Static hybrid amplify and forward (AF) and decode and forward (DF) relaying for cooperative systems

In this paper, we propose a static hybrid amplify and forward (AF) and decode and forward (DF) relaying protocol for cooperative systems. In such a scheme, relays close to the source amplify the received signal whereas the remaining relays transmit only if they decode correctly. We consider two subclasses of the proposed hybrid AF–DF relaying protocol. In the first one, all AF relays and DF relays that have decoded correctly transmit using orthogonal channels. The second protocol, called opportunistic hybrid AF–DF relaying, consists in activating only the relay offering the highest instantaneous signal to noise ratio (SNR) among AF relays and the relays that have decoded correctly. The outage SNR probability, and the exact and asymptotic bit error probability (BEP) values of both all-participating and opportunistic hybrid AF–DF relaying protocols are derived and compared to conventional AF and DF relaying. The proposed protocol offers better performance than AF relaying and similar performance to DF relaying with a lower computational complexity. Simulation results are also provided to verify the tightness of the derived results.     

Low-complexity soft-output signal detector based on AI-SSOR preconditioned conjugate gradient method over massive MIMO correlated channel

Massive multiple-input multiple-output (MIMO) techniques with a large number of antenna elements at base station (BS) have been proved as an alternative to provide potential opportunity to increase the spectrum and energy efficiency. However, in the system, there generally exists a spatial correlation effect due to insufficient antenna elements spacing and/or the lack of rich scattering at BS. The minimum mean square error (MMSE) method performs signal detection at the expense of large-scale matrix inversion operation. Thus, the conjugate gradient (CG) method has received a lot of attentions to realize the MMSE detection efficiently. Unfortunately, this efficiency can be compromised due to the ill-conditioned equalization matrix of MMSE method over the correlated channel environments. Moreover, the hard output signal detection exhibits a sharply degradation in performance for higher-order quadrature amplitude modulation (QAM). Therefore, the modern communication systems use the soft-output information, i.e., log-likelihood ratio (LLR) along with the forward error-correcting code (FEC) to achieve satisfactory performance. The LLR computation along with a higher-order QAM remains challenging due to the exhaustive search of symbol in the modulation constellation. In this paper, a low-complexity soft-output signal detector based on approximate inverse symmetric successive over-relaxation preconditioned conjugate gradient (AI-SSOR-CG-SOD) method is proposed to realize MMSE method detection for uplink multiuser massive MIMO correlated channel. In the proposed method, a new preconditioner, an AI-SSOR, which is based on the Neumann series approximation of the inverse of the conventional SSOR preconditioner is firstly developed to handle ill-conditioned matrix, and then incorporated with CG method to improve the convergence rate and performance. According to the characteristic of the Gray-coding that adjacent symbols in the constellation set have only one different bit, the constellation set is divided multiple times based on the bits of the inphase and the quadrature components of the symbol, which reduces the complexity of the LLR computation of the transmitted bits by avoiding the exhaustive search process. Simulation results show that the AI-SSOR preconditioner is robust against spatial correlation effect, and the proposed detector converges at 3 iterations. Simulation results also show that the proposed detector achieves a better trade-off between the complexity and the performance compared to other existing detectors.     

A Generalized Spatial Modulation System Using Massive MIMO Space Time Coding Antenna Grouping

Massive multiple input multiple output (MIMO), also known as a very large-scale MIMO, is an emerging technology in wireless communications that increases capacity compared to MIMO systems. The massive MIMO communication technique is currently forming a major part of ongoing research. The main issue for massive MIMO improvements depends on the number of transmitting antennas to increase the data rate and minimize bit error rate (BER). To enhance the data rate and BER, new coding and modulation techniques are required. In this paper, a generalized spatial modulation (GSM) with antenna grouping space time coding technique (STC) is proposed. The proposed GSM-STC technique is based on space time coding of two successive GSM-modulated data symbols on two subgroups of antennas to improve data rate and to minimize BER. Moreover, the proposed GSM-STC system can offer spatial diversity gains and can also increase the reliability of the wireless channel by providing replicas of the received signal. The simulation results show that GSM-STC achieves better performance compared to conventional GSM techniques in terms of data rate and BER, leading to good potential for massive MIMO by using subgroups of antennas.     

