MIMO系统中随参信道的容量分析

在确定性的恒参信道中信道容量是确定的值,就是香农信道容量,它是可靠信息传输的上界。然而在现实情况下信道不是确定性的而是随机时变的,在现实的随参信道的情况下,对MIMO系统中的容量进行了理论分析,并进行了系统性仿真研究。     

MIMO系统容量的降雨衰减频率特性分析

多输入多输出技术可用有限的频谱资源提高信道容量,改善系统性能。本文将气象环境影响作为一个乘性噪声,通过推导相关信道模型的收发天线相关系数,从统计特性角度建立相关信道矩阵,研究为如何减小MIMO信道容量受降雨的影响提供了依据。     

MIMO-OFDM通信系统研究

采用多入多出(MIMO)技术可以提高信道容量和信道可靠性,降低误码率.正交频分复用(OFDM)是一种特殊的多载波传输方案,各子载波在整个符号周期上正交,各子载波信号子频谱可以互相重叠,提高频带利用率.MIMO-OFDM技术是OFDM与MIMO技术结合形成的一种新技术,该技术是在OFDM传输系统中采用阵列天线实现空间分集,提高了信号质量.本文全面介绍了MIMO技术和OFDM技术及两者的结合,分析实现MIMO-OFDM技术的框架.     

WiMAX系统中MIMO信道模型的性能仿真

提出了IEEE802.16e协议中,一种适用于研究MIMO系统性能的信道模型-SCME信道城市宏环境。讨论了MIMO信道模型的适用条件。通过在WiMAX上行浮点平台仿真Virtual MIMO性能证明：SCME信道城市微环境能充分体现出MIMO信道的各种特性,是作为MIMO系统性能评估和比较的理想信道模型。     

MOMO-OFDM技术及其在局域网中应用

采用正交频分复用(OFDM)可以提高频带利用率.采用MIMO技术可以提高信道容量和信道可靠性,降低误码.MIMO-OFDM将OFDM技术与MIMO技术结合起来,在不增加带宽与功率的前提下,可以增加数据的传输数率,被视为下一代无限局域网的核心技术.文章简单介绍了MIMO-OFDM技术的原理.并探讨了其在下一代高速无限局域网中的应用.     

MIMO-OFDM技术及其在局域网中应用

采用正交频分复用(OFDM)可以提高频带利用率。采用MIMO技术可以提高信道容量和信道可靠性,降低误码。MIMO-OFDM将OFDM技术与MIMO技术结合起来,在不增加带宽与功率的前提下,可以增加数据的传输数率,被视为下一代无限局域网的核心技术。文章简单介绍了MIMO-OFDM技术的原理,并探讨了其在下一代高速无限局域网中的应用。     

LTE MIMO室内改造方案及信道容量分析

室内覆盖在网络建设中是极其关键和重要的环节,越来越受到运营商的重视,MIMO作为LTE核心技术之一,在提高信道容量,增强信道可靠性等方面起着重要作用,因此,对支持MIMO的LTE室内分布方案及相应的信道的容量进行研究显得非常必要.从LTE室内解决方案入手,着重讨论支持MIMO的情形,并对不同LTE室内改造方案进行对比.     

MIMO系统及其信道容量分析

主要介绍了MIMO系统的由来,以及对其主要的研究历程,在此基础上给出了MIMO系统的模型,以及MIMO系统输入输出的表达式,最后还进一步分析了MIMO系统的信道容量。     

移动无线信道技术在地下矿井中应用研究

多输入多输出技术(MIMO)是多天线技术和信号处理技术中,越来越受关注的新一代关键技术。本文将该MIMO技术应用在地下矿井中,建立了矿井环境下的MIMO系统的GBDB散射和直射分量信道模型,推导了该模型的空时相关函数。仿真结果表明本文方法有效。     

