New generalized zero forcing beamforming for serving more users in energy-harvesting enabled networks

This paper considers a multi-user wireless communication network supported by a multiple-antenna base station (BS), where the users who are located sufficiently close to the BS employ wireless energy harvesting (EH) to replenish their energy needs. The objective of this work is to design an efficient beamforming to maximize the minimum throughput among all the information users (IUs), subject to EH constraints. In this regard, transmit time-switching approach is employed, where energy and information are transmitted over different fractions of a time-slot. To achieve efficient EH, a conjugate beamforming (matched filtering) is applied. To design efficient information beamforming for max–min throughput optimization, conventional zero-forcing (ZF) beamforming can be adopted, however, it will not suppress multi-user interference if the number of users is greater than the number of antennas at the BS. To this end, different from the existing works which employ regularized zero-forcing (RZF) beamforming, this work proposes a new generalized zero-forcing (GZF) beamforming, which promises better max–min throughput compared to that achieved by the RZF beamforming. A new path-following algorithm is developed to achieve max–min throughput optimization by GZF beamforming, which is based on a simple convex quadratic program over each iteration.     

多输入多输出广播信道下基于有限反馈的最大输出SINR线性天线合并算法

在基于有限反馈的多天线MIMO广播信道下,由信道量化误差带来的多用户干扰(MUI)会严重地降低系统性能。天线合并技术可以利用多接收天线提供的多维自由度有效地改善系统性能。该文针对最近被证明为最优的反馈资源分配策略,设计了一种线性天线合并算法,该算法在提高反馈精度和增强期望信号增益之间做出合理的折中,可使期望输出信噪干扰比(SINR)最大化。首先导出了线性合并器期望输出SINR的下界闭合表达式,然后利用这个表达式得到使输出SINR最大化的线性合并器。仿真表明该线性合并算法与已有算法相比具有明显的性能提升。     

Impact of hardware impairments on large-scale MIMO systems over composite RG fading channels

In this paper, we analyze the impact of receiver hardware impairments on the achievable sum rate of multiple-input multiple-output (MIMO) systems, where the channel follows composite Rician-Gamma (RG) distribution and may be correlated at the transmitters. More specifically, we derive the analytical expressions on the lower bound for the achievable sum rate of regular and large-scale MIMO systems with zero-forcing (ZF) receivers. In order to obtain deeper insights, the asymptotic analysis for the achievable sum rate of regular MIMO systems at high signal-to-noise ratio (SNR) regime is explored. It explicitly reveals that there is a finite rate ceiling on the achievable sum rate for regular MIMO systems at high SNRs, which is irrespective of the transmit power. Additionally, for large antenna configuration, three representative cases are considered insightfully by deriving in closed-form expressions for the asymptotic achievable sum rate. It demonstrates that the finite rate ceiling vanishes for large-scale MIMO limits, which means that large-scale MIMO systems are robust to hardware impairments.     

一种改进的信号泄露噪声比多用户预编码算法

时分复用(TDD)系统通过信道互异性可以在发送端得到下行信道矩阵。由于上下行信道存在着处理延时,时变信道下,延时带来的信道误差会降低多用户MIMO预编码的系统性能。信道预测在某些情况下能够较好地改善信道误差,但预测误差又会给系统性能带来损失。该文针对预测误差带来的性能损失,提出了一种基于预测误差改进的预编码算法。改进算法根据预测误差的方差对预编码向量进行修正,能够进一步提高系统误码率性能。仿真结果表明,在高车速情况下,该算法比传统的预测预编码算法能带来更大的性能增益。     

SVD-based MIMO Precoding and Equalization Schemes for Realistic Channel Knowledge: Design Criteria and Performance Evaluation

Multiple-input multiple-output (MIMO) based communication systems with precoding, bit-loading and equalization procedures are considered in this paper. Applications of precoding schemes, which are based on Singular Value Decomposition (SVD) of the channel matrix H assume almost always ideal channel knowledge at the transmitter and/or receiver site. This paper investigates an SVD based MIMO approach considering non ideal radio channel estimation results. In any case the MIMO channel matrix H is decomposed into Eigenmodes. In case of an ideal radio channel knowledge the SVD based precoding procedure, which is applied at the transmitter site, is going to consider all possible Eigenmodes which results in a perfect separation of all signals at the receive antenna output and into a minimum bit-error-rate (BER). It will be shown in this paper that in case of non ideal channel knowledge and a limited accuracy in the channel matrix H estimation a reduced number of Eigenmodes in the precoding process will become an optimum and will lead into an increased BER performance.

Efficient ZF-WF strategy for sum-rate maximization of MU-MISO cognitive radio networks

This article presents an efficient quasi-optimal sum rate (SR) maximization technique based on zero-forcing water-filling (ZFWF) algorithm directly applied to cognitive radio networks (CRNs). We have defined the non-convexity nature of the optimization problem in the context of CRNs while we have offered all necessary conditions to solve the related SR maximization problem, which considers power limit at cognitive transmitter and interference levels at primary users (PUs) and secondary users (SUs). A general expression capable to determine the optimal number of users as a function of the main system parameters, namely the signal-to-interference-plus-noise ratio (SINR) and the number of BS antennas is proposed. Our numerical results for the CRN performance are analyzed in terms of both BER and sum-capacity for the proposed ZF-WF precoding technique, and compared to the classical minimum mean square error (MMSE), corroborating the effectiveness of the proposed technique operating in multi user multiple input single output (MU-MISO) CRNs.     

基于满意度准则采用混合波束成型预编码的调度方法

为了满足未来无线宽带网络中多种服务质量(QoS)要求业务并存的需求,该文提出一种多天线下行系统中结合混合波束成型预编码技术基于满意度的调度方法。该调度方法联合考虑用户的QoS要求及其信道质量,灵活地使用随机波束成型和迫零波束成型预编码技术,并通过惩罚机制避免特定用户占用超出其需求的带宽,更有效地为用户分配令其满意的资源,使各种QoS要求的用户获得满意的服务。仿真结果证明,与现有的方法相比,该文提出的方法在保证用户服务质量的同时,能更好地利用系统资源。