OFDMA框架下一种低代价直接信道信息反馈方法

该文提出一种低代价下行信道信息实时反馈方法.在接收端将模拟量信道信息扩频后叠加在上行信息序列中进行上传,不必为下行信道信息分配单独的时频资源.在基站侧利用干扰消除原理,迭代进行信息序列检测与信道信息估计.由于对下行信道信息进行了扩频处理,即使分配较低的能量也能在基站侧可靠恢复.仿真实验证明这种方法的有效性.     

基于信道反馈的MIMO-OFDM系统多用户分集研究

利用包含信道质量的反馈信息,多用户分集能显著提高无线通信系统的性能。然而,在多载波多天线(MIMO-OFDM)的架构下, 反馈所有用户的所有信道质量信息(CQI)将占据大量的无线资源,从而降低了频谱效率,因此各种有限信道反馈算法被提出来减少系统的反馈开销。该文主要研究了基于两种典型的有限信道反馈的多用户分集增益,并与理想反馈进行了对比。系统平均频谱效率数学表达式的推导考虑了可选调制方式有限的特性,更符合实际。仿真用于评估各种反馈算法下的多用户分集性能,其结果与理论分析相当匹配。并且只要恰当地选取反馈参数,有限信道反馈算法可以在不损失多用户分集增益的前提下,极大的降低反馈开销,这为设计实际系统的信道反馈提供了参考。     

一种FDD大规模MIMO系统下行信道估计算法

信道估计是大规模多输入多输出(MIMO)系统的关键技术之一。本文针对频分双工(FDD)大规模MIMO正交频分复用(OFDM)系统,研究了下行信道估计问题。通过利用大规模MIMO-OFDM信道在角度-频域中的块稀疏特性,提出了基于块匹配追踪的低复杂度估计算法。另外,针对采用时域正交导频存在估计周期过长,有可能超过系统相干时间的问题,提出了天线分组发送方案,通过牺牲观测数据长度来换取信道估计周期的减少。仿真结果表明,所提算法具有良好的抗噪性能,可以准确找出稀疏向量的非零值位置,并可自适应确定稀疏度。     

存在信道估计误差的有限反馈多用户多输入多输出传输性能分析

该文针对存在信道估计误差的有限反馈多用户多输入多输出(MIMO)传输性能进行分析。基于量化微元逼近理论得出了多用户迫零波束赋型系统容量的下界;该下界表明：存在信道估计误差时,随着码本尺寸的增大,高信噪比条件下系统容量趋于一有限值;并且,信道估计误差越大,系统容量随码本尺寸收敛越早。进一步分析了采用多用户选择分集的系统容量性能,分析表明,当用户数量趋于无穷大时,和容量有界。该文结果和现有文献的结论不同,并经由仿真结果进行验证。     

快时变FDD大规模MIMO系统智能CSI反馈方法

针对快时变频分双工(FDD)大规模多输入多输出(MIMO)系统中因无线信道干扰使信道状态信息(CSI)矩阵中存在噪声以及多普勒频移导致的时间相关性使系统无法保证高可靠和低时延通信的问题,提出一种智能CSI反馈方法.该方法利用卷积神经网络(CNN)和批标准化(BN)网络对CSI矩阵中的噪声进行提取并且学习信道的空间结构,...     

下行多用户MIMO-OFDMA/SDMA系统动态资源分配

该文对下行多用户MIMO-OFDMA/SDMA系统动态资源分配算法进行了研究,在满足各种约束条件的前提下,以最大化系统吞吐量为目标建立了相应的优化模型。由于最优解难以获得,将整个优化过程分两步完成,第1步定义了一个用于度量配置多根天线的用户空间兼容性的指标,并根据该指标提出了相应的调度算法;第2步提出了两种次优的资源分配算法。仿真结果表明,所提算法优于传统的随机调度算法,与功率复用策略结合时,所提算法的性能接近于基于用户选择的最优分配算法的性能。     

多用户FDD大规模MIMO下行系统能效功率分配算法

针对多用户频分双工(Frequency Division Duplexing,FDD)大规模多输入多输出(Multiple-Input MultipleOutput,MIMO)下行系统,从绿色通信角度出发,研究了能效准下基站训练序列信号和有效数据信号的功率分配问题。首先,利用大维随机矩阵理论,推导得出能效目标函数的解析表达式。基于此,采用高发射信噪比条件,将原始的非凸分式问题转化为拟凹问题。进而,证明了全局最优功率解的存在性和唯一性,并发现最优导频功率和数据功率之比为常数,且该常数仅由系统用户数、导频长度以及信道相干时长所决定。利用该关系式,获得最优功率的闭合形式解,并提出一种低复杂度的迭代优化算法。最后,通过Matlab数值仿真对所提功率分配算法进行了验证,分析了不同系统参数(如天线数、用户数、电路功耗等)对系统最优能效性能的影响,同时可以看到通过少量的迭代次数便可收敛到稳定点。     

