60 times lower run-time when compared to the counterparts of the method. [ABSTRACT FROM AUTHOR]

This paper considers a novel virtual pilot-assisted channel estimation algorithm for multiple input multiple output single carrier frequency domain equalization (MIMO-SCFDE) systems over fast time-varying multipath channels. Given that the fast time-varying channels can no longer support the assumption that the channel frequency-domain response remains invariant for the duration of one SC-FDE symbol, most of the channel estimation methods cannot be directly applied to MIMO-SCFDE systems. We put forward an iterative interfrequency interference cancellation method for the time-varying multipath channels over one SC-FDE symbol. The proposed method utilizes the virtual pilot-assisted channel estimation and partial minimum-mean-square-error equalization to improve the accuracy of the estimation. Simulation results validate the improved performance of the proposed method for MIMO-SCFDE systems over fast time-varying multipath channels. [ABSTRACT FROM AUTHOR]

This paper investigates an outage-constrained secrecy rate maximization (OC-SRM) problem based on the statistical channel uncertainty assumption in an underlay multiple-input multiple-output (MIMO) cognitive radio network, where the secondary transmitter provides simultaneous wireless information and power transfer to receivers. Our objective is to design the transmit covariance matrix and artificial noise aided covariance matrix through maximizing the secrecy rate of the secondary user while satisfying the given outage probability requirements. The designed problem is nonconvex and challenging. We employ the existing theory to reformulate the original problem into two equivalent subproblems by introducing auxiliary variables in order to overcome the difficulty arising from the Shannon capacity expression. The Bernstein-type inequality approach is resorted to conservatively approximate the probabilistic constraints. The merit of the transformation and conversion is that the tractable solutions of the original OC-SRM problem can be easily obtained through solving two convex conic subproblems alternately. Furthermore, we extend the proposed algorithm to solve full uncertainty model design. Numerical results demonstrate the efficacy of the proposed designs. [ABSTRACT FROM AUTHOR]

Combined with N-continuous (NC) precoding, the spatial modulation (SM) orthogonal frequency division multiplexing (OFDM) system offers considerable sidelobe suppression for the downlink transmission, at the cost of additional interference to the transmit signal. Therefore, this paper focuses on investigating the impact of the NC precoder on the bit error rate (BER) performance of the SM-OFDM system. The BER performance is analyzed over the frequency-selective Rayleigh fading channel under two distinct scenarios, i.e., perfect channel estimation and interference suppression based minimum mean square error (MMSE) channel estimation. First, we propose an approximate system model for the NC precoded SM-OFDM system along with an analysis on the introduced interference, and then derive the average BER performance of the system with perfect channel estimation. Based on the above proposed approximate system model, we further analyze the interference based upon MMSE channel estimation, and investigate the characteristics of channel estimation errors. Furthermore, we derive the average BER performance of the NC precoded SM-OFDM system with imperfect channel estimation. The numerical results show that the analytical BER closely matches its simulated counterpart under different system configurations, and demonstrate that the proposed approximate system model is in good agreement with the precise one. [ABSTRACT FROM PUBLISHER]

This paper proposes a new artificial noise (AN) scheme that combines with the relay selection techniques to improve the physical layer security for a wiretap full-duplex decode-and-forward cooperative network. The communication consists of two phases. In the first phase, the source transmits a message to the selected full-duplex relay, which simultaneously injects AN to mitigate eavesdropping attacks. In the second phase, the selected relay decodes the source message, XORs the source message and AN, and then broadcasts the mixed-signal to the destination. Different form existing schemes, the proposed AN scheme makes the eavesdropper fail in obtaining any information about the source message directly in the second phase. We take into account the correlation of the channel coefficients for the same link during different phases in the performance analysis of AN-aided max-min (MM) and partial (Par) relay selection schemes, and characterize the security-reliability trade-off (SRT) of the proposed schemes by the closed-form expressions of outage probability and intercept probability. Numerical results show that the proposed AN-aided MM/Par relay selection achieves a better SRT performance than the corresponding full-duplex mode assisted AN-aided relay selection scheme in existing literature. Furthermore, the MM scheme outperforms the Par scheme in terms of the SRT, and the SRT of the MM scheme can be substantially improved by increasing the number of relays, while the improvement of the Par scheme is limited. [ABSTRACT FROM AUTHOR]

Benefiting from high spectral efficiency, agility of carrier aggregation and support for asynchronous transmissions, offset quadrature amplitude modulation based filter bank multicarrier (OQAM/FBMC) is being developed as an attractive alternative to cyclic-prefix based orthogonal frequency division multiplexing (CP-OFDM) as the air interface technology for future communications. However, its non-orthogonal nature results in intrinsic interference among symbols and subcarriers, which makes channel estimation in OQAM/FBMC significantly more difficult than that in CP-OFDM. In this paper, we propose a novel preamble design method based on intrinsic interference utilization for OQAM/FBMC channel estimation. Specifically, we build a preamble by triplets of subcarriers, each of which is determined by a preamble power optimization problem that minimizes the channel estimation mean square error (MSE) at the central subcarrier. We derive the optimal closed-form solution by exploiting the linearly dependent relationship between preamble symbols and intrinsic interference weights. Moreover, extensions to multiple-input multiple-output (MIMO) setup capable of improving both spectral efficiency and channel estimation performance are investigated. Theoretical analysis and simulation results show the superiority of the proposed preamble design method over the conventional methods in terms of channel estimation MSE, bit error ratio (BER) and peak-to-average power ratio (PAPR). [ABSTRACT FROM AUTHOR]

