任意分集方式多输入多输出无线通信系统的统计信道建模

针对极化分集多输入多输出系统的传统统计模型存 在着对不同极化方向上的功率变化设置不合理的问题, 提出一种功率矩阵对其进行纠正; 对采用不同分集方式的多输入多输出系统信道建模的原理进行分析, 提出对功率矩阵和相关矩阵进行复合计算的方法, 建立了一种适用于任意分集方式多输入多输出系统的统计信道模型, 该模型能够确切反映出同时受到距离分集和极化分集影响的多输入多输出系统之统计特征.     

多天线信道空间衰落相关性近似算法及其复杂性研究

信道空间衰落相关性(SFC)主要取决于波达信号的功率方位谱(PAS)和多天线阵列收发模式.深入研究了移动通信系统中多天线阵列SFC近似计算法及其复杂性.首先导出在典型PAS为均匀分布、高斯分布以及拉普拉斯分布下的SFC函数的闭合表达式.再研究在波达信号PAS小角度扩展时的近似计算法,建立多输入多输出(MIMO)多天线接收信道模型,深入分析所选择的天线阵列和电波传播参数对MIMO系统信道容量的影响.通过理论计算和仿真实验得出近似计算法在特定条件下具有很好的拟合度,定量分析了近似计算法在对MIMO多天线系统分析时的适用性和计算效率.该算法能极大地减低理论计算复杂性,提高分析和仿真MIMO多天线系统的效率.     

基于空间分集的高空平台光链路性能研究

针对高空平台不稳定性以及大气湍流对平台光通信性能的影响,提出利用空间分集技术改善高空平台光通信链路性能。在系统采用开关键控(OOK)调制条件下,利用矩母函数特性分别得到采用协作分集技术和多输入多输出(MIMO)技术的高空平台光链路误码率表达式,并求解协作通信系统中继平台的最优位置。仿真结果表明:协作分集技术与光MIMO技术对高空平台光链路性能的改善效果受到跟瞄误差的限制。采用发射选择分集的光MIMO技术对光链路的误码率性能最好。与采用重复码的MIMO方法相比,协作分集技术更适用于跟瞄误差大的通信系统。中继平台的最优位置与中继策略以及跟瞄误差无关。在中继平台最优位置附近,采用协作分集的光链路性能优于采用重复码MIMO光通信链路。     

浅水时变多途信道特性分析与模型实验研究

时变多途水声信道是影响水声通信性能的一个重要因素,深入了解水声信道挣性并对水声信道进行建模具有重要的研究意义。本文在分析传统时变信道模型基础上,从时域角度出发,提出采用AR (ρ)模型对已有的浅水时变多途信道模型中的小尺度衰落分量进行修正。然后基于莲花湖实测信道数据,分析了时变信道各个路径的幅度、时延、时间相干系数、系统传递函数等特性,并对修正模型进行了验证正。从仿真结果来看,修正模型与试验结果拟合的很好。本文从多个方面对水声信道特性进行了分析,有助于对水声信道的深入了解,同时为水声通信系统性能评估提供了一种仿真信道模型。     

基于强度叠加编码的空间光多输入多输出通信

针对空时编码技术在空间激光通信应用中受到的限制,提出了一种基于强度叠加编码的空间光多输入多输出(MIMO)通信算法,设计了算法中使用的码元--光强码的编码和解码规则,分析了不同天线阵列组合下的系统信道容量,给出了最佳判决门限选择方法,并在此基础上计算了不同系统组成下的误码率.仿真计算表明,与单发单收系统相比,强度叠加编...     

大气激光通信中多光束传输性能分析和信道建模

多光束传输技术是克服大气激光通信中大气湍流效应的有效途径之一。首先从理论上分析了大气湍流对多光束大气激光通信系统性能的影响和多光束大气传输的光强起伏特性,然后利用统计分析的方法,建立了一个以传输距离z、光束数目n、发射孔径之间的距离St、接收孔径Dr等为参量的多光束大气传输信道模型。最后,结合相关文献提供的实验结果对该信道模型进行了实验验证和误码性能分析。结果表明,当S1≥√λz或Dr远大于大气湍流相干长度ρo时,随着n的增大,接收光强将趋于对数正态分布．降低了大气激光通信系统的误码率,从而验证了多光束传输对于克服大气湍流影响的有效性。     

