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。     

空间相关信道下酉空时系统的最大似然 多符号差分检测算法

 传统的酉空时系统,通常假设信道衰落系数之间相互独立,这个条件在实际系统中却很难满足,天线之间的空间相关性造成系统性能恶化.针对该问题,本文提出了空间相关信道下酉统空时系的最大似然多符号差分检测算法.本算法只需获取每个观测窗口的第一个符号,以该符号为导频符号,其传输效率渐近为1,并且不要求系统具有反馈信道,算法中最大似然解的快速搜索可以通过球形译码来实现.计算机仿真结果表明:本算法可以在不明显增加开销的情况下,有效的提高空间相关信道下酉空时系统的误码率性能.     

一种重叠Alamouti码的最大似然检测优化算法

针对准正交重叠Alamouti码(Overlapped Alamouti Code,OAC)采用最大似然(maximum likelihood,ML)接收机检测时译码复杂度高的缺点,提出了一种ML译码优化算法。利用等价信道矩阵具有部分正交性的特点,将等价信道矩阵拆分成2个相互正交的子等价信道矩阵,使得在检测每个符号分组时可分别检测2个较短分组,从而降低了ML接收机的译码复杂度。改进算法保持了与ML译码相近的误码率性能,而运算量大幅度降低,从而克服了ML译码复杂度高的缺点。     

酉空时调制系统中基于多符号差分检测的软检测器

该文设计了一种适用于差分酉空时调制体制的低复杂度软检测算法。该算法基于多符号差分检测,为软判决译码模块提供编码比特的对数似然比信息。仿真表明,在通常容许的误码范围内,采用所提出的软检测算法构建的差分酉空时调制系统比原硬判决系统节省2～4dB的信号功率,并解除了基于单符号差分检测的软检测算法在快衰落信道下的错误平层。     

空时分组码的差分检测和多符号差分检测

在介绍差分空时分组码编译码原理的基础上,给出了基于最大似然判决的差分检测和多符号差分检测方案,并对这两种译码方案的性能进行了比较。相对于普通的相干译码,这两种方案在发射和接收端都不需要对传输信道进行估计,因此具有较低的译码复杂度。最后,通过仿真结果可以看出相干检测、差分检测和多符号差分检测性能间的差异。     

一种基于统计裁剪的球形译码算法

球形译码的半径对译码的复杂度有很大的影响。文章在卡方分布特性的基础上设计了一种基于统计裁剪的改进球形译码算法,该算法通过减去估算出来的未检测层的半径的大小,达到对当前检测层的半径进行缩减的目的;同时综合考虑了信道的影响,对均方误差较大的列进行ML检测,剩余信号进行树裁剪的SD算法。仿真表明,该算法大大降低了球形译码的算法复杂度。     

一种低复杂度的差分酉空时调制多符号球形译码算法

该文提出了一种瑞利衰落信道下差分酉空时调制系统中多符号差分球形译码的改进算法。该算法在执行球形译码的最大似然度量搜索时,仅对具有较小最大似然度量的部分测试符号进行搜索,从而大大减少了搜索的次数,同时提出了一种逐项进行的最大似然度量计算方法,可以尽早发现超过搜索范围的测试符号并终止计算,在避免无谓的运算负担的同时得到所需的具有较小最大似然度量的部分测试符号。仿真表明,在适中的信噪比范围内,该算法在牺牲少量系统性能的基础上降低了超过50%的运算量。     

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.     

降低高条件数信道下的球形译码算法复杂度的方法

MIMO系统中,球形译码可以在保证接近ML检测性能的前提下大大降低检测复杂度。但当信道矩阵条件数很高时,球形译码的复杂度仍然会很高。在分析了这一现象的原因后,本文提出了在高层对权值进行合并的一种球形译码算法,因为其减小了译码搜索过程中对树的高层节点的访问的概率,由此降低了搜索复杂度。仿真结果表明,这种算法在低信噪比、高条件数时可以节约20％的浮点运算操作次数。     

MIMO-OFDM系统中基于变分贝叶斯EM算法的联合符号检测与信道估计

基于变分贝叶斯期望最大化(VBEM, variational Bayes expectation maximization)算法和Turbo原理,提出了时变信道条件下MIMO-OFDM系统中的联合符号检测与信道估计算法.设计的软入软出空时检测器在采用列表球形译码避免穷尽搜索的同时,考虑了信道估计误差方差矩阵的影响;利用空时检测获得的发送信号后验概率分布估计,推出了新的Kalman前向后向递归信道估计器.仿真结果表明,在时变多径信道条件下,提出的算法比传统EM算法和面向判决算法更加具有顽健性.     

