Channel capacity of two-antenna BLAST architecture

The BLAST architecture has been recently proposed as an extremely efficient tool for wireless communications in rich multipath environments. However. The channel capacity of the BLAST architecture strongly depends on the correlation between individual channels. The author reports an explicit closed-form expression of the channel capacity of a two-antenna BLAST architecture as a function of the channel correlation     

分布式MIMO系统信道容量分析

首先推导了分布式MIMO点对点链路遍历信道容量的近似表达式或理论下界,然后给出小区平均遍历容量的表达式.在此基础上,研究D-MIMO与C-MIMO系统分别在BT和ST两种天线选择机制下的平均遍历容量.最后通过仿真,证明了所推导理论表达式的正确性,同时比较了两种MIMO系统的信道容量.     

Channel capacity of the distributed MIMO relay in visible light communication systems

Visible light communication (VLC) is a novel paradigm that uses light-emitting diode (LED) light as an information carrier and has several advantages over radio-frequency communication in terms of the bandwidth, security and multi-path fading. When the VLC system is considered in an indoor environment, LED lamps, which are placed at the ceiling to provide ambient light, can offer rich spatial resources for VLC as distributed intermediate relaying terminals. This paper introduces a novel distributed multiple-input multiple-output (D-MIMO)-relaying VLC scheme and analyzes its communication performance. Using the sum rate of the broadcasting and multiple access relay channels, a tight upper bound on the channel capacity was derived. The numerical results showed that the D-MIMO-relaying VLC scheme outperformed the direct-path-based scheme in terms of the channel capacity. For a given indoor environment, the capacity of D-MIMO-relaying VLC can be improved further by selecting the appropriate relay parameters, such as the number of LED–PD pairs in a relay, distance between relays and height of relays.     

MIMO的反馈信道研究

该文提出了在闭环MIMO容量研究中引入了率失真理论的研究方法,推导出了反馈信道速率和闭环MIMO容量之间的数学关系。通过理论分析和仿真结果,得出了有关反馈信道速率与信噪比,天线数,闭环MIMO容量之间变化关系的四个重要结论。为实际的闭环MIMO系统设计提供了折衷反馈信道开销和闭环MIMO容量的依据,对系统设计有重要的指导意义.     

MIMO信道建模方法

对MIMO衰落信道的精确描述是设计多天线无线系统非常重要的一个要求。首先简要介绍了MIMO技术的发展史,同时详细介绍了MIMO信道的建模方法,比较了不同建模方法之问的异同。着重介绍了射线追踪方法构建MIMO信道模型的方法,给出了在确定性环境中的信道矩阵的构建方法。同时给出了信道容量的计算方法。     

On the approximation of MIMO capacity

Information theoretical optimization problems related to the resource allocation of wireless cellular and ad hoc networks are not solvable in closed form due to the nonlinear logarithmic representation of the Shannon capacity. This paper introduces functional approximations to the MIMO capacity over flat Rayleigh fading channels, which allow for analytical solutions to network resource optimization problems. The precision of the suggested approximations is assessed and is shown to provide a very close match to the exact capacity expression.     

MIMO系统信道容量研究

针对单用户MIMO系统信道的容量特性展开研究。首先详细推导了无衰落信道下信道容量表达式,然后重点分析了瑞利衰落信道下,接收端已知信道状态信息,发射端已知信道状态分布时的容量特性。最后分别针对瑞利衰落信道下,采用发射分集、接收分集以及BLAST传输结构的系统容量进行仿真。仿真结果表明:给定发射功率,独立的瑞利衰落信道条件下,MIMO系统容量随最小天线数目的增加而线性增加,极大地提高了系统容量。     

Low complexity MIMO scheduling with channel decomposition using capacity upperbound

In multiuser MIMO systems, the base station schedules transmissions to a group of users simultaneously. Since the data transmitted to each user are different, in order to avoid the inter-user interference, a transmit preprocessing technique which decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO channels can be used. When the number of users is larger than the maximum that the system can support simultaneously, the base station selects a subset of users who have the best instantaneous channel quality to maximize the system throughput. Since the exhaustive search for the optimal user set is computationally prohibitive, a low complexity scheduling algorithm which aims to maximize the capacity upper bound is proposed. Simulation results show that the proposed scheduling algorithm achieves comparable total throughput as the optimal algorithm with much lower complexity.     

Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection

This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multipleinput and multiple-output (MIMO) channels. The proposed MCMC detector (Log-MAP-tb b-MCMC) operates in a strictly bit-wise fashion and adopts Log-MAP algorithm with table look-up. When concatenated with an optimized low-density parity-check (LDPC) code, Log-MAP-tb b-MCMC can operate within 1.2-1.8 dB of the capacity of MIMO systems with 8 transmit/receive antennas at spectral efficiencies up to n = 24 bits/channel use (b/ch). This result improves upon best performance achieved by turbo coded systems using list sphere decoding (LSD) detector by 2.3-3.8 dB, leading to nearly 50% reduction in the capacity gap. Detailed comparisons of the Log- MAP-tb b-MCMC with LSD based detectors demonstrate that MCMC detector is indeed the detector of choice for achieving channel capacity both in terms of performance and complexity.     

平坦信道下的MIMO信道估计误差分析

基于导频序列推导了频率平坦多输入多输出(MIMO)信道下的最小二乘信道估计(LS)误差;将信道估计误差等效为高斯噪声,推导了信道估计条件下系统的等效信噪比,提出了用系统的等效信噪比来分析和评估在信道估计误差条件下系统的误码性能;最后用等效信噪比的方法评估了ZF-V-BLAST算法在信道估计下的性能,结果表明和计算机仿真结果基本相吻合。     

使用MIMO技术的固定中继蜂窝网容量分析

为固定中继蜂窝网络提供了一种新的性能分析方案,该方案以引入未来将广泛使用的MIMO天线系统为出发点,通过分析在不存在固定中继和存在固定中继两种情况下系统信道容量的变化,考察固定中继蜂窝网络架构的优越性。通过SIMO MISO和MIMO各种情况下的信道容量计算,运用蒙特卡罗方法,得出最后的数值结果。     

Observation-Based Time-Varying MIMO Channel Model

This paper presents a method to model and simulate time-varying narrowband multiple-input–multiple-out (MIMO) channels based on observations from measured data. The data were obtained in a vehicular urban environment, with a fixed transmitter array and a mobile receiver array. The measured channel response matrices were decomposed to isolate the coupling from the transmitter eigenbasis to the received eigenbasis, as in the Weichselberger model. These complex coupling elements have been characterized and seen to comprise directional components that may be Ricean or Rayleigh fading. The Rayleigh fading directional components can be well modeled using the von Mises probability density function, which is parameterized for the time-varying model using the measured data. The model has been validated by comparing the mutual information and eigenstructure autocorrelation characteristics of its output with those of the measured data. The statistical nature of the model means that different realizations can be generated, each representative of the originating data.      

MIMO capacity with interference

System capacity is considered for a group of interfering users employing single-user detection and multiple transmit and receive antennas for flat Rayleigh-fading channels with independent fading coefficients for each path. The focus is on the case where there is no channel state information at the transmitter, but channel state information is assumed at the receiver. It is shown that the optimum signaling is sometimes different from cases where the users do not interfere with each other. In particular, the optimum signaling will sometimes put all power into a single transmitting antenna, rather than divide power equally between independent streams from the different antennas. If the interference is either sufficiently weak or sufficiently strong, we show that either the optimum interference-free approach, which puts equal power into each antenna, or the approach that puts all power into a single antenna is optimum and we show how to find the regions where each approach is best.     

