衰落信道硬判决解调下的Turbo码译码方法

实际应用中某些通信系统的解调器只能输出硬判决信息,无法较好地匹配Turbo码采用的软输入软输出译码算法。针对衰落信道,提出了一种对硬判决信息进行修正,改善Turbo码译码性能的方法。该方法通过对译码初始化信息根据不同的可靠性进行补偿,可改善来自信道的硬判决接收值的准确性。仿真结果表明,改进方法可有效提高Turbo码译码的性能,复杂度也较低。     

衰落信道下多级编码方案的软判决译码

研究Rayleigh衰落信道下,软判决译码对三种不同映射方案多级编码系统性能的影响.基于信道容量规则,构造卷积码为分量码的8ASK多级编码系统,在多阶段译码中提出利用信道状态信息的软判决支路度量计算公式,并探讨系统的误码传播特性,研究结果可为衰落信道编码调制方案的最佳设计度量提供参考.     

DS/CDMA同步信道中的多用户联合检测和译码

将迭代(Turbo)处理的思想应用于DS/CDMA系统同步信道的多用户检测和译码中,接收机利用信道译码的先验信息进行多用户前端处理,而其输出又作为信道译码器软输入,从而使多用户检测和信道译码联合进行,通过迭代逐渐逼近单用户性能,减少多址干扰的影响。仿真结果给出了迭代处理方法在不同信噪比条件下的比特误码率性能。     

一种新的π/4DQPSK解调译码方案

本文提出了一种新的π/4DQPSK解调译码方案.该方案利用非冗余纠错差分解调的硬判决信息对Viterbi软判决译码时的量度加权,从而改变了传统的差分解调结合软判决译码的量度值,使差分解调软输出的信噪比得到改善,提高了Viterbi软判决译码的性能.计算机仿真表明,相对于传统的差分解调结合软判决译码,该算法在误比特率BER为10-5时在AWGN信道中有1.4dB的性能改善,在Rician信道中同样有显著的性能改善.这使得在普遍采用差分解调软判决译码的卫星通信系统中系统容量和通信质量都得到显著改善.     

软信息辅助硬判决译码在自由空间光通信中的应用

由于在性能和复杂度之间的良好折中,软信息辅助硬判决译码近年来受到了光通信领域的高度关注,其中包括了软信息辅助比特标记(Soft-Aided Bit-Marking,SABM)算法.为了易于硬件实现,本文基于阶梯码(Staircase Code,SCC)提出了一种改进型SABM算法(improved SABM,iSABM),称为iSABM-SCC.iSABM-SCC利用信道软信息,通过两个可信度阈值将硬判决输出比特标记为三种可信度等级,用以辅助硬判决译码识别译码错误和扩展纠错能力,达到提升阶梯码性能的目的.在受大气湍流影响的自由空间光通信中的仿真表明,iSABM-SCC性能显著优于标准SCC和RS码.以强湍流信道为例,码率为0.75的iSABM-SCC在4-PAM调制下较标准SCC产生的性能增益可达4.37 dB,在8-PAM调制下较RS码产生的性能增益可达11.06 dB.     

软判决译码中软信息的提取

本文基于单载波和多载波传输的等效基带模型的衰落信道,采用比特交织的编码调制(BICM)系统,研究了软判决译码所需的软信息的提取。通过仿真说明,反馈信道噪声信息的结合解调与译码的迭代译码方法具有一定的鲁棒性。     

一种新的迭代判决反馈差分空时检测算法

针对快衰落信道,提出了Turbo码与块差分空时调制(BDSTM)串行级联的差分空时设计方案,并以该设计方案为基础,提出了一种新的迭代判决反馈差分空时检测(IDF-DSTD)算法.该算法实现了具有软输入软输出的判决反馈差分空时检测(SISO DF-DD),一方面在判决反馈线性滤波器中通过引入先验信息,提高了线性预测的准确性,另外,SISO DF-DD与外侧Turbo译码器之间通过边信息的交换实现了迭代检测与译码.仿真结果表明,在未知信道状态信息(CSI)的条件下,本文算法的误码性能接近已知CSI的相干检测,优于判决反馈块差分空时调制(DFBDSTM)约2dB.     

