Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.NPRP grant 6-070-2-024 from the Qatar National Research Fund (a member of Qatar Foundation)Scopu

Sparse Equalizers for OFDM Signals with Insufficient Cyclic Prefix

The cyclic prefix (CP) is appended in orthogonal frequency division multiplexing (OFDM) signals to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) induced by the communication channel, which limits its spectral efficiency. Therefore, inserting an insufficient CP and equalizing the resulting ICI and ISI is a method that has been circulating the literature for a while, aiming at increasing the efficiency of OFDM systems. In this paper, we propose a reduced-complexity sparse linear equalizer and a decision-feedback equalizer for OFDM signals with insufficient CP. A performance-complexity trade-off is highlighted, where we show that it is possible to equalize the received signal with a reduced complexity equalizer while having a limited performance loss. Our proposed equalizer designs are not only less complex to realize, but are shown to provide a higher data rate. The proposed equalizers are further evaluated in terms of the worst-case coherence, a metric determining the effectiveness of our used approach. Numerical results show that we can significantly and reliably reduce the order of the design complexity while performing very close to the conventional complex optimal equalizers. 2013 IEEE.This work was supported by GSRA from the Qatar National Research Fund (a member of Qatar Foundation) under Grant 2-1-0601-14011. The statements made herein are solely the responsibility of the authors.Scopu

QoS-Aware Precoder Optimization for Radar Sensing and Multiuser Communications Under Per-Antenna Power Constraints

In this work, we concentrate on designing the precoder for the multiple-input multiple-output (MIMO) dual functional radar-communication (DFRC) system, where the dual-functional waveform is designed for performing multiuser downlink transmission and radar sensing simultaneously. Specifically, considering the signal-independent interference and signal-dependent clutter, we investigate the optimization of transmit precoding for maximizing the sensing signal-to-interference-plus-noise ratio (SINR) at the radar receiver under the constraint of the minimum SINR received at multiple communication users and per-antenna power budget. The formulated problem is challenging to solve due to the nonconovex objective function and nonconvex per-antenna power constraint. In particular, for the signal-independent interference case, we propose a distance-majorization induced algorithm to approximate the nonconvex problem as a sequence of convex problems whose optima can be obtained in closed form. Subsequently, our complexity analysis shows that our proposed algorithm has a much lower computational complexity than the widely-adopted semidefinite relaxation (SDR)-based algorithm. For the signal-dependent clutter case, we employ the fractional programming to transform the nonconvex problem into a sequence of subproblems, and then we propose a distance-majorization based algorithm to obtain the solution of each subproblem in closed form. Finally, simulation results confirm the performance superiority of our proposed algorithms when compared with the SDR-based approach. In conclusion, the novelty of this work is to propose an efficient algorithm for handling the typical problem in designing the DFRC precoder, which achieves better performance with a much lower complexity than the state-of-the-art algorithm

Joint beamforming design for secure RIS-assisted IoT networks

This paper studies secure communication in an internet-of-things (IoT) network, where the confidential signal is sent by an active refracting reconfigurable intelligent surface (RIS)-based transmitter, and a passive reflective RIS is utilized to improve the secrecy performance of users in the presence of multiple eavesdroppers. Specifically, we aim to maximize the weighted sum secrecy rate by jointly designing the power allocation, transmit beamforming (BF) of the refracting RIS, and the phase shifts of the reflective RIS. To solve the non-convex optimization problem, we propose a linearization method to approximate the objective function into a linear form. Then, an alternating optimization (AO) scheme is proposed to jointly optimize the power allocation factors, BF vector and phase shifts, where the first one is found using the Lagrange dual method, while the latter two are obtained by utilizing the penalty dual decomposition method. Moreover, considering the demands of green and secure communications, by applying the Dinkelbach’s method, we extend our proposed scheme to solving a secrecy energy maximization problem. Finally, simulation results demonstrate the effectiveness of the proposed design

Active RIS Assisted Rate-Splitting Multiple Access Network: Spectral and Energy Efficiency Tradeoff

With the increasing demand of high data rate and massive access in both ultra-dense and industrial Internet-of-things networks, spectral efficiency (SE) and energy efficiency (EE) are regarded as two important and inter-related performance metrics for future networks. In this paper, we investigate a novel integration of rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) into cellular systems to achieve a desirable tradeoff between SE and EE. Different from the commonly used passive RIS, we adopt reflection elements with active load to improve a newly defined metric, called resource efficiency (RE), which is capable of striking a balance between SE and EE. This paper focuses on the RE optimization by jointly designing the base station (BS) transmit precoding and RIS beamforming (BF) while guaranteeing the transmit and forward power budgets of the BS and RIS, respectively. To efficiently tackle the challenges for solving the RE maximization problem due to its fractional objective function, coupled optimization variables, and discrete coefficient constraint, the formulated nonconvex problem is solved by proposing a two-stage optimization framework. For the outer stage problem, a quadratic transformation is used to recast the fractional objective into a linear form, and a closed-form solution is obtained by using auxiliary variables. For the inner stage problem, the system sum rate is approximated into a linear function. Then, an alternating optimization (AO) algorithm is proposed to optimize the BS precoding and RIS BF iteratively, by utilizing the penalty dual decomposition (PDD) method. Simulation results demonstrate the superiority of the proposed design compared to other benchmarks

IEEE Access Special Section Editorial: Advances in Power Line Communication and its Applications

