一种新的多天线系统中的快速广义球形解码算法

该文提出了一种新的广义球形解码算法.与常规球形解码算法相比,它能够处理多输入多输出系统(MIMO)中发送天线M多于接收天线N的情形,并且其解码速度远大于已有的广义球形解码算法.其基本思想是将M维的传输信号矢量分成N-1和M-N+1维的子矢量xa和xb,通过一些简单地变换,就可以使用一个常规球形解码器来选取合适的xb,然后再利用另一个常规球形解码器来获得xa,从而得到整个传输信号矢量.仿真结果表明,这种新的快速广义球形解码算法(命名为双层球形解码算法)比现有的广义球形解码算法具有更低的复杂度.     

基于±1二次规划的低复杂度球形解码算法

从MIMO检测的±1二次规划模型出发,推导了最大似然MIMO检测最优解的必要条件。在此基础上提出了一种基于必要条件的球形解码改进算法,该算法在球形解码剪枝策略的基础上利用必要条件对树型搜索的节点进行进一步剪枝,从而明显降低了运算复杂度,而不降低球形解码检测算法的误比特率性能。     

广义空间调制系统的低复杂度检测算法

针对广义空间调制( GSM)系统接收端最大似然( ML)检测算法计算复杂度极高的缺点,提出了一种基于压缩感知( CS)信号重构理论的低复杂度信号检测算法。首先,在多输入多输出( MI-MO)信道模型下,通过改进正交匹配追踪( OMP)算法,得到一个激活天线索引备选集;然后,利用ML算法在该备选集中进行遍历搜索,检测出激活天线索引和星座调制符号。仿真结果表明所提算法的检测性能接近于ML算法,且复杂度约为ML算法的2%。因此,所提算法在保证检测性能的同时也大大降低了计算复杂度,实现了检测性能与复杂度之间的平衡。     

低复杂度的MIMO系统粒子滤波检测

该文通过降低采样大小和信号检测搜索空间给出了两种低复杂度的多输入多输出(MIMO)系统粒子滤波(PF)检测方法:球形约束PF和多层映射PF。在球形约束PF中,首先基于迫零原则求得所需的球形约束,然后利用该球形约束减少粒子滤波过程中每一级重要性采样生成的粒子数。多层映射PF则采用多层映射将大小为4L的正交幅度调制(QAM)星座划分为L个4-QAM星座的级联以降低信号检测的搜索范围。计算机仿真结果表明,第1种方法能够在大发送天线数的情况下保持系统性能且有效地降低粒子滤波的计算复杂度;而第2种方法能够以较低的错误性能损失为代价获得计算复杂度的极大降低。     

无线MIMO系统中天线选择技术的算法

针对多天线需要多射频链路带来的高硬件成本,分析了低复杂度的MIMO天线选择的必要性,介绍了递增天线选择算法、递减天线选择算法和改进的递增递减天线选择算法.链路仿真结果表明:递增递减算法可以快速选择出使系统容量最大的天线子集,该算法简单易于实现,计算速度快,获得的结果非常接近穷尽搜索方法得到的结果.     

多天线系统中逼近最大似然的快速检测算法

该文针对无编码的多输入多输出无线通信系统中的最大似然检测接收机在发端天线数较多、调制阶数较高时计算复杂度过高的问题,提出了一种低复杂度的球形译码算法。该算法首先利用信道信息对待检测的发送信号矢量进行分组,然后对各组内的信号矢量采用球形译码进行最大似然检测,并在组间做干扰消除。理论分析和仿真表明,该算法不仅复杂度低,而且能够逼近最大似然检测的性能。     

广义空间调制MIMO系统的优化检测算法

针对大规模多输入输出（multiple-input multiple-output,MIMO）系统中采用广义空间调制（generalized spatial modulation,GSM）时信号检测复杂度过高的问题,提出一种新型天线分组激活方案.该方案首先需将发送天线分组激活,得到天线索引备选集,然后把天线组合符号按质量因子大小进行排序,最后遵循可信度判断准则进行量化判决检测,以此得到最佳的检测结果.相较于传统算法,所提出的检测算法避免了对信号空间的遍历搜索,在大规模天线系统下的性能更加优异.计算和仿真结果表明,本文提出的算法具有复杂度低、误码率低的特点,在采用广义空间调制的通信系统中具有较高的工程应用价值.     