类卷积译码的容错解扰算法

针对自同步扰码系统的联合信源信道译码问题,本文将自同步扰码看作一种特殊的卷积编码,提出了类似卷积译码的软输入软输出(SISO)自同步去扰算法。该算法利用信源冗余更新扰码序列的外信息,在信道译码时作为先验信息进行译码,实现了自同步去扰与信道译码之间的软信息交互,充分利用了信源冗余信息,使得接收系统的性能得到了有效提升。仿真结果表明,在TPC编码条件下,当信源冗余度为70%时,联合信源信道译码的性能增益约为4.1dB。相比于单一纠错编码系统,当通信系统中存在自同步扰码时,联合信源信道译码具有更大的性能增益。      

LDPC码在水下激光通信中的研究

为了研究低密度奇偶校验码在水下激光通信系统中的性能,采用软判决迭代译码算法对系统误比特率进行了仿真,并对水下激光通信的信道模型和低密度奇偶校验码的编译码方式进行了探讨.在一定码长和调制阶数条件下,当信号光子数ns增大时,可以使误比特率降到10-5以下.结果表明,通过利用光电检测输出的软信息进行低密度奇偶校验软判决译码可以明显地降低系统误比特率.     

非理想信道不同量化规则软决策算法性能分析

在分布式检测系统中,为提高系统的检测性能,各传感器向融合中心发送多位二进制判决信息用来表示判决的可信度及判决结果。不同的量化规则及信道条件对融合系统的检测性能都有较大影响。推导出了无记忆非理想信道的条件下概率转移矩阵与误码率的关系,研究了误码率对两种不同量化规则软决策融合检测性能的影响,对比分析了两种不同量化规则的软决策融合在非理想信道条件下检测性能的优劣。最后通过3个传感器组成的网络,量化等级为3的条件下,根据N-P准则仿真对比分析了两种不同量化规则的软决策融合在不同信道条件下检测性能。     

Optimum soft decision decoding with channel state information inthe presence of fading

The article first presents the formulation for computing the optimum soft decision metrics for decoding of convolutional codes on fading channels and then demonstrate the performance gains achieved in using the optimum soft decision metrics. The optimum soft decision metrics use channel state information to account for signal strength variations due to fading. The formulation for computing the optimum soft decision metrics is given for the general case in which the statistics of the additive noise on the channel is nonstationary. However, the formulation is applied to a more simple case in which the noise is assumed to be stationary. The results indicate that at moderate signal-to-noise ratios, the 2 dB advantage usually claimed for soft decision decoding over hard decision decoding on Gaussian channels is achievable on fading channel, with the rate 3/4 code used, if the channel state information is incorporated in the soft decision metrics     

一种基于信道状态信息的最优软判决译码

针对衰减信道卷积码的译码,给出了当信道附加噪声非固定时,计算最优软判决度量的表达式。仿真结果表明,在适当的信噪比条件下,采用该方法比硬判决的信噪比提高2dB。     

Soft decision metric generation for QAM with channel estimation error

The channel code bit log likelihood ratio (LLR) for soft decision decoding is derived for quadrature amplitude modulated signals (QAM). The effect of imperfect channel knowledge on soft decision decoding performance is studied. Our results indicate this effect increases with channel estimation error and/or QAM modulation level. A metric based on generalized log likelihood ratio (GLLR) is derived for soft decision channel decoding with imperfect channel knowledge. Numerical results show that the GLLR-based metric outperforms the conventional minimum distance decoding metric that does not take into account channel estimation error.     