无线通信中MIMO-OFDM系统研究

多输入输出（MIMO）技术和正交频分复用（0FDM）技术各有独特的优势和缺陷。MIMO技术可以大幅度提高无线通信系统的容量,但是抗频率选择性信道能力不强;OFDM技术利用正交子载波抗频率选择性信道,提高了频率利用率,易受频率偏差的影响,存在较高的峰值平均功率比。MIMO与OFDM技术结合构成的MIMO—OFDM系统既可以达到很高的传输效率,又有很强的可靠性,具有很大的研究空间和实用前景。     

MIMO-OFDM技术研究

多入多出(MIMO)系统在发射端和接收端分别设置多副天线,采用MIMO技术可以提高信道容量和信道可靠性,降低误码率。正交频分复用(OFDM)是一种特殊的多载波传输方案,各子载波在整个符号周期上正交,各子载波信号子频谱可以互相重叠,提高了频带利用率。MIMO-OFDM技术是OFDM与MIMO技术结合形成的一种新技术,该技术是在OFDM传输系统中采用阵列天线实现空间分集,提高了信号质量。本文中全面介绍了MIMO技术和OFDM技术及两者的结合,分析了实现MIMO-OFDM技术的框架,未来的工作是如何用硬件来仿真实现这个系统。     

MIMO通信系统研究

MIMO无线传输技术能在不增加带宽与功率的情况下成倍地提高无钱通信系统的容量和频谱准备效率,因此成为新一代无线通信系统中的关键技术之一.本文对MIMO无线通信系统原理结构及其关键技术进行了分析介绍.     

A cognitive TV white space-broadband power line MIMO system for indoor communication networks

Broadband power line communication (BPLC) is a promising solution to satisfy the growing data rate demands for broadband indoor communication networks. However, the BPLC transmission power spectral density (PSD) is restricted in the very high frequency (VHF) band to avoid harmful interference to the existing wireless services. In this paper, a new hybrid system is proposed utilizing BPLC and cognitive radio over TV white space (TVWS) to enhance the system capacity over BPLC in VHF, forming a VHF TVWS BPLC multiple-input multiple-output (MIMO) system. An iterative precoding algorithm is proposed to satisfy the interference limit at the TV primary user (PU) receiver (Rx) and enhance the ergodic capacity. Moreover, a power allocation algorithm is developed for the MIMO system to achieve the maximum ergodic capacity subject to the average total power constraint and limit of interference to TV PU. Simulation results demonstrate the significant enhancement in the achieved capacity by our proposed system in the VHF band compared to both previous cognitive and hybrid BPLC systems.     

Subcarriers-and-its allocation algorithms for downlink OFDMA-based MIMO systems

This paper proposes four resource (subcarriers-and-bits) allocation methods for OFDMA-based multiuser MIMO system. We employ adaptive modulation according to the channel state information (CSI) of each user to meet the symbol error rate (SER) requirement. The first scheme is based on transmit spatial diversity (TSD), in which the vector channel with the highest gain between the base station and specific antenna at remote terminal is chosen for transmission. The second scheme assigns subcarrier to the best user and employs spatial multiplexing on the MIMO system to further enhance the throughput. The space-division multiple-access (SDMA) scheme assigns single subcarrier simultaneously to the remote terminals with pairwise “nearly orthogonal” spatial signatures. In the fourth scheme, we propose to design the transmit beamformers based on the zero-forcing (ZF) criterion such that the multi-user interference (MUI) is completely removed. Moreover, spatial multiplexing technique is jointly exploited to achieve throughput multiplication. Numerical results demonstrate that all the proposed algorithms are simple and reliable and the fourth scheme is the best since all users are allowed to share single subcarrier.     

On the achievable tracking performance of NCSs over SNR limited channels

In this paper, the achievable tracking performance limitations of discrete-time, multi-input multi-output (MIMO) networked control systems (NCSs) are studied. The channel is modeled as an additive white Gaussian noise and signal-to-noise ratio (SNR) limited channel with feedback. Under this framework, the closed relationships among stabilization, tracking performance, and SNR limited are quantitatively revealed. Some new results a.erived according to the allpass factorization and Youla parameterization of two degrees of freedom controller. The results show that the best tracking performance is in connection with the unstable poles, non-minimum phase zeros of the system. It is also demonstrated that the tracking performance will be badly degraded by feedback channel noise and due to the SNR limited. Finally, a simulation example is presented to validate the conclusions.     