采用去网格相关向量机的水下多径稀疏信道估计

在采用训练序列的水下稀疏信道估计问题中,由于采样过程的存在产生了测量矩阵的网格,所以当多径时延不恰好位于网格上时,传统的有网格方法就无法准确估计出该多径的位置,在网格间距较大时这个问题更加严重。针对这个问题,本文构建了一个去网格的稀疏信道估计模型,这个估计模型的测量矩阵包含了对网格外偏差进行调整的参数,在此基础上进一步采用相关向量机的方法对这个调整参数进行估计,得到网格外的偏差值。针对两种不同的水下稀疏多径信道模型进行的仿真试验证明,此方法相比其它有网格稀疏信道估计算法,在估计误差和误码率上有提升,在网格间距较大时,优势更加明显。     

无背景噪声时光多输入多输出系统的信道容量

信道容量是通信系统能够达到的最大传输速率,是衡量通信系统通信能力的重要指标之一。在建立了光多输入多输出(MIMO)的信道模型之后,结合脉冲位置调制(PPM)分析了光MIMO系统的平均容量和中断容量;在无背景辐射的条件下,分别推导出了有无衰落时光MIMO平均容量封闭形式的近似表达式。在相同发射功率和传输带宽条件下,得到了光MIMO技术能成倍提高现有系统信道容量的结论。通过Monte Carlo仿真实验进一步证明了理论的正确性。     

多波束分集深海远程正交频分复用水声通信

针对深海远程信道传播衰减大、多途扩展严重的问题,提出一种单输入多输出（SIMO）模型下的水声正交频分复用（OFDM）多波束空间分集均衡方法。建立了深海远程信道下SIMO-OFDM接收信号模型,对宽带波束形成处理后的多个到达角度的波束输出进行独立的多普勒补偿和稀疏信道估计,最后基于最大比合并实现多波束均衡。相对于远程通信中常用的单波束处理方法,所提方法可获得额外的不同到达角度的多径分集增益;且基于阵列波束形成处理可明显提升各个波束输出信噪比,避免了单阵元信噪比过低导致的信道估计误差增大的问题。所提方法的计算复杂度大于单波束均衡,但低于多阵元最大比合并均衡。基于BELLHOP的数值仿真和中国南海实验结果表明,所提方法的误码率性能明显优于单波束均衡和最大比合并均衡,且在100 km的距离上实现了通信速率199 bps的无误码通信。     

基于多径信道模型研究时间反演腔的反演特性

基于时间反演腔的电磁波时间反演技术在许多方面有着潜在的应用,如脉冲压缩、功率合成、微扰探测、波束成形等.其中,时间反演腔通常采用具有多径传输特征的微波混沌腔.利用衍射理论,虽然可以证明这类腔体在时间反演过程中具有时空聚焦特性并可用于脉冲压缩,但是它不能用于分析腔体的反演性能.为了得到一个合适的分析方法并可用于指导时间反演腔设计,本文基于信道理论,分析电磁波传播的散射、扩散和衰减特性,构建了时间反演腔的多径信道模型,并详细研究了路径之间的串扰特征,给出反演重构信号的时间旁瓣产生机理、时移特征以及对主瓣的干扰情况.另外,根据随机平面波假设,还分析了空间焦斑的分布特征.实际焦斑大小不但受限于衍射极限而且还与初始焦斑大小有关.这些理论分析结果与实验和数值仿真结果基本一致.     

Broad Coverage Precoding for 3D Massive MIMO with Huge Uniform Planar Arrays

In this paper, we propose a novel broad coverage precoder design for three-dimensional (3D) massive multi-input multi-output (MIMO) equipped with huge uniform planar arrays (UPAs). The desired two-dimensional (2D) angle power spectrum is assumed to be separable. We use the per-antenna constant power constraint and the semi-unitary constraint which are widely used in the literature. For normal broad coverage precoder design, the dimension of the optimization space is the product of the number of antennas at the base station (BS) and the number of transmit streams. With the proposed method, the design of the high-dimensional precoding matrices is reduced to that of a set of low-dimensional orthonormal vectors, and of a pair of low-dimensional vectors. The dimensions of the vectors in the set and the pair are the number of antennas per column and per row of the UPA, respectively. We then use optimization methods to generate the set of orthonormal vectors and the pair of vectors, respectively. Finally, simulation results show that the proposed broad coverage precoding matrices achieve nearly the same performance as the normal broad coverage precoder with much lower computational complexity.     