上下行信道不对称性对TDD-MIMO系统的影响

时分双工和多输入多输出技术均是超三代移动通信中的关键技术。在传统的关于时分双工的文献中,发送端信道状态信息均通过上下行信道的对称性获得。然而实际中由于受温度、湿度等影响,射频电路增益会缓慢变化,于是关于上下行信道对称的假设不再成立,这必定会对性能产生影响。本文详细分析了该影响并提出通过采用射频电路参数反馈法来解决这一问题。仿真结果表明,相对于传统的上行信道重用法,采用射频参数反馈法提高了系统信道容量。     

Rician信道下基于信道均值信息的自适应反馈方案

在多天线多用户下行系统中,当信道为莱斯(Rician)衰落时,基于瑞利(Rayleigh)信道假设设计出的有限反馈方法将会导致系统反馈开销的浪费。该文提出了一种适用于Rician信道的自适应反馈方案。该方案根据各用户信道的均值信息计算出相应的信道方向分布函数,然后利用其函数设计判决门限来调整各用户的量化反馈码本,使各用户量化码本中的码字矢量更加集中在用户信道矢量方向周围。另外,该方案可以自适应于不同的信道分布,在保证一定的量化误差下,根据信道均值的大小自适应调节各用户的反馈比特数,显著减少了用户的反馈量。仿真结果表明,与基于Rayleigh信道假设的有限反馈方案相比,该文提出的自适应反馈方案在不降低系统的吞吐率性能的前提下显著降低了用户的反馈开销。     

基于能效优化的大规模MIMO FDD下行系统导频和功率资源分配算法

该文针对大规模MIMO FDD下行系统,联合考虑信道估计与数据传输两个阶段的资源分配问题,提出一种能效资源分配算法。该方法以最大化能效为目标,以导频时长、导频功率和数据功率为参量,在指定发射功率和频谱效率约束的条件下建立优化模型。由于目标函数无精确解析形式,借助确定性等价原理对其近似并求得闭合表达式。进而,利用分数规划将原分式形式目标函数等价转换为减式形式,再利用目标函数的下界将非凸优化问题逐步释放为相对容易求解的等效问题,最终获得一种3层迭代能效资源优化算法。仿真结果验证了所提算法的有效性,且具有较快的收敛速度。     

基于人工智能的大规模天线信道状态信息反馈研究

信道状态信息（channel state information,CSI）的精确获取是大规模天线发挥效能的关键。在现有的通信系统中，上下行链路互易性不理想时，基于码本进行下行链路的CSI反馈。随着天线规模的增大，码本CSI反馈所需要的开销也越来越大。给出了基于人工智能（artificial intelligence,AI）的CSI反馈压缩方法，分析了基于AI的CSI反馈的标准化影响、通信流程与面临的挑战，提供了评估结果。评估结果表明，相对于基于频域基向量压缩的码本CSI反馈，基于AI的CSI反馈在相同的反馈精度下可以显著地降低反馈开销。     

基于压缩感知的大规模MIMO下行信道状态信息获取

信道状态信息（Channel State Information,CSI）对于大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）发挥高性能至关重要。但在上下行传输信道不存在互易性的频分双工（Frequency Division Duplex,FDD）制式下,若采用传统的信道估计方法会给CSI的获取带来巨大的导频开销和计算量。考虑利用大规模 MIMO 信道的虚角域稀疏性来减少获取CSI所需开销,在此基础上进一步研究了大规模 MIMO 正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统中各子载波信道在虚角域的共同稀疏特性和稀疏支撑集的时间相关特性,达到降低信道维度的目的,则大大减少了基站对 CSI 获取所需的资源开销。同时,为了降低信道稀疏支撑集信息获取所需的导频开销和提高信息的时效性,利用压缩感知技术对支撑集进行估计。仿真结果验证了所提方案性能的优越性。     

基于人工智能的大规模MIMO信道状态信息反馈综述

大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)技术凭借其高能量效率和高频谱效率的优势成为下一代移动通信的核心技术之一,其系统增益的基础在于基站能够精确获知信道状态信息(Channel State Information,CSI).由于大规模MIMO系统中基站天线数量巨大,基...     

Multiple antenna MMSE based downlink precoding with quantized feedback or channel mismatch

In this paper, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. In any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-tonoise ratio (SNR) regime, and similar to [1], [2], it is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance.     

基于动平衡状态理论的反馈线性化直接方法的改进

基于动平衡状态理论的反馈线性化直接方法,是一种建立在控制系统动平衡状态渐近稳定概念上的新的设计方法,它应用动平衡状态渐进稳定性来进行非线性系统的反馈线性化设计.本文基于动平衡状态理论的反馈线性化直接方法进行了讨论、完善和补充,针对它在对仿射非线性系统进行设计时出现的问题,提出了改进的基于动平衡状态理论的反馈线性化直接方法,它在形式和方法上对基于动平衡状态理论的反馈线性化直接方法做了一定的改进.由于动平衡状态理论的新颖性,由此引申出来的控制系统分析和设计方法将会陆续出现,论文也只是做了简单的尝试和补充,此理论还有很大的研究空间.     

