基于多任务贝叶斯压缩感知的稀疏可重构天线阵的优化设计

建立方向图可重构天线的联合稀疏模型,基于多任务贝叶斯压缩感知理论提出一种稀疏可重构天线阵的优化设计方法.该方法在实现方向图精确重构的同时可以大幅减少天线数量,节省平台空间,降低设计成本.首先基于多任务贝叶斯压缩感知理论建立多目标方向图的稀疏优化模型,根据权值向量的先验概率分布,利用快速相关向量机估计超参数的最大后验概率来得到多组阵元位置及其激励,实时改变激励以获得不同方向图的稀疏逼近.仿真验证了该方法能够以较少的阵元个数和较高的方向图拟合精度快速实现方向图重构.     

宽带极化与方向图可重构天线研究

随着无线通信系统的快速发展, 宽带可重构天线将在未来发挥巨大作用.文中综述了四种宽带极化与方向图可重构天线, 它们都具有提高通信系统容量, 消除极化失配, 扩大辐射范围等特点.首先介绍了一种宽带的多线极化可重构天线.此款天线基于L型探针馈电的贴片天线, 实现了0°, 45°, 90°以及—45°极化的选择, 具有宽带、低剖面、高增益的特点.其次, 同样基于L型探针馈电的贴片天线, 通过引入一个输出相位可重构的功分馈电网络, 实现了宽带的圆极化可重构天线, 其同样具有宽带、低剖面、高增益的特点.除了极化可重构天线, 文中还介绍了两款方向图可重构天线, 可分别实现线极化以及圆极化的全向锥状波束以及定向辐射波束的方向图可重构.前者是基于宽带的单极子贴片天线跟L型探针馈电的贴片天线的有机结合.后者是基于环缝隙的贴片天线配合激励端口可重构的功分馈电网络的组合.此两款天线均具有结构紧凑、宽带、增益稳定的特点.     

基于可重构天线的时间反演安全通信方法

方向图可重构天线可以选择信号传播的空间信道,而时间反演技术可以回溯信号的传播路径(空间聚焦特点)。因此,文中将时间反演技术和方向图可重构天线技术结合可以产生多个具有不同截获位置的信号。将信息分别调制到这些信号上,可以改善信息传播的安全性。文中,利用MATLAB所构建的电磁仿真模型模拟室内空间环境,对这一方法进行了仿真研究。     

用于有限反馈MIMO系统中的统计多模发射天线选择算法

利用多输入多输出（MIMO）系统中的发射端天线选择算法,可以在降低复杂度的同时,有效地提高系统性能。考虑到基于线性接收机的空间复用系统,在通过已选择的发射天线上采用等功率分配等增益传输可以减少反馈信息量。因此,文章提出了空间相关衰落信道下可提升系统容量的统计多模发射天线选择方法。     

自适应MIMO系统中的支持选择功能的四单元天线

天线选择是自适应MIMO系统中实现可重构多天线的一种有效方法.提出了一种支持选择功能的四单元天线.通过在馈电网络中增加PIN二极管,该天线具备选择任意一组天线单元的功能,同时未被选择的天线单元终端加载匹配的集总负载以维持方向图的稳定.测量结果表明:在任意一种天线单元组合下,该天线都可以覆盖UMTS频段并保持较低的互耦;同时天线单元的方向图具有稳定性.     

现代移动通信中发射分集技术研究

基于发送端多天线系统的发射分集技术是现代移动通信系统中抗信道衰落影响的一项关键技术。全面介绍发射分集技术的概念和实现方式,利用频率、时间、空间、极化、角度、调制等各种无线资源均可实现有效的发射分集方案,并且详细分析了各类典型的发射分集技术的特点和性能,理论分析有助于推广多天线发射分集系统在实际通信系统中的进一步应用。     

基于特征空间的MIMO天线选择算法

多输入多输出(MIMO)系统中多天线阵元(MEA)的使用增加了硬件成本和信号处理负担,而天线选择技术能够在损失MIMO性能很小的条件下大幅度降低硬件需求.在最大化信道容量的准则下,提出了一种基于信道状态信息(CSI)特征空间的渐消算法及相应的启发式简化算法,并说明了简化算法等价于特征空间矩阵上的基于范数的选择(NBS)算法.仿真实验表明,在接收天线选择个数大于发送天线个数的条件下,两种算法达到的中断容量接近最优选择算法,且计算时间较小.     