MIMO系统中格点减少检测算法的探讨

相对于传统的单天线系统,M IMO(多输入多输出)技术能够大大提高频谱的利用率,因而被认为是新一代移动通信系统的关键技术。格点减少算法从一个全新的角度解决了多输出信号的检测问题,具有良好的发展前景。文中简要介绍了格点减少算法的数学原理,详细介绍了格点减少算法在M IMO信号检测中的应用,并在分析其性能和计算复杂度的基础上,比较了格点减少算法与其他检测算法的差异。     

基于修正扩展信道矩阵的球形解码算法

球形解码算法是多输入多输出(MIMO)系统一种性能较好的信号检测算法,只是其计算复杂度较高,为此,有学者提出运用最小均方误差(MMSE)和压缩系数控制的初始半径来降低复杂度,然而对于16QAM调制的情形,该算法虽能降低复杂度却也损失了部分误码率。针对这一问题,文章提出一种基于修正扩展信道矩阵的球形解码算法,仿真结果表明,改进的算法在16QAM调制时不仅可以改善信号的误码率,而且基本不增加算法的计算复杂度。     

一种新的用于多天线系统的快速球形解码算法

本文提出了一种实现多输入—多输出(MIMO)无线系统最大似然(ML)信号检测的快速球形解码器框架,在本框架内,算法不需要确定半径参数,同时,在算法的搜索阶段只需要访问最少的树节点数,从而降低算法的复杂度。另外,当我们采用一种直接的Schnorr-Euchner枚举(SEE)方法时,本球解码框架可用于复数MIMO系统。仿真结果显示,和其它球形解码器相比,本解码器能大大提升最大似然(ML)检测的速度。     

An efficient generalized sphere decoder for rank-deficient MIMO systems

We derive a generalized sphere decoder (GSD) for rank-deficient multiple input multiple output (MIMO) systems using N transmit antennas and M receive antennas. This problem arises when N>M or when the channel gains are strongly correlated. The upper triangular factorization of the Grammian yields an under-determined system and the standard sphere decoding (SD) fails. For constant modulus constellations, we modify the maximum likelihood (ML) cost metric so that the equivalent Grammian is rank N. The resulting GSD algorithm has significantly lower complexity than previous algorithms. A method to handle nonconstant modulus constellations is also developed.     

Fast ML Detection for Quasi-Orthogonal STBCs of Rate 2 in Under-Determined Systems [Transactions Papers]

A fast maximum-likelihood (ML) detection scheme is proposed for the important quasi-orthogonal Space-Time Block Codes (STBCs) of symbol rate 2 for three and four transmission antennas. In particular, the proposed scheme is applicable even to the under-determined system where the number of transmission antennas is larger than that of the receive antennas. The half of the symbols of the transmission matrix are detected by two dependent double-layer sphere decoders, which are referred to as dual double-layer sphere decoding in this paper. The remaining half of the symbols are detected by single-symbol detection, of which complexity is extremely low. Numerical results demonstrate that the proposed new detection method improves the detection speed up to ten times depending on the Signalto- Noise Ratio (SNR) compared to the state-of-the-art scheme.     

User Selection Algorithms for MU‐MIMO Systems with Coordinated Beamforming

In this paper, we propose two novel user selection algorithms for multiuser multiple‐input and multiple‐output downlink wireless systems, in which both a base station (BS) and mobile stations (MSs) are equipped with multiple antennas. Linear transmit beamforming at the BS and receive combining at the MSs are used to avoid interference between users and find a better sum‐rate capacity performance. An optimal technique for selecting users would entail an exhaustive search, which in practice becomes computationally complex for a realistic number of users. Suboptimal algorithms with low complexity are proposed for a coordinated beamforming scheme. Simulation results show that the performance of the proposed algorithms is better than that provided by previous algorithms and is very close to an optimal approach with reduced complexity.     