Passive indoor human daily behavior detection method based on channel state information

The daily behavior detection of indoor human based on CSI is developing rapidly in the field of WSN.At present,most of the research is still in the environment of 2.4 GHz,so the detection rate,robustness and overall performance still need to be improved.In order to solve this problem,a passive indoor human behavior detection method HDFi (Human Detection with Wi-Fi) based on CSI signal was proposed.The method was used to detect the indoor human daily behavior in a 5 GHz band environment,which was divided into three steps:data acquisition,data processing,feature extraction,online detection.Firstly,the experiment collected typical daily behavioral data in complex laboratory and relatively empty meeting room.Secondly,the amplitude and phase data with more obvious features were extracted and processed by low-pass filtering to obtain a set of stable and noise-free data,and then the fingerprint database was established effectively.Finally,in the real-time detection stage,the collected data features were classified by SVM algorithm to extract more stable eigenvalues,and a classification model of indoor human daily behavior detection was established,and then matched the data in the fingerprint database.The experimental results show that the proposed method has the characteristics of high efficiency,high precision and good robustness,and the method does not need any testing personnel to carry any electronic equipment,so it has high practicability.     

利用信道状态信息的室内定位技术

多径效应导致基于信号接收强度（RSSI）的室内定位方法精度不高,采用更细粒度的物理层信道状态信息（CSI）可以区分不同路径,提高定位精度。在已有基于CSI室内定位方法的基础上,通过改进对数距离路径损耗模型,得到CSI与传输距离的关系,并结合目标位置所测得的CSI值回归出目标与发射端的距离,最后通过三边定位法预测出目标的位置坐标。实验表明,相比基于RSSI的定位方法以及已有的基于CSI的定位方法,所提方法2 m以内的误差概率提高了将近40%和20%,有效提高了定位精度。     

Unquantized and uncoded channel state information feedback in multiple-antenna multiuser systems

We propose a channel state information (CSI) feedback scheme based on unquantized and uncoded (UQ-UC) transmission. We consider a system where a mobile terminal obtains the downlink CSI and feeds it back to the base station using an uplink feedback channel. If the downlink channel is an independent Rayleigh fading channel, then the CSI may be viewed as an output of a complex independent identically distributed Gaussian source. Further, if the uplink feedback channel is an additive white Gaussian noise channel, and the downlink CSI is perfectly known at the mobile terminal, it can be shown that UQ-UC CSI transmission (that incurs zero delay) is optimal in that it achieves the same minimum mean-squared error distortion as a scheme that optimally (in the Shannon sense) quantizes and encodes the CSI, while theoretically incurring infinite delay. Since the UQ-UC transmission is suboptimal on correlated wireless channels, we propose a simple linear CSI feedback receiver that can be used to improve the performance of UQ-UC transmission while still retaining the attractive zero-delay feature. We provide bounds on the performance of such UQ-UC CSI feedback and study its impact on the achievable information rates. Furthermore, we explore its application and performance in multiple-antenna multiuser wireless systems, and also propose a corresponding pilot-assisted channel-state estimation scheme.     

Adaptive MIMO-OFDM based on partial channel state information

Relative to designs assuming no channel knowledge at the transmitter, considerably improved communications become possible when adapting the transmitter to the intended propagation channel. As perfect knowledge is rarely available, transmitter designs based on partial (statistical) channel state information (CSI) are of paramount importance not only because they are more practical but also because they encompass the perfect- and no-knowledge paradigms. In this paper, we first provide a partial CSI model for orthogonal frequency division multiplexed (OFDM) transmissions over multi-input multi-output (MIMO) frequency-selective fading channels. We then develop an adaptive MIMO-OFDM transmitter by applying an adaptive two-dimensional (2-D) coder-beamformer we derived recently on each OFDM subcarrier, along with an adaptive power and bit loading scheme across OFDM subcarriers. Relying on the available partial CSI at the transmitter, our objective is to maximize the transmission rate, while guaranteeing a prescribed error performance, under the constraint of fixed transmit-power. Numerical results confirm that the adaptive 2-D space-time coder-beamformer (with two basis beams as the two "strongest" eigenvectors of the channel's correlation matrix perceived at the transmitter) combined with adaptive OFDM (power and bit loaded with M-ary quadrature amplitude modulated (QAM) constellations) improves the transmission rate considerably.     

基于信道状态信息的室内感知技术

广泛存在的 Wi-Fi 网络带来了移动互联网商业服务的巨大发展,也成为现代社会的基础设施之一。从当前 Wi-Fi 网络的核心技术出发,透过无线信道状态分析的角度,阐述了无线感知技术的基本原理和实现方法,论述了近年来无线感知领域的技术创新,特别是基于信道状态信息的室内人体姿态和环境感知技术进展,最后分析了未来的发展趋势,为之后相关的研究提供了参考。