Near capacity multiple access scheme for interference channel usingcomplex-valued signals

A multiuser detection scheme is proposed for channels using non-spread signals. Trellis encoders and different random interleavers are employed for each user to remove the ambiguity in decoding each user's data from the composite received signal. With symbol-by-symbol soft decision, near channel capacity performance is obtained     

Iterative multiuser detection

Communication channels that involve both error-control coding and multiple-access signaling are of increasing interest in applications such as cellular telephony, wireless computer networks, and broadband local access. Optimal data detection and decoding in such channels generally require a level of computational complexity that is prohibitive for these types of applications. Turbo multiuser detection (MUD) addresses this problem by applying turbo principle of iteration among constituent decision algorithms, with intermediate exchanges of soft information about tentative decisions. This principle is applied in this paper by considering MUD and error-control decoding as the two constituent decision algorithms. The resulting iteration between soft MUD and soft channel decoding yields good results. This article reviews this area outlining both the basic principles involved and the basis for low-complexity turbo multiuser detectors that require minimal increased complexity over that of the standard channel decoder.     

Channel coding for satellite mobile channels

The deployment of channel coding and interleaving to enhance the bit-error performance of a satellite mobile radio channel is addressed for speech and data transmissions. Different convolutional codes (CC) using Viterbi decoding with soft decision are examined with inter-block interleaving. Reed-Solomon (RS) codes with Berlekamp-Massey hard decision decoding or soft decision trellis decoding combined with block interleaving are also investigated. A concatenated arrangement employing RS and CC coding as the outer and inner coders, respectively, is used for transmissions via minimum shift keying (MSK) over Gaussian and Rayleigh fading channels. For an interblock interleaving period of 2880 bits, a concatenated arrangement of an RS(48,36). over the Galois field GF(256) and punctured PCC(3,1,7) yielding an overall coding rate of 1/2, provides a coding gain of 42dB for a BER of 10^?6, and an uncorrectable error detection probability of 1–10^?9.     

A combined decision fusion and channel coding scheme for distributed fault-tolerant classification in wireless sensor networks

In this paper, we consider the distributed classification problem in wireless sensor networks. Local decisions made by local sensors, possibly in the presence of faults, are transmitted to a fusion center through fading channels. Classification performance could be degraded due to the errors caused by both sensor faults and fading channels. Integrating channel decoding into the distributed fault-tolerant classification fusion algorithm, we obtain a new fusion rule that combines both soft-decision decoding and local decision rules without introducing any redundancy. The soft decoding scheme is utilized to combat channel fading, while the distributed classification fusion structure using error correcting codes provides good sensor fault-tolerance capability. Asymptotic performance of the proposed approach is also investigated. Performance evaluation of the proposed approach with both sensor faults and fading channel impairments is carried out. These results show that the proposed approach outperforms the system employing the MAP fusion rule designed without regard to sensor faults and the multiclass equal gain combining fusion rule     

AWGN信道下LDPC码的译码算法研究

在高斯白噪声(AWGN)信道情况下,针对LDPC码的译码算法进行深入分析后,对适用于低密度奇偶校验(LDPC)码的硬判决译码算法与软判决译码算法进行了仿真与对比分析,并通过引入乘性校正因子以降低软判决算法中对数域置信传播(LLR-BP)算法的变量消息相关性。仿真分析表明改进后的LLR-BP算法与原算法相比,在几乎不增加计算复杂度的情况下,其译码纠错性能得到了明显的改善。因而改进后的LLR-BP算法具有明显的优越性。     

Algebraic Soft-Decision Decoding of Reed–Solomon Codes Using Bit-Level Soft Information

The performance of algebraic soft-decision decoding of Reed–Solomon codes using bit-level soft information is investigated. Optimal multiplicity assignment strategies for algebraic soft-decision decoding (SDD) with infinite cost are first studied over erasure channels and the binary-symmetric channel. The corresponding decoding radii are calculated in closed forms and tight bounds on the error probability are derived. The multiplicity assignment strategy and the corresponding performance analysis are then generalized to characterize the decoding region of algebraic SDD over a mixed error and bit-level erasure channel. The bit-level decoding region of the proposed multiplicity assignment strategy is shown to be significantly larger than that of conventional Berlekamp–Massey decoding. As an application, a bit-level generalized minimum distance decoding algorithm is proposed. The proposed decoding compares favorably with many other Reed–Solomon SDD algorithms over various channels. Moreover, owing to the simplicity of the proposed bit-level generalized minimum distance decoding, its performance can be tightly bounded using order statistics.