频率方向图复合可重构寄生单极子天线阵列

提出了一种能应用于无线通讯系统的新型介质支撑开关寄生阵列天线.基于八木天线原理,天线可以实现频率及方向图的复合可重构.所引入的开关用来切换不同状态的工作频率并实现方向图的扫描.地支结构用来改善天线的阻抗匹配并展宽频带.测量结果表明:天线阵列可以在保证回波损耗小于-10 dB的情况下完全覆盖1710～1880 MHz、1...     

采用最大比率发射技术的天线选择系统性能研究

Alamouti方案(ALS)是仅有满速率的正交空时分组码(STBC),通过天线选择技术和优化发射功率提高其性能.若发射端知道全部的系统信道状态信息(CSI),文章提出在发射端混合最大比率发射(MRT)分集技术和发射天线选择(TAS)技术.基于信道增益系数大小的Frobenius范数最大的天线选择准则,系统选择瞬时输出信噪比(SNR)最大的天线子集{NT,2;mr}工作.采用MRT对Alamouti编码的双天线发射功率进行优化分配.仿真结果表明:采用混合MRT和TAS两技术后,基于ALS的多天线系统的比特误码率(BER)性能和信道容量均得到了明显改善.这一结论对有充足CSI的通信系统用于克服信道影响和提高系统传输速率具有借鉴意义.     

MIMO—OFDM系统下基于频谱利用率的自适应发射方案选择

本文提出并分析了一种MIMO-OFDM系统下,考虑相关空间信道的自适应发射方案选择算法.采用比特交织卷积编码,在以下三种发射模式间进行选择:空间复用、空间分集和复用/分集的混合模式.我们通过对MIMO-OFDM系统中采用迫零(ZF)接收机在高信噪比条件下的错误概率的简化分析,得出空间相关的多天线系统下的自适应选择算法,在给定的误码率条件下可获得使频谱利用率最大化的编码速率、调制模式和发射模式,并反馈到发射端,有效改善了系统的性能.     

Capacity achieving high rate space-time block codes

It is well known, that the Alamouti scheme is the only space-time code from orthogonal design achieving the capacity of multiple-input multiple-output (MIMO) wireless communication system with n/sub T/=2 transmit antennas and n/sub R/=1 receive antenna. In this work, we propose the n-times stacked Alamouti scheme for n/sub T/=2n transmit antennas and show that this scheme achieves the capacity in the case of n/sub R/=1 receive antenna. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas we achieve a high portion of the capacity with this scheme.     

协同信道空时优化MIMO无线传输系统

该文提出一种基于虚拟信道的空时优化多输入多输出(MIMO)无线传输系统。通过在发射端产生不同的空时虚拟信道,与实际空间无线信道级联,构成系统的整体传输信道即协同空分信道。系统可以根据接收端的反馈信息采用模拟退火算法来优化虚拟信道,改善误码率(BER)性能。利用虚拟信道方法,可以使一根MIMO发射天线在同一时间、同一频段传输多路叠加合并后的数据信号,从而可以使发射的不同数据信号的总路数超过发射天线的数量,突破了现有MIMO系统在同一时间、同一频段最多只能发射与发射天线数量相等的不同数据信号的传统方式,可以显著提高系统的频谱效率。仿真结果和基于ZC706和AD9361硬件平台的微波暗室实际测试结果充分验证了新MIMO系统的有效性。     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

关于MIMO系统的天线子集选择性能的研究

讨论了有关 MIMO 无线系统中的天线子集选择性能的问题。首先建立了 MIMO 信道模型,对信道模型进行了分析,接着对信道矩阵为非满秩的情况进行了研究,分别采用几种组合对发射、接收天线进行选择,得出不同组合对信道容量的影响。仿真结果表明,选择发射天线可以增加信道容量,选择接收天线虽然无助于增加信道容量,但在不会严重降低信道容量的前提下,可以降低系统的成本。     

混合STBC-VBLAST系统天线选择方案研究

研究表明MIMO系统中接收端SNR是一加权卡方随机变量,其权值为相应信道协方差逆阵的对角元素。为获得传输效率和传输可靠性间的折衷,利用协方差矩阵逆阵的对角元素,提出一种基于最小平均误码率（BER）的混合STBC-VBLAST发射天线选择方案。通过与传统无选择的VBLAST系统和有选择的VBLAST系统的BER和容量分别进行仿真比较,验证了所提混合STBC-VBLAST系统天线选择方案的优越性。     

Receive antenna selection for MIMO systems over correlated fading channels

In this letter, we propose a novel receive antenna selection algorithm based on cross entropy optimization to maximize the capacity over spatially correlated channels in multiple-input multiple-output (MIMO) wireless systems. The performance of the proposed algorithm is investigated and compared with the existing schemes. Simulation results show that our low complexity algorithm can achieve near-optimal results that converge to within 99% of the optimal results obtained by exhaustive search. In addition, the proposed algorithm achieves near-optimal results irrespective of the mutual relationship between the number of transmit and receive antennas, the statistical properties of the channel and the operating signal-to-noise ratio.     