The homogeneous Poisson point process is widely used to model spatial distribution of base stations and mobile terminals. The same process can be used to model underlay device-to-device (D2D) network; however, neglecting homophilic relation for D2D pairing presents underestimated system insights. In this paper, we model both spatial and social distributions of interfering D2D nodes as proximity-based independently marked homogeneous Poisson point process. The proximity considers physical distance between D2D nodes whereas social relationship is modeled as Zipf-based marks. We apply these two paradigms to analyze the effect of interference on coverage probability of distance-proportional power-controlled cellular user. Effectively, we apply two types of functional mappings (physical distance, social marks) to Laplace functional of PPP. The resulting coverage probability has no closed-form expression; however, for a subset of social marks, the mark summation converges to digamma and polygamma functions. This subset constitutes the upper and lower bounds on coverage probability. We present numerical evaluation of these bounds on coverage probability by varying number of different parameters. The results show that by imparting simple power control on cellular user, ultradense underlay D2D network can be realized without compromising the coverage probability of cellular user. [ABSTRACT FROM PUBLISHER]

In wireless localization services, a wideband spectrum is required for high resolution ranging. For this purpose, unlicensed bands have received substantial interest for their potential to reduce deployment cost. However, in the unlicensed spectrum, narrowband interference is often present and distorts band-limited reference signals for channel impulse response (CIR) estimation that is a key component to determine the location of users. In this paper, we propose a new Bayesian compressive sensing (BCS) framework to estimate complex-valued targets and apply it to mitigate the impact of subband interference on CIR estimation accuracy. Our Bayesian approach estimates the CIR by maximizing the posterior probability of the CIR from frequency domain signals in which a portion of the signal is corrupted by the interference. Based on the BCS framework, we propose three interference mitigation techniques that utilize the information on interfered subbands differently. We demonstrate the superior performance of the proposed schemes by showing improved ranging error statistics using measured indoor channels in the 5.8 GHz band. [ABSTRACT FROM AUTHOR]

In interference channels, channel state information (CSI) can be exploited to reduce the interference signal dimensions, and thus, achieve the optimal capacity scaling, i.e., degrees of freedom, promised by the interference alignment technique. However, imperfect CSI, due to channel estimation error, imperfect CSI feedback and time selectivity of the channel, lead to a performance loss. In this paper, we propose a novel limited feedback algorithm for single-input single-output interference alignment in time-variant channels. The feedback algorithm encodes the channel evolution in a small number of subspace coefficients, which allow for reduced-rank channel prediction to compensate for the channel estimation error due to time selectivity of the fading process and feedback delay. An upper bound for the rate loss caused by feedback quantization and channel prediction is derived. Based on this bound, we develop a dimension switching algorithm for the reduced-rank predictor to find the best tradeoff between quantization and prediction error. Besides, we characterize the scaling of the required number of feedback bits in order to decouple the rate loss due to channel quantization from the transmit power. Simulation results show that a rate gain over the traditional nonpredictive feedback strategy can be secured and a $60\%$ higher rate is achieved at 20-dB signal-to-noise ratio with moderatesxst mobility. [ABSTRACT FROM PUBLISHER]

In this paper, we study a two-way relaying system with analog network coding whereby both the relay and the two sources are under the effect of erroneous channel state information (CSI) and network interference that originate from a Poisson field of interferers. Our contribution is twofold: 1) We characterize the interference affecting the aforementioned nodes by presenting a general model that incorporates the expected correlation of the interference process that affects the relay, which in turn affects the two sources; 2) by deriving the interference statistics, particularly its first moment, we also derive analytical formulas for the distribution of the signal-to-interference-plus-noise ratio (SINR) of the two sources in the high-SINR region, which reveal that in that region, the amount of correlation between the interference processes affecting the relay and the two sources does not affect the SINR distribution. These statistics are subsequently used to derive analytical expressions of the average sum symbol error rate (SER) and the achievable average sum rate of the system. Finally, the theoretical results are corroborated by means of Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

Providing ubiquitous connectivity inside a mobile vehicle is a challenging task that requires efficient vehicle-to-infrastructure communication. A wireless mesh network (WMN) provides a cost-effective and easily maintainable solution to manage the backhaul of vehicular communication. The mesh points (MPs) act as access points for mobile vehicles and connect them to the Internet through multihop mesh communication. IEEE 802.11s is the recent standard for a WMN, which provides mesh coordinated function controlled channel access (MCCA) for efficient and minimum-contention channel access at MPs. However, the standard MCCA-based communication provides equal-time fair channel access, which is not suitable for vehicular communication. This paper proposes an efficient channel access mechanism based on IEEE 802.11s MCCA to provide proportionally fair channel access. A distributed scheme is proposed to calculate traffic load at every MP, and based on the traffic load, the MCCA is tuned to meet the required proportionality constraint. The efficiency of the proposed scheme is confirmed using theoretical analysis and simulation results. [ABSTRACT FROM PUBLISHER]

This paper investigates pilot design and allocation in multi-cell massive multiple-input multiple-output systems with two-tier receiving. As the length of pilot is limited, the pilots cannot be orthogonal and cause interference. The sum rate as well as the signal-to-interference-plus-noise ratio (SINR) of the system are firstly analyzed. The sum rate upper bound and the asymptotic SINR are derived. The analysis shows that the pilot correlation and the spatial correlation jointly affect the sum rate. Based on this observation, the discrete Fourier transform vectors are employed in designing pilots with various correlation values. Then, with the channel correlation information and the designed pilots, the pilots are allocated to the cells in a greedy way with the object of maximizing the sum rate upper bound. Moreover, the sum rate analysis, the pilot design, and the pilot allocation are extended to the scenario with grouped correlations. Simulation results show that the proposed pilot design and allocation performs better than other pilots and the derived upper bound is effective. [ABSTRACT FROM AUTHOR]