Algorithms for the MIMO Single Relay Channel

The MIMO single relay channel consists of a transmitter, a relay, and a receiver, all equipped with multiple antennas, located in an environment with distance-dependent path loss as well as scattering. We describe an optimal and a heuristic algorithm to solve the spatial energy allocation problem for the MIMO single relay channel when the scattering clusters on the direct and relay links are non-overlapping. These algorithms can be applied to existing wireless LAN systems that aim to increase their performance via relays. By simulations, we compare the performances of joint and uniform energy allocations across the spatial channels, and the performances of a direct transmission system and a system that utilizes the relay node     

MIMO信道模型分析﹡

无线信道作为移动通信传输媒介,所有信息包含其中.要想充分利用频谱资源并且使传输信息的质量和容量最大化,信道特性应被清楚了解.同时,研究移动通信4G技术在复杂的无线传播环境中性能,离不开MIMO信道模型,因此对MIMO信道模型的分析十分必要.简要介绍了MIMO信道模型分类,并着重研究了基于几何分布统计信道模型的基础模型—SCM信道模型.最后对多普勒、时延扩展以及角度扩展仿真分析,验证了SCM信道建模的正确性.     

MMSE信道估计下的软输出MMSE MIMO检测算法

信道编码的MIMO无线通信系统中,MIMO信号检测器需要输出编码比特的对数似然比,以获得更好的误码率性能.现有的软输出MMSE MIMO检测算法基于理想信道估计得到,在实际信道估计下会导致性能损失.本文针对MMSEMIMO信道估计,基于MMSE信道估计的统计特性,推导了考虑信道估计误差影响的新的软输出MMSE MIMO检测算法.仿真结果表明,相对于现有的软输出MMSE MIMO检测算法,所提出的算法可以显著降低由于信道估计误差导致的残留误码平层,而增加的计算复杂度可以忽略不计;同时,所提算法对信道估计误差方差的相对误差不敏感,具有实际应用的价值.     

On the Gaussian MIMO Relay Channel With Full Channel State Information

This paper addresses the problem of source and relay transmit covariance optimization on the Gaussian MIMO relay channel with full channel state information (CSI), i.e., assuming perfect knowledge of all channels. For full-duplex relaying, we show that the cut-set bound on capacity can be computed as the solution of a convex problem, thus providing a tighter bound than previously published. For time division duplex (TDD) relaying, both upper and lower bounds on capacity are derived, and the transmit covariance matrices are optimized for decode-and-forward (DF) strategies with either partial or full decoding at the relay. A generic procedure is introduced to formulate these problems into a standard convex form, and to solve them efficiently. Suboptimum precoders are also proposed which have a specific matrix structure that either leads to a closed-form expression or at least reduces the dimension of the optimization problem. Practical aspects related to transmit power constraints and CSI availability are then discussed. Finally, simulations in a cellular downlink scenario show that the partial DF strategy can achieve a rate very close to capacity for realistic values of the source to relay SNR, and that the rate loss due to suboptimum precoder structures remains small for typical antenna configurations.      

闭环MIMO的容量损失研究

首先建立了闭环MIMO(multiple-input-multiple-output)的系统模型,推导出了闭环MIMO容量损失与反馈信道速率之间的数学关系。通过仿真这个数学关系,得出了在不同信噪比、天线数、中断概率下,容量损失相对于反馈信道速率变化规律的相关结论。这个数学关系和这些结论,为实际的闭环MIMO系统设计提供了一定的基础依据,对综合考虑信噪比、天线数、中断概率、闭环MIMO容量损失和反馈信道速率的系统设计有参考意义。     

基于信道状态的MIMO预编码算法

针对多输入多输出（MIMO）的应用需要,研究了一种利用发端信道状态信息（CSIT）进行预编码,增强系统性能的方法。该方法在发送端采用线性预编码器对CSIT进行预编码,合理分配不同天线的发射功率以提高系统性能;分别在低、高信噪比条件下,对进行预编码前后的容量比值差值进行了仿真分析。分析结果表明：进行预编码后,MIMO系统容量明显改善,以上研究结果对MIMO的工程应用有良好的参考意义。     

MIMO系统的信道容量

近年来信息论研究表明,MIMO系统具有巨大的理论容量。首先介绍了信息理论中信道容量概念的发展,描述了一个在实验室实时完成的V-BLAST无线通信结构实例,最后讨论了MIMO系统在通信领域的应用。