Fast antenna subset selection in MIMO systems

Multiple antenna wireless communication systems have recently attracted significant attention due to their higher capacity and better immunity to fading as compared to systems that employ a single-sensor transceiver. Increasing the number of transmit and receive antennas enables to improve system performance at the price of higher hardware costs and computational burden. For systems with a large number of antennas, there is a strong motivation to develop techniques with reduced hardware and computational costs. An efficient approach to achieve this goal is the optimal antenna subset selection. In this paper, we propose a fast antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Our algorithm achieves almost the same outage capacity as the optimal selection technique while having lower computational complexity than the existing nearly optimal antenna selection methods. The optimality of the proposed technique is established in several important specific cases. A QR decomposition-based interpretation of our algorithm is provided that sheds a new light on the optimal antenna selection problem.     

Performance evaluation of spatially multiplexed MIMO systems with subset antenna transmission in interference limited environments

Transmit antenna selection in spatially multiplexed multiple-input multiple-output (MIMO) systems is a low complexity low-rate feedback technique, which involves transmission of a reduced number of streams from the maximum possible to improve the error rate performance of linear receivers. It has been shown to be effective in enhancing the performance of single-user interference-free point-to-point MIMO systems. However, performance of transmit antenna selection techniques in interference-limited environments and over frequency selective channels is less well understood. In this paper, we investigate the performance of transmit antenna selection in spatially multiplexed MIMO systems in the presence of co-channel interference. We propose a transmission technique for the downlink of a cellular MIMO system that employs transmit antenna selection to minimize the effect of co-channel interference from surrounding cells. Several transmit antenna selection algorithms are proposed and their performance is evaluated in both frequency flat and frequency selective channels. Various antenna selection algorithms proposed in the literature for single user MIMO links are extended to a cellular scenario, where each user experiences co-channel interference from the other cells (intercell interference) in the system. For frequency selective channels, we consider orthogonal frequency division multiplexing (OFDM) with MIMO. We propose a selection algorithm that maximizes the average output SINR over all subcarriers. A method to quantify selection gain in frequency selective channel is discussed. The effect of delay spread on the selection gain is studied by simulating practical fading environments with different delay spreads. The effect of the variable signal constellation sizes and the number of transmitted streams on the bit error rate (BER) performance of the proposed system is also investigated in conjunction with the transmit antenna selection. Simulation results show that for low to moderate interference power, significant improvement in the system performance is achievable with the use of transmit antenna selection algorithms. Even though the gain due to selection in frequency selective channels is reduced compared to that in flat fading channels due to the inherent frequency diversity, the performance improvement is significant when the system is interference limited. The performance improvement due to reduced number of transmit streams at larger signal constellation sizes is found to be more significant in spatially correlated scenarios, and the gain due to selection is found to be reduced with the increased delay spread. It is found that employing transmit antenna selection algorithms in conjunction with adaptation of the number of transmitted streams and the signal constellation sizes can significantly improve the performance of MIMO systems with co-channel interference.     

Low-Complexity Throughput-Based Antenna Selection Method

Antenna selection is a low-cost low-complexity attractive approach in MIMO systems that capture many advantages of these systems. In this paper, our objective is to select the best antennas that maximize throughput with truncated selective repeat automatic repeat request at data link layer in zero-forcing MIMO receivers. We propose a novel binary particle swarm optimization method with throughput as its fitness function for joint transmit and receive antenna selection. The results of simulations demonstrate that the proposed throughput based antenna selection method has better performance compared to capacity based methods, and PSO algorithm can significantly reduce computational complexity.     

基于MIMO系统的天线选择

多天线MIMO（Multiple Input Multiple Output）系统利用多个收、发天线有效地改善无线通信系统性能，提高系统容量，增强系统可靠性。然而，由于使用多天线同时收发，这要求发射机和接收机使用与天线一样多的射频链路，增加了系统成本和复杂度。使用天线选择技术可以降低系统成本和复杂度，同时保留MIMO系统的优越性能。文中首先介绍了MIMO系统的实现方式，然后讨论天线选择的方法及性能，最后提出天线选择技术还存在的问题，并得出相关的结论。