Cooperative spectrum sharing MIMO systems with successive decoding

A spectrum sharing system with primary and secondary nodes, each equipped with an arbitrary number of antennas, is investigated. Particularly, the outage performance of an underlay cognitive system is analytically studied, in the case when the end-to-end ($e2e$) communication is established via an intermediate relay node. To better enhance the $e2e$ communication, successive interference cancellation (SIC) is adopted, which compensates for both the transmission power constraint and the presence of interference from primary nodes. Both the relay and secondary receiver perform unordered SIC to successively decode the multiple streams, whereas the decode-and-forward relaying protocol is used for the $e2e$ communication. New closed-form expressions for the $e2e$ outage performance of each transmitted stream are derived in terms of finite sum series of the Tricomi confluent hypergeometric function. In addition, simplified yet tight approximations for the asymptotic outage performance are obtained. Useful engineering insights are manifested, such as the diversity order of the considered system and the impact of interference from the primary nodes in conjunction with the constrained transmission power of the secondary nodes.     

多极化MIMO信道特性与天线设计*

多极化MIMO技术在高频谱效率和紧凑型MIMO通信系统中具有较大的应用潜力,其信道特性与天线辐射特性和环境散射特性以及它们之间的相互作用密切相关,目前紧凑型、低耦合的多极化MIMO天线设计仍存在很大挑战。本文简要介绍和总结了多极化MIMO信道建模理论、多极化天线实现方式和信道特性测量实验等,并指出存在的一些问题和未来的研究方向。     

Outage capacity analysis of the massive MIMO diversity channel

We consider the massive Multiple Input Multiple Output (MIMO) channel affected by independent and identically distributed Rayleigh fading, with linear processing at both transmitter and receiver sides to pursue full diversity, and analyze its outage capacity for large number of antennas. We first discuss the classical Single Input Multiple Output (SIMO) diversity channel that encompasses Maximal Ratio Combining (MRC) or Selection Combining (SC). For MRC, a numerical computation and a Gaussian Approximation (GA) are considered, whereas for SC an exact evaluation is presented. The analysis is then straightforwardly extended to the Multiple Input Single Output (MISO) diversity channel that encompasses Maximal Ratio Transmission (MRT) or transmit antenna selection. The general full diversity MIMO channel is finally considered, with optimal linear processing or simple antenna selection at both transmitter and receiver. If the number of antennas is sufficiently large on at least one side, the outage capacity of each considered diversity channel approaches that of a reference Additive White Gaussian Noise (AWGN) channel with properly defined Signal-to-Noise Ratio (SNR), which provides a performance benchmark. This conclusion is valid for large but realistic number of antennas compatible with the assumption of independent fading.     

Secrecy energy efficiency optimization for multiuser massive MIMO wiretap systems with transmit antenna selection

Massive multiple-input-multiple-output (Massive MIMO) significantly improves the capacity of wireless communication systems. However, large-scale antennas bring high hardware costs, and security is a vital issue in Massive MIMO networks. To deal with the above problems, antenna selection (AS) and artificial noise (AN) are introduced to reduce energy consumption and improve system security performance, respectively. In this paper, we optimize secrecy energy efficiency (SEE) in a downlink multi-user multi-antenna scenario, where a multi-antenna eavesdropper attempts to eavesdrop the information from the base station (BS) to the multi-antenna legitimate receivers. An optimization problem is formulated to maximize the SEE by jointly optimizing the transmit beamforming vectors, the artificial noise vector and the antenna selection matrix at the BS. The formulated problem is a nonconvex mixed integer fractional programming problem. To solve the problem, a successive convex approximation (SCA)-based joint antenna selection and artificial noise (JASAN) algorithm is proposed. After a series of relaxation and equivalent transformations, the nonconvex problem is approximated to a convex problem, and the solution is obtained after several iterations. Simulation results show that the proposed algorithm has good convergence behavior, and the joint optimization of antenna selection and artificial noise can effectively improve the SEE while ensuring the achievable secrecy rate.     