Blocking probability of massive MIMO: What is the capacity of a massive MIMO IoT system?

In this paper, we provide a methodology to evaluate the capacity of a Massive multiple-input multiple-output (MIMO) supported Internet of Things (IoT) system in which a large number of low cost low power IoT devices transmit and receive sporadic data. Numerous IoT devices are supported by a single cell Massive MIMO base station (BS) with maximum-ratio (MR) processing. Orthogonal reference signals (RSs) or pilots are assigned randomly to all the IoT devices for channel estimation purpose. The number of simultaneously active IoT devices follows Poisson distribution. Due to the tremendous number of IoT devices, orthogonal RSs are heavily reused, which severely degrades the receiver signal quality. One of the most important performance criteria for this kind of system is the blocking probability which shows the percentage of the outage IoT devices, and how we maintain the low blocking probability while supporting all the IoT devices simultaneously is particularly important. Due to RS reuse, we can divide IoT devices into two groups based on their interference levels. We provide detailed theoretical analyses, and show that the blocking primarily happens to the group with higher interference level. Increasing the number of service antennas and/or reducing the number of IoT devices can help to improve the performance of the blocking probability, however there is a regime in which the parameter adjustment helps little to improve the performance. Based on these factors, we provide a useful algorithm to improve the performance of blocking probability. A number of simulation results are also provided to validate the theoretical analysis.     

2.4GHz MIMO 网状网络中一种固定信道分配方法（英文）

由于无线网路中链路质量的不稳定、信号的广播传输模式和节点之间存在的相互干扰，针对提高无线网状网络性能的信道分配和路由选择将更加复杂。采用多信道成为一种可选的提高网络容量的方法。本文提出了一种基于2.4GHz 802.11无线网状网络的一种固定信道分配方法，采用了多输入多输出技术使得网络中的数据流以流水线的方式进行传输。在这个场景下多条并行的流可以同时被激活，以此来提升UDP和TCP的传输性能。通过对802.11b网络中1、6和11三个相互不重叠的信道的分配，该信道分配算法在空间上实现邻居节点之间的干扰最小化，其中信道1和11被分配给网状网络的主干传输部分，信道6被分配给用户接入网络。文章最后通过NS2仿真实验，并对本文提出的算法进行了分析。实验结果证明网络的平均吞吐率有大幅度提升，且多跳传输的延迟也被降低。     

Optimal beamforming-selection spatial precoding using population-based stochastic optimization for massive wireless MIMO communication systems

The beamforming-based spatial precoding (BBSP) method has been proposed to reduce the overheads of the downlink training and the channel state information feedback in the frequency-division duplex (FDD) massive multiple-input-multiple-output (MIMO) wireless communication systems. However, the original BBSP method suffers from the interference problem at user equipments (UEs) because of using a set of pre-defined fixed beamforming coefficients. Moreover, the BBSP method can not deal with the performance degradation due to mutual coupling (MC) effect because of massive antennas deployed at transmitter and receiver. This paper presents a precoding method that incorporates a beamforming-selection spatial precoding (BSSP) scheme with a population-based stochastic optimization algorithm such that the designed beamforming coefficients can greatly reduce the severe interference between UEs and alleviate the MC effect on the performance of massive MIMO systems. The proposed method can not only achieve better bit error rate (BER) performance than the conventional BBSP method, but also preserves the advantages of the BBSP method having lower overheads of the downlink training and the CSI feedback. In particular, we propose an appropriate fitness function based on an averaged BER formula for the population-based stochastic optimization algorithm to find the optimal beamforming coefficients. Numerical simulations are also presented for both the urban-macro and the urban-micro wireless MIMO scenarios to validate the superior BER performance of the proposed precoding method as compared to the existing BBSP method.