一种低复杂度盖尔圆MIMO系统发射天线选择算法

该文在研究MIMO系统中相关信道下穷举搜索算法、盖尔圆算法等基础上,提出一种低复杂度盖尔圆算法。算法通过每次迭代中删除最小特征值所对应的列,来提高特征值的下界并减小天线间的相关性使得容量最大化或误码率最小化。理论分析和仿真结果表明,该算法在所选天线数目较多场合下具有较低的复杂度,同时其容量和误码性能优于基于范数最大的算法,接近最优穷举搜索算法。     

Joint antenna subset selection for spatial multiplexing systems based on statistical and instantaneous selection criteria

While the joint transmit/receive (Tx/Rx) AnSS with exhaustive search is the best solution for error rate minimization, its complexity makes it difficult for implementation on practical systems. To overcome this disadvantage, we propose a two-stage AnSS algorithm for the spatial multiplexing (SM) in the multiple input multiple output (MIMO) system, which employs both the statistical (i.e., average Euclidean distance, AED) and instantaneous selection criteria (i.e., modified instantaneous Euclidean distance, M-IED). The proposed algorithm reduces the computational complexity by decoupling the joint Tx/Rx selection into two separate selections of the numbers of Tx/Rx antennas and antenna subset, respectively. We show that the proposed AED criterion can be implemented through a simple look up table (LUT), thereby significantly reducing the computational complexity. Simulation results and computational complexity comparisons, prove that the proposed two-stage AnSS algorithm for the SM scheme reduces the hardware and computational complexity without any loss of the signal-to-noise ratio (SNR) and the diversity order, compared to the exhaustive search method.     

Joint estimation of the channel and I/Q imbalance for two-way relay networks

In modern day communication systems, the massive MIMO architecture plays a pivotal role in enhancing the spatial multiplexing gain, but vice versa the system energy efficiency is compromised. Consequently, resource allocation in-terms of antenna selection becomes inevitable to increase energy efficiency without having any obvious effect or compromising the system spectral efficiency. Optimal antenna selection can be performed using exhaustive search. However, for a massive MIMO architecture, exhaustive search is not a feasible option due to the exponential growth in computational complexity with an increase in the number of antennas. We have proposed a computationally efficient and optimum algorithm based on the probability distribution learning for transmit antenna selection. An estimation of the distribution algorithm is a learning algorithm which learns from the probability distribution of best possible solutions. The proposed solution is computationally efficient and can obtain an optimum solution for the real time antenna selection problem. Since precoding and beamforming are also considered essential techniques to combat path loss incurred due to high frequency communications, so after antenna selection, successive interference cancellation algorithm is adopted for precoding with selected antennas. Simulation results verify that the proposed joint antenna selection and precoding solution is computationally efficient and near optimal in terms of spectral efficiency with respect to exhaustive search scheme. Furthermore, the energy efficiency of the system is also optimized by the proposed algorithm, resulting in performance enhancement of massive MIMO systems.

     

Acquisition for DS/CDMA systems with multiple antennas in frequency-selective fading channels

A generalized code acquisition scheme for direct-sequence code-division multiple-access systems with multiple antennas is proposed over frequency-selective fading channels. The proposed scheme is developed on the framework of a generalized configuration of multiple antennas and correlators. The nonconsecutive search method is generalized and extended to multiple antenna systems to exploit multipath signals in improving acquisition performance over frequency-selective fading channels. The proposed scheme also adopts a hybrid decision strategy to make effective decisions on acquisition. The mean acquisition time performance of the proposed acquisition scheme is analyzed and evaluated in frequency-selective Rayleigh-fading channels with general multipath delay profiles and spatial-fading correlations. The effects of nonconsecutive search on mean acquisition time are investigated for various channel environments, and the optimal choice of decision strategy is discussed. Furthermore, effects of various configurations of multiple antennas and correlators, decision thresholds, and correlation interval on the performance are also investigated.     

A simple transmit diversity technique for wireless communications

This paper presents a simple two-branch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown that the scheme may easily be generalized to two transmit antennas and M receive antennas to provide a diversity order of 2M. The new scheme does not require any bandwidth expansion or any feedback from the receiver to the transmitter and its computation complexity is similar to MRRC