Modified leakage-based transmit filter designs for multi-user MIMO systems

This paper proposes two modified definitions of signal-to-leakage-plus-noise ratio (mSLNR) as criteria for linear transmit filter design in Multi-User MIMO systems. The proposed criteria incorporate receiver structures and priority weight matrices into the precoder design, which can effectively exploit unused receive signal spaces, in the case that available eigenmodes are not fully transmitted, and can potentially prioritise users’ data streams. Iterative SLNR (iSLNR) precoding algorithms based on the proposed mSLNR definitions are also presented. Further, the variations of the iSLNR algorithms are thoroughly studied. In particular, the impact of the mSLNR definitions, choices of receive filters and iteration types on the convergence property and sum-rate performance is discussed. Moreover, the effect of weight matrices on users’ prioritisation is elaborated. For extreme weight values, the proposed algorithms are shown to converge to either eigenbeamforming or null-space decomposition techniques. Further, a robust design of the proposed schemes for the case of imperfect channel state information (CSI) is presented. It is shown that adequate knowledge of effective receive subspaces can be attained by simply assuming matched filters (MF) in the iterative precoding process, while further improvement can be obtained by an actual implementation of interference-mitigation-capable receivers.     

Decision-directed Kalman particle filter with application to the MIMO phase noise channel

Demodulation of data transmitted over time-varying channels with a free running hidden Markov state, like the phase noise channel or the fading channel, requires that the receiver tracks the hidden channel state. The tracking technique adopted in the paper is based on non-data-aided sequential importance sampling, also known as particle filtering.The paper proposes a new particle filtering framework for data communication receivers based on an importance distribution such that each individual particle becomes a decision-directed Kalman filter relying upon its local symbol-by-symbol hard decisions. In this framework, different particles are left free to take different sequences of decisions. This leaves to the receiver the possibility of exploring different sequences of transmitted modulation symbols. The weight of the particle will be high for those particles that took in the past the correct sequence of decisions, while will be low for those particles that took wrong decisions. In the resampling procedure, particles with high weight will survive, while particles with low weight will be terminated, leaving space to the birth of new particles resampled from the surviving ones.The crucial point in importance sampling is the choice of the importance distribution and the main novelty of the paper is the proposal of an importance distribution such that the particles of the particle filter become decision-directed Kalman filters. One important benefit brought by our proposed method is that, being non-data-aided, it does not need pilot symbols, thus allowing to preserve the transmission rate. A significant application example, presented and developed in the paper, is constituted by MIMO systems affected by phase noise, where the channel state vector consists of many parameters.     

Lower bound on the capacity of distributed MIMO systems with spatially correlated Rician/Lognormal fading

This paper presents an analytic lower bound of ergodic capacity for distributed MIMO (D-MIMO) systems that experience not only Rician fading but also shadowing effects of Lognormal distributed. In particularly, we consider that the Rician fading channel is spatially correlated at both transmitter and receiver. In the communication environment corresponding to this setting, the angle spread at the transmitter and the angle spread at the receiver are both insufficient, and the non-fading components co-exists with the fading components. Such communication environment is very common. In the process of deriving the analytic lower bound, in order to avoid Hayakawa polynomials that cannot be analytically expressed, non-central quadratic forms are transformed to non-central Wishart matrices by use of inequality. The validity of the presented lower bound is verified by computer simulations. The simulation results show the influence of the number of radio ports at the transmitter, the number of antennas at the transmitter or receiver, correlation level (angle spreads) and Rician K-factor on the capacity of systems. In all cases, the presented bound remains tight across the entire signal-to-noise ratio (SNR) regime.     

Data detection based on matrix decomposition for massive MIMO systems in realistic channel scenarios

Massive multiple-input multiple-output (MIMO) is a key technology for modern wireless communication systems. In massive MIMO receivers, data detection is a computationally expensive task. In this paper, we explore the performance and the computational complexity of matrix decomposition based detectors in realistic channel scenarios for different massive MIMO configurations. In addition, data detectors based on decomposition algorithms are compared to the approximate-inversion detection (AID) methods. It is shown that the alternating-direction-method-of-multipliers-based-Infinity-Norm (ADMIN) detection is promising in realistic channel environment and the performance is stable even when the ratio of the base-station (BS) antenna elements to the number of users is small. In addition, this paper studies the performance of several detectors in imperfect channel state information (CSI) and correlated channels. Our work provides valuable insights for massive MIMO systems and very large-scale integration (VLSI) designers to select the appropriate massive MIMO detector based on their specifications.