ECM and SAGE based joint estimation of timing and frequency offset for DMIMO–OFDM system

Distributed multiple-input multiple-output (DMIMO) technology is a key enabler of coverage extension and enhancement of link reliability in wireless networks through distributed spatial diversity. DMIMO employs classic relay channels in between the source and the destination to opportunistically form a virtual antenna array (VAA) for emulating cooperative diversity. Use of multiple antennas at the relays further increases capacity and reliability of the relay–destination channel through multiplexing and diversity of MIMO antennas respectively. In such network, the signal received at the destination is characterized by multiple timing offsets (MTO) due to different propagation delay and multiple carrier frequency offsets (MCFO) due to independent oscillators of the relays. Hence, synchronization becomes a crucial issue in DMIMO in order to realize the distributed coherence. In this paper, we address joint estimation of MCFO and MTO in DMIMO orthogonal frequency division multiplexing (OFDM) with MIMO configuration at the relays for estimate-and-forward (EF) relaying protocol. Two iterative algorithms, based on expectation conditional maximization (ECM) and space alternating generalized expectation–maximization (SAGE) are proposed for joint estimation in presence of inter carrier interference (ICI). The robustness of both the estimators to ICI is evaluated by mathematical analysis and supported by extensive simulations. The performance of the proposed estimators is assessed in terms of mean square error (MSE) and bit error rate (BER). The theoretical Cramer–Rao lower bound (CRLB) of estimator error variance is also derived.     

Distributed spatial modulation with dynamic frequency allocation

This paper proposes a distributed implementation of spatial modulation (SM) using cognitive radios. In distributed spatial modulation (DSM), multiple relays form a virtual antenna array and assist a source to transmit its information to a destination. The source broadcasts its signal, which is independently demodulated by all the relays. Each of the relays then divides the received data in two parts: the first part is used to decide which one of the relays will be active, and the other part decides what data it will transmit to the destination. An analytical expression for symbol error probability is derived for DSM in independent and identically distributed (i.i.d.) Rayleigh fading channels. The analytical results are later compared with Monte Carlo simulations. Further, an instantaneous symbol error rate (SER) based selection combining is proposed to incorporate the direct link between the source and destination with existing DSM. Next, DSM implementation is extended to a cognitive network scenario where the source, relays, and destination are all cognitive radios. A dynamic frequency allocation scheme is proposed to improve the performance of DSM in this scenario. The frequency allocation is modeled through a bipartite graph with end-to-end SER as a weight function. The optimal frequency allocation problem is formulated as minimum weight perfect matching problem and is solved using the Hungarian method. Finally, numerical results are provided to illustrate the efficacy of the proposed scheme.     

Relay selection and nonlinear energy harvesting in full-duplex multi-relay cooperative network

Energy harvesting (EH) is a promising technique to extend the lifetime energy-constrained devices in wireless networks. This paper analyses the significance of relay selection and non-linear EH in evaluating the performance of Full-duplex (FD) decode-and-forward (DF) multi-relay cooperative network. The relay selection is considered under three scenarios based on channel state information (CSI) availability. We compare the EH performance of a hybrid power-time-splitting (PTS)-based non-linear energy harvester with time-spitting (TS) and power-splitting (PS) EH at the relay node. We derive the expression of outage probability (OP) of FD DF multi-relay cooperative network over independent and identically distributed Rayleigh fading channels. Numerical results show that the outage performance of the system is significantly enhanced by deploying an ideal relay selection scheme. This paper also gives insights about the combined effect of saturation threshold of non-linear EH and residual self-interference (RSI) on the system performance. Unlike linear EH systems, the non-linear EH causes the outage floor even when the RSI is significantly small. The response of the system is also analysed for the impact of TS and PS ratios. Furthermore, we also investigate the system’s performance in terms of other system parameters like the number of relays and data transfer rate. Monte Carlo simulations are used to verify the analytical expressions.     

Improved Chernoff Bound of Gaussian Q-function with ABC algorithm and its QAM applications to DB SC and MRC systems over Beaulieu–Xie channels

In this study, we propose an improved upper bound for the Gaussian Q function by using artificial bee colony algorithm. Then, we investigate the performance of the dual-branch (DB) selection combining (SC) and maximal ratio combining (MRC) systems over the Beaulieu–Xie fading channels. The probability density functions of the instantaneous signal to noise ratio for the considered systems are obtained. Employing the proposed upper bound, we derive closed-form expressions of the error probability for the quadrature amplitude modulation (QAM) techniques such as rectangular QAM (RQAM), cross QAM (XQAM), and hexagonal QAM (HQAM). Furthermore, the asymptotic error probability expressions for the DB SC system are also obtained to simplify the analyses. The effects of some key parameters in the systems are shown in the results. Comparisons of the different modulation types and the different upper bound approaches for the Gaussian Q function are presented. Finally, it has been shown that the upper bound approximation presented in this study can be widely used for many communication applications.     

