连续衰落信道下适用于酉空时调制的多符号差分球形译码算法

基于连续衰落信道假设,将一种具有递推形式的近似最大似然(ML)度量嵌入自动球形译码算法中,提出了多符号差分近似自动球形译码(MSDAASD)。该算法适用于一般酉空时星座,克服了准静态信道假设下多符号差分球形译码(MSDSD)的错误平层现象,具有接近ML检测的性能,其平均复杂度在大多数情况下低于相同假设下的判决反馈检测算法。     

基于动态分组的球形译码算法

在MIMO信号检测中,采用最大似然算法可以使系统的误码率最低,但最大似然算法要搜索整个信号空间,计算速度相当慢。球形译码算法性能最接近最大似然算法,它通过减少需要比较的信号点可大大降低计算量。提出了动态分组的球形译码算法,对传统球形译码算法进行了改进。仿真结果表明,所提算法可以根据M IMO系统的需要进行动态调整,可在小信噪比时降低误码率,大信噪比时提高译码速率。     

MIMO系统中一种改进的ZF-OSIC信号检测算法

为了寻找一个可靠性较高且复杂度较低的多输入多输出(Multiple Input Multiple Output,MIMO)检测算法,文中基于MIMO系统中传统的排序的迫零串行干扰抵消ZF-OSIC(Zero Forcing-Ordered Successive Interference Cancellation,ZF-OSIC)以及最大似然ML(Maximum Likelihood,ML)信号检测算法,提出一种将两种传统算法相结合的新算法,ZF-OSIC K-correction检测算法,该算法综合了二者的优点。运用ML算法中的枚举思想来选择性地修正ZF-OSIC算法得到的检测结果,从而在算法复杂度增加不大的情况下,得到性能的改善,准确度更加逼近ML算法。     

V-BLAST光MIMO系统检测算法分析

为了降低系统光多输入多输出(MIMO)系统的复杂度,提高系统的性能,介绍了迫零(ZF)检测算法、最小均方误差(MMSE)检测算法、最大似然(ML)检测算法在垂直分层空时编码(V-BLAST)光MIMO空时系统中的应用。从理论上对算法性能和复杂度进行研究,然后在MATLAB建立仿真模型,对多模光纤的传输函数进行仿真,结果表明在多模光纤链路中,ZF算法性能较低;MMSE算法较ZF算法有所改进;ML算法通过比较接收符号和原发送的符号之间的相似度,从而获得原符号的最小差错概率,其性能最好。     

低复杂度MIMO检测技术分析

为了克服多径传播对信号传输的影响,提出了多入多出(MIMO)检测的3种低复杂度算法,给出了各种算法的具体原理,特别对基于Chase原理的检测算法进行了介绍,论述了相对于最大似然算法可减低复杂的程度,研究了各种算法的误码率性能及复杂度。给出了2发2收MIMO系统和3发3收MIMO系统的仿真结果。结果表明,球形译码算法和基于Chase原理的MIMO检测算法能以比较低的复杂度,获得逼近最大似然检测算法的误码率性能。研究的检测算法为MIMO无线通信接收机的硬件实现提供了理论基础。     

针对大规模多输入多输出的动态调整排序串行干扰消除算法

针对多输入多输出（MIMO）系统非线性检测中排序串行干扰消除（OSIC）算法信号检测性能弱的问题,提出了一种可动态调整的OSIC(D-OSIC)检测算法。为解决早期的误差传播问题,通过最大似然（ML）算法选择最佳符号,提高ML-D-OSIC算法的检测性能。根据遍历容量动态调节消除层的数目,并结合混合迭代算法降低算法的复杂度。仿真结果表明,ML-D-OSIC算法的信号检测性能明显优于OSIC算法,检测性能可通过调整预定义阈值、偏移量和权重而提升,且复杂度远低于ML算法。     

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。     

基于正交训练序列的MIMO系统联合最大似然时频同步和信道估计

该文推导了多输入多输出(MIMO)系统中的符号定时、频偏和信道参数的联合最大似然(ML)估计。针对联合ML估计没有闭合的表达式、数值计算复杂度高的问题,该文提出了一种基于重复结构的正交训练序列的简化估计算法。该估计算法形式简单、复杂度低,且仍为最大似然估计。最后仿真分析了最大似然参数估计的均方误差与接收信噪比和天线数目的关系,并与Cramer-Rao界作了比较,表明了该算法的有效性。     