Power line communication (PLC) is a growing technology which utilizes the existing pre-installed power delivery infrastructure for data transmission. While it is true that the history of PLC technology goes back to the beginning of the last century, when the first data transmission over power lines took place for low data rate control and monitoring purposes, PLC has recently regained a considerable amount of research attention due to the dawn of the internet and the increasing need for fast connectivity. PLC is also expected to serve as a reliable communication medium for many emerging applications of Internet of Things (IoT) and Smart Grids (SGs)

Advances in single carrier block modulation with frequency domain processing

International audienceThis special issue focuses on single carrier block modulation (SC-BM) with frequency domain processing. This class of modulation and multiple access schemes complements the orthogonal frequency division multiple access (OFDMA) and its variations. For example, LTE (the long term evolution of the 3GPP standard), and LTE-Advanced, employ OFDMA in the downlink (base stations to mobiles) and SC-FDMA, a version of SC-BM in the uplink (mobiles to base stations). The main reason for adapting the technology of SC-FDMA for uplink LTE is the fact that OFDMA has high "peak-to-average power ratio" (PAPR), which is a disadvantage for mobile devices that are limited by power availability. Besides its advantage of low PAPR, SC-BM technology has a similar performance/complexity to that of OFDMA, and simple frequency domain equalization methods for combating dispersive channels. There were 17 papers submitted to this special issue. All had merits, but the review process reduced the number of accepted papers to 9. The accepted papers cover a number of novel and advanced aspects of single carrier block modulation with frequency domain processing: near-optimal nonlinear and iterative equalization techniques; applications to CDMA, MIMO and ARQ; channel estimation; and application to free-space optical transmission. Following is a summary of the papers. In the paper "Iterative Successive Interference Cancellation for Quasi-Synchronous Block Spread CDMA Based on the Orders of the Times of Arrival", Wang, Bocus, and Coon [1] describe an interference cancellation scheme based on the times of arrival of the signals from different users, and they show that for practical channels this ordering criterion is equivalent to ordering with respect to decreasing average SINR. In "Complexity Reduced MLD Based on QR Decomposition in OFDM MIMO Multiplexing with Frequency Domain Spreading and Code Multiplexing", Nagatomi, Kawai, and Higuchi [2] propose a reduced-complexity maximum likelihood signal detection method for MIMO-OFDM systems with frequency-domain spreading and code multiplexing. They show how to exploit signal orthogonalization based on QR decomposition of the product of the channel and spreading code matrices in the frequency domain to obtain significant complexity reductions. In "Frequency-domain Block Signal detection with QRM-MLD for Training Sequence-aided Single-carrier Transmission", Yamamoto, Takeda and Adachi [3] propose replacement of the cyclic prefix with a known training sequence. The object is to improve BER performance of an equalization scheme which uses QR decomposition with M-algorithm detection, while keeping the number of surviving paths low for reduced complexity. The scheme is especially effective for 16QAM and 64QAM modulation. The paper "Joint Iterative Tx/Rx MMSE-FDE and ISI Cancellation for Single-carrier Hybrid ARQ with Chase Combining" by Takeda and Adachi [4] applies transmitter and receiver equalization and iterative intersymbol interference cancellation to a system with hybrid ARQ transmission, Chase combining and antenna diversity. The equalizer parameters at both transmitter and receiver are optimized for each retransmission. The paper "Novel Techniques of Single Carrier Frequency Domain Equalization for Optical Wireless Communications" by Acolaste, Bar-Ness, and Wilson [5] investigates the application of single-carrier frequency-domain equalization to diffuse optical wireless communications and demonstrates its advantages over OFDM in terms of reduced PAPR and improved error rate in the presence of LED nonlinearity. In the paper "Semi-Blind Channel Estimation for IFDMA in Case of Channels with Large Delay Spreads", Sohl and Klein [6] propose a subspace-based channel estimation algorithm which can cope with large delay spreads. In previous work on IFDMA, the number of channel taps that can be estimated was limited to the number of subcarriers per user. The subspace analysis in this paper relaxes this constraint and increases the number of taps that can be estimated. The paper "Channel Frequency response Estimation for MIMO with Systems with Frequency-Domain Equalization " by Yang, Shi, Chew, and Tjhung [7] suggests a training-based channel frequency response (CFR) estimation scheme which is hardware efficient when integrated with and SC-FDE and space time coding (STC) in MIMO Systems. An MSE analysis of this CFR estimation scheme is provided, which considered linear estimators based on both LS and minimum MSE criteria. Also with a given constraint which effectively limits the transmit power of the training signals, the paper investigates the optimal design of training signals under different a priori knowledge of the channel statistics. For the special case of 2 transmit antennas, it was demonstrated that CFR estimation could be implemented in adaptive manner. The paper by Dang, Ruder, Schober and Gerstacker [8], "MMSE Beamforming for SC-FDMA Transmission over MIMO ISI Channels", derives minimum mean squared error beamforming strategies for multi-antenna reception, as well as further modifications to reduce the transmitted peak to average power ratios. The paper by Nishino, Tanahashi, and Ochiai [9], "A Bit Labeling Design for Trellis-Shaped Single-Carrier PSK with PAPR Reduction", investigates application of trellis shaping to reduce the PAPR of band-limited single-carrier PSK signals. The authors demonstrate that the uncoded bit error rate and PAPR reduction capability of trellis shaping is highly dependent on bit labeling. They propose a bit labeling scheme for high-order PSK constellation that can efficiently reduce PAPR while achieving BER performance comparable to that of Gray labeling