Performance analysis of multiuser diversity with antenna selection in MIMO MRC systems

This paper presents a performance analysis of a user scheduling scheme for multiuser multiple-input–multiple-output (MIMO) systems with maximum ratio combining (MRC) and transmit antenna selection exploiting the multiuser and antenna diversities over independent and non-identically distributed (i.ni.d.) Rayleigh fading channels (heterogeneous case). A normalized SNR-based scheduling scheme that can guarantee user fairness is considered and new closed-form expressions for the outage probability, average channel capacity, and average bit error rate are derived. The system performance in the homogenous case (independent and identically distributed (i.i.d.) users) can be simply obtained from the derived expressions as a special case of the heterogenous case. Using the derived analytical expressions the system performances for both heterogenous and homogeneous cases are evaluated and compared. Finally, the impact of receiver antenna correlation on the system performance is evaluated.     

Deep-BiGRU based channel estimation scheme for MIMO–FBMC systems

Deep Learning (DL)–based wireless communication systems have the potential to improve the conventional functions and current architecture of communication systems. In this paper, we propose a novel DL-based channel estimation scheme for multiple-input multiple-output filter bank multicarrier with offset quadrature amplitude modulation (MIMO-FBMC/OQAM) systems called deep bidirectional gated-recurrent unit (BiGRU) scheme. This scheme can easily be applied to a single-input single-output (SISO) system. The proposed scheme is divided into two stages: offline and online. The network is first trained in the offline stage. The prediction of channel information and estimation of the channel matrix using the trained network is then performed in the online stage. The simulation results in terms of the normalized mean square error (NMSE) and bit error rate (BER) demonstrate that, under different time-varying channel models, the proposed DL scheme significantly improves the channel estimation performance of FBMC for single and multiple antennas compared to conventional interference approximation method (IAM) channel estimation methods.     

Gamma-Gamma湍流信道中大气光通信系统误码特性分析

大气信道中的大气湍流是影响无线激光通信系统性能的主要因素之一, 其引起的强度闪烁效应会对接收信号的提取和还原造成很大干扰。基于Gamma-Gamma概率分布的大气湍流信道统计模型, 研究了利用副载波相移键控(PSK)强度调制技术的大气光通信系统的误码特性; 推导了副载波二进制相移键控(BPSK)及开关键控(OOK)两种调制模式下的系统误码率表达式; 对在一定条件下的大气光通信系统, 比较了副载波BPSK和OOK两种调制模式的误码特性; 分析了链路特征、接收口径尺寸、通信波长和天顶角等因素对系统误码率的影响。结果表明, 增大接收孔径和通信波长都能有效地降低系统误码率, 而天顶角的增大则会使系统误码率增加, 副载波BPSK调制模式的误码特性要优于OOK调制模式的误码特性。     

基于DPIM调制的MIMO空间光通信系统

为了抑制空间光通信中大气湍流效应和降低误包率,提出了一种引入分布式多出多入技术,基于数字脉冲间隔调制的多出多入空间光通信系统.在弱湍流信道模型和APD探测器下建立了多出多入系统链路模型,推导了最大似然检测下的最佳阈值和误包率.计算结果表明：发射分集通过多路径传输平滑接收信号光强起伏|接收分集增加孔径平滑效应,减弱接收光强起伏|在发射平均功率、接收孔径总面积和背景噪音相同的条件下,数字脉冲间隔调制的不同多出多入系统存在几乎相同的最佳雪崩光电二极管增益|比较多出多入通信系统下三种调制方式,数字脉冲间隔调制的误包率较少劣于PPM调制而大大优于OOK调制.     

Ground-to-Satellite Optical Communication Link Performance with Spatial Diversity in Weak Atmospheric Turbulence

Abstract

In this article, performance improvement of a free-space optical communication link with spatial diversity is evaluated for coherent (sub-carrier BPSK and sub-carrier QPSK) and non-coherent (OOK and Q-PPM) modulation schemes in an atmospheric turbulence fading channel. Based on Kolmogorov's theory, the link performance characterized by the signal-to-noise ratio or bit error rate is evaluated for both modulation schemes. It is observed that there is performance improvement with the increase in the order of transmit diversity for all the modulation schemes. Sub-carrier BPSK modulation outperforms the other modulation schemes in terms of the minimum signal-to-noise ratio requirement for a given bit error rate. Also, the effect of correlation among different transmitting antenna beams on the link performance is analyzed.     

Simple, accurate formula for the average bit error probability of multiple-input multiple-output free-space optical links over negative exponential turbulence channels

In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.     