MIMO协同中继系统中的最大似然合并解调算法

协同中继系统通过合并解调不同路径的信号副本,得到比非协同系统更优的误码性能。传统的合并解调算法将合并解调过程分开处理,性能较差。该文针对多输入多输出（MIMO）放大转发协同中继系统,基于最大似然（ML）准则,提出了在目的节点对来自源节点和中继节点的信号进行合并解调的新算法。该算法首先对来自源节点和中继节点的信号进行ML合并,然后采用传统的MIMO最大似然检测完成信号的解调。分析与仿真结果表明,与最大比合并（MRC）等算法相比,在不同调制方式和信道条件下,所提算法均获得了显著的性能增益,且高阶调制下的复杂度低。      

连续衰落信道下适用于酉空时调制的最大似然多符号差分检测算法

为酉空时调制系统设计的多符号差分球形译码(MSDSD)能以较低复杂度获得最大似然(ML)检测性能。但是,该算法基于准静态信道假设,当将它用于快衰落信道时会出现严重的误码平层现象。本文基于连续衰落信道假设,推导了一种ML度量的递推形式,并将其嵌入自动球形译码算法中,得到了的多符号差分自动球形译码(MSDASD)算法。该算法适用于一般酉空时星座,克服了MSDSD的误码平层现象,可达到ML检测的性能,其平均复杂度在大多数情况下低于相同假设下的判决反馈检测算法。     

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。     

An approximate MAP-based iterative receiver for MIMO channels using modified sphere detection

For coded multiple-input multiple-output spatial multiplexing (MIMO-SM) systems, the iterative receiver consisting of the MIMO detector and decoding can provide near optimal performance. While the sphere detection (SD) technique can be employed to implement the MIMO maximum likelihood (ML) detection with a lower complexity, some modifications of the SD have been proposed to provide a soft-decision for iterative receivers. In the paper, we propose an alternative approach that is based on a quadratic cost function to find the maximum a-posteriori (MAP) solution for the MIMO detection. Using the proposed approach, the MAP detection with the soft-decision can be straightforwardly implemented by the SD technique. Compared to the existing approach, in the new scheme, the soft-decision is well defined and it avoids a numerical instability in computing a soft-decision (which is an approximation of the log likelihood ratio (LLR)). Through simulation results, it is shown that the performance of the proposed scheme is comparable to that of the existing approach.     

The Error Probability of the Fixed-Complexity Sphere Decoder

The fixed-complexity sphere decoder (FSD) has been previously proposed for multiple-input multiple-output (MIMO) detection in order to overcome the two main drawbacks of the sphere decoder (SD), namely its variable complexity and its sequential structure. Although the FSD has shown remarkable quasi-maximum-likelihood (ML) performance and has resulted in a highly optimized real-time implementation, no analytical study of its performance existed for an arbitrary MIMO system. Herein, the error probability of the FSD is analyzed, proving that it achieves the same diversity as the maximum-likelihood detector (MLD) independent of the constellation used. In addition, it can also asymptotically yield ML performance in the high-signal-to-noise ratio (SNR) regime. Those two results, together with its fixed complexity, make the FSD a very promising algorithm for uncoded MIMO detection.     

Reduced-Complexity (Quasi-)Maximum-Likelihood Detectors with No Performance Degradation for S-QAM Modulated MIMO Systems

This paper proposes a rotation and scaling based transformation method to simplify the (quasi-)maximum-likelihood (ML) detectors (such as QRD-M, sphere decoding (SD), etc.) for the square quadrature amplitude modulation (S-QAM) modulated multiple-input and multiple-output (MIMO) systems with no performance degradation. The key idea of the simplification is to utilize the symmetric shape of the S-QAM constellation so that after rotation and scaling, real multiplication and addition with certain constellation points in symbol replica generation simply transform into bit shifting or even vanish. As an illustrative example, the QRD-M detector is employed in this work. By using the proposed method, the number of real multiplications of the symbol replica generation required for the QRD-M detector is reduced by 50% and 25% for 4-QAM and 16-QAM, respectively. The numbers of real addition reduction is twice the amount of multiplication. The underlying principle of the proposed rotation and scaling transformation can be straightforwardly extended to amplitude and phase-shift keying (APSK) modulated MIMO systems employing the QRD-M, SD, list sequential sphere decoder (LISS), list sphere decoding (LSD), and the full ML detectors.     