On Multiple Symbol Detection for Diagonal DUSTM Over Ricean Channels

This letter considers multiple symbol differential detection for multiple-antenna systems over flat Ricean-fading channels when partial channel state information (CSI) is available at the transmitter. Using the maximum likelihood (ML) principle, and assuming perfect knowledge of the channel mean, we derive the optimal multiple symbol detection (MSD) rule for diagonal differential unitary space-time modulation (DUSTM). This rule is used to develop a sphere decoding bound intersection detector (SD-BID) with low complexity. A suboptimal MSD based decision feedback DD (DF-DD) algorithm is also derived. The simulation results show that our proposed MSD algorithms reduce the error floor of conventional differential detection and that the computational complexity of these new algorithms is reasonably low.     

Multiple-symbol differential sphere decoding

In multiple-symbol differential detection (MSDD) for power-efficient transmission over Rayleigh fading channels without channel state information, blocks of N received symbols are jointly processed to decide on N-1 data symbols. The search space for the maximum-likelihood (ML) estimate is therefore (complex) (N-1)-dimensional, and maximum-likelihood MSDD (ML-MSDD) quickly becomes computationally intractable as N grows. Mackenthun's low-complexity MSDD algorithm finds the ML estimate only for Rayleigh fading channels that are time-invariant over an N symbol period. For the general time-varying fading case, however, low-complexity ML-MSDD is an unsolved problem. In this letter, we solve this problem by applying sphere decoding (SD) to ML-MSDD for time-varying Rayleigh fading channels. The resulting technique is referred to as multiple-symbol differential sphere decoding (MSDSD).     

酉空时调制系统中最大似然多符号差分检测的性能分析

在酉空时调制系统中,针对连续衰落信道下最大似然多符号差分检测给出了一种误符号率截断联合界的数值计算方法.采用Gauss-Chebyrshev求积公式对成对错误概率进行数值计算,并利用提取主要错误事件技术对误符号率的联合界进行了化简.数值与仿真结果表明,采用该方法计算出的截断联合界可以在低信噪比下提供误符号率的一个上界,在较高信噪比下获得它的良好估计.在性能分析基础上进一步提出了一种近似最大似然度量,分析与仿真说明,采用该度量的多符号差分检测算法的性能非常接近最大似然检测.     

Differential space–time network coding in MIMO two‐way relay channel network

This paper focuses on noncoherent detection scheme for multiple‐input multiple‐output two‐way relay channel network with two two‐antennas source nodes and one single‐antenna relay node. An orthogonal differential space–time network coding (ODSTNC) scheme based on relay detection and forward protocol is proposed. The proposed scheme combines space–time coding with network coding, and the differential modulation and detection are used in both multiple access stage and broadcast stage. The multiple‐symbol differential detection is employed at the relay. The maximum likelihood decision and its low‐complexity sphere decoding decision are given. The upper and lower bounds on the average symbol error probability for this system under differential binary phase shift keying (DBPSK) are derived, and a diversity order of 2 is confirmed to be achieved. The simulation results show that the ODSTNC scheme has good performance, and it is available for the applications of far distance signal transmission between two terminals where channel state information is unknown. Copyright © 2014 John Wiley & Sons, Ltd.     

Fast multiple-antenna differential decoding

We present an algorithm based on lattice reduction for the fast decoding of diagonal differential modulation across multiple antenna. While the complexity of the maximum-likelihood (ML) algorithm is exponential both in the number of antenna and the rate, the complexity of our approximate lattice algorithm is polynomial in the number of antennas and the rate. We show that the error performance of our lattice algorithm is very close to the ML algorithm     

On maximum-likelihood detection and the search for the closest lattice point

Maximum-likelihood (ML) decoding algorithms for Gaussian multiple-input multiple-output (MIMO) linear channels are considered. Linearity over the field of real numbers facilitates the design of ML decoders using number-theoretic tools for searching the closest lattice point. These decoders are collectively referred to as sphere decoders in the literature. In this paper, a fresh look at this class of decoding algorithms is taken. In particular, two novel algorithms are developed. The first algorithm is inspired by the Pohst enumeration strategy and is shown to offer a significant reduction in complexity compared to the Viterbo-Boutros sphere decoder. The connection between the proposed algorithm and the stack sequential decoding algorithm is then established. This connection is utilized to construct the second algorithm which can also be viewed as an application of the Schnorr-Euchner strategy to ML decoding. Aided with a detailed study of preprocessing algorithms, a variant of the second algorithm is developed and shown to offer significant reductions in the computational complexity compared to all previously proposed sphere decoders with a near-ML detection performance. This claim is supported by intuitive arguments and simulation results in many relevant scenarios.     

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。