Automatic modulation classification using bimodal parallel multichannel deep learning framework for spatial multiplexing MIMO system

In recent years, automatic modulation classification (AMC) has proved its importance for the military as well as civil applications and deep learning (DL) based AMC has attracted wide attention. But existing methods neglect to consider the advantages of both multimodality and complementarities simultaneously in a single DL framework for multiple-input multiple-output (MIMO) system. To mitigate this, bimodal multichannel configurable DL-based AMC has been presented for the MIMO system under perfect channel state information with zero forcing equalizer. The proposed DL framework consists of two parallel structures of multichannel convolutional layers in which one multichannel structure is fed with in-phase/quadrature (I/Q) as first modal information while another multichannel structure accepts amplitude/phase as second modal information. Features extracted from this parallel structure then pass through long short-term memory (LSTM) layers for further extracting temporal information effectively. Finally, classification is accomplished through fully connected layers. Simulation results manifest the robustness of the proposed framework that achieves an average accuracy of about 0.6% to 12% higher compared to the state-of-the-art DL models. Simulations also illustrate the impact of antenna diversities with spatial multiplexing on the classification.     

基于空间光调制器的MIMO大气传输特性研究

大气湍流对无线光通信系统的影响不可忽视,为了更准确地反映实验室模拟多输入、多输出(MIMO)大气湍流信道的实际特征,提出了一种利用相位屏来模拟MIMO大气湍流信道的方法,并针对基于液晶空间光调制器（LC-SLM）的液晶调制法展开研究,通过实验验证该方法的可行性。实验结果表明:通过相位屏模拟MIMO大气湍流信道的激光光斑发生不同程度的畸变,湍流环境下两路激光发射系统比单路发射激光系统功率稳定性好,在前向纠错误差极限（3.8×10?3）下,单个发射单个接收系统的链路代价为10.5 dB,2个发射2个接收的MIMO系统的链路代价为9.3 dB。该项研究对于实验室模拟MIMO大气湍流信道实验方法提供一种新思路。     

Effectiveness of Space-Division Multiple-Access in MIMO Communication Systems with Parallel Data Transmission

We consider multiple-input multiple-output (MIMO) cellular communication systems with antenna arrays at both link ends and data transmission via parallel eigenchannels matched with a random spatial channel. We analyze the effectiveness of the space-division multiple-access (SDMA) method, which does not require estimation of signal-arrival directions and is based on orthogonalization of the parallel channels of all users. We obtained approximate analytical expressions for the mean ratio of the signal power to the noise power and the MIMO system capacity, which are derived for the case of Rayleigh fading of signals. Although the obtained formulas are much simpler than the exact ones, they ensure high accuracy for an arbitrary number of transmitting and receiving antennas and an arbitrary power of transmitter. Our results demonstrate the high effectiveness of the proposed SDMA method.     

BER analysis of BPSK-SIM-based SISO and MIMO FSO systems in strong turbulence with pointing errors

Free space optics (FSO) is one of the sprouting technologies in optical communication systems domain. It can be employed as an alternative for the conventional radio frequency (RF) links to work out the current limitations in communication systems. But, the major drawback in FSO communication is the effect of random environment conditions on its performance. In this paper, we analyze the bit error rate (BER) and outage performance of single-input single-output (SISO) and multiple-input multiple-output (MIMO) FSO systems in strong atmospheric turbulence using binary phase shift keying subcarrier intensity modulation (BPSK-SIM) signaling technique. The closed-form expressions are derived and the results are realized in terms of 2D and 3D plots.     

Influence of the nonlinear propagation effect on the optical signal-to-noise ratio of 400G optical fiber communication systems

The influence of the nonlinear propagation effect on three 400 Gb/s/ch(400G)optical fiber communication systems with typical modulation formats,dual-carrier 16-quadrature amplitude modulation(16QAM),single-carrier 16QAM(single-16QAM),and four-carrier quadrature phase-shift keying,are investigated.The received optical signal-to-noise ratio(OSNR),affected by the nonlinear interference noise together with the amplified spontaneous emission noise,are compared with three 400G systems and a standard 100 Gb/s/ch system by numerical simulations.Both single channel and multichannel cases are considered.Single-16QAM is found to have the best OSNR among those modulation formats.     

Downlink channel estimation in FDD cell-free massive MIMO

In frequency-division duplexing (FDD) cell-free massive multiple-input multiple-output (MIMO) systems, an excessive channel estimation overhead is a critical issue that limits the system performance. In this paper, by exploiting the sparse channel characteristics of such a cell-free system, we apply compressive sensing to estimate the channel state information and solve the excessive pilot overhead problem. The proposed algorithm estimates several channel coefficients with significant gains in the power domain and ignores the approximately zero coefficients. Compared to minimum mean square error (MMSE) estimation with orthogonal pilots, the proposed method significantly reduces the pilot overhead in an FDD cell-free massive MIMO system. The access points (APs) that contribute low gains feature reduced energy consumption because the power coefficients corresponding to zero gains in the sparse channel are assigned zeros in the power control process. Therefore, to improve the energy efficiency, the ignored channel coefficients reduce the power overhead.