A Statistical Pruning Strategy for Schnorr-Euchner Sphere Decoding

The high computational complexity of maximum likelihood (ML) decoding can impact many applications such as code division multiple access (CDMA) and multiple-input multiple-output (MIMO) systems. The sphere decoder (SD) as an efficient ML decoder has therefore received significant attention in the wireless research community. This letter presents a new statistical method to reduce the complexity of the Schnorr and Euchner sphere decoder (SESD). The method uses a set of bounds, which are computed using the conditional probability based on the minimum metric of the current solution. A lookup tabic for the bounds can be computed offline. The proposed method is effective for any number of antennas with complexity savings about 50% or more over the conventional SD approach.     

基于MIMO系统的球形译码算法的改进

在最大似然检测中,球形译码算法是一种有效的快速算法。提出一种基于MIMO系统的新的快速球形译码算法,它的复杂度比传统的算法要小的多。在提出的方法中,初始半径的选择并不重要。这种改进算法的译码性能和复杂度由两个参数来控制。因此,该方法存在着译码性能和复杂度的均衡。通过计算机仿真,可以看到,提出改进算法的译码性能得到了较大的提高。     

Zero forcing based sphere decoder for generalized spatial modulation systems

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero‐forcing (ZF)‐based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.     

A new complex sphere detector with SE enumeration

Multiple-Input Multiple-Output (MIMO) techniques are promising in wireless communication systems for its high spectral efficiency. Sphere Detector (SD) is favoured in MIMO detection to achieve Maximum-Likelihood (ML) performance. In this paper, we proposed a new SD method for MIMO-Orthogonal Frequency Division Multiplexing (OFDM) systems based on IEEE802.11n, which uses Singular Value Decomposition (SVD) in complex domain to reduce the computation complexity. Furthermore, a new Schnorr-Euchner (SE) enumeration algorithm is also discussed in detail. The computer simulation result shows that the computational complexity and the number of visited nodes can be reduced significantly compared with conventional SD detectors with the same Bit Error Rate (BER) performance.     

标准球形译码算法在发射相关MIMO信道下的平均复杂度分析

球形译码算法作为实现MIMO系统最大似然检测的一种有效方法,受到广泛重视.目前,几乎所有对球形译码算法的研究,均是基于假设信道衰落系数完全统计独立并且同分布,而在实际环境下,天线之间通常存在相关性,这样会使球形译码算法的复杂度发生变化.本文针对标准的球形译码算法,对其在发射相关MIMO信道下的复杂度进行了数学分析,推导了平均复杂度的数学表达式,并利用计算机仿真,比较了在不同的信噪比和不同的发射天线数下,发射相关性强弱对算法复杂度的影响.     

Symbol detection in spatial multiplexing system using particle swarm optimization meta-heuristics

Symbol detection in multi-input multi-output (MIMO) communication systems using different particle swarm optimization (PSO) algorithms is presented. This approach is particularly attractive as particle swarm intelligence is well suited for real-time applications, where low complexity and fast convergence is of absolute importance. While an optimal maximum likelihood (ML) detection using an exhaustive search method is prohibitively complex, PSO-assisted MIMO detection algorithms give near-optimal bit error rate (BER) performance with a significant reduction in ML complexity. The simulation results show that the proposed detectors give an acceptable BER performance and computational complexity trade-off in comparison with ML detection. These detection techniques show promising results for MIMO systems using high-order modulation schemes and more transmitting antennas where conventional ML detector becomes computationally non-practical to use. Hence, the proposed detectors are best suited for high-speed multi-antenna wireless communication systems. Copyright © 2008 John Wiley & Sons, Ltd.