Soft multiuser decoding for vector quantization over a CDMA channel

An approach to optimal soft decoding for vector quantization (VQ) over a code-division multiple-access (CDMA) channel is presented. The decoder of the system is soft in the sense that the unquantized outputs of the matched filters are utilized directly for decoding (no decisions are taken), and optimal according to the minimum mean-squared error (MMSE) criterion. The derived decoder utilizes a priori source information and knowledge of the channel characteristics to combat channel noise and multiuser interference in an optimal fashion. Hadamard transform representations for the user VQs are employed in the derivation and for the implementation of the decoder. The advantages of this approach are emphasized. Suboptimal versions of the optimal decoder are also considered. Simulations show the soft decoders to outperform decoding based on maximum-likelihood (ML) multiuser detection. Furthermore, the suboptimal versions are demonstrated to perform close to the optimal, at a significantly lower complexity in the number of users. The introduced decoders are, moreover, shown to exhibit near-far resistance. Simulations also demonstrate that combined source-channel encoding, with joint source-channel and multiuser decoding, can significantly outperform a tandem source-channel coding scheme employing multiuser detection plus table lookup source decoding     

Hadamard-based soft decoding for vector quantization over noisychannels

We present an estimator-based, or soft, vector quantizer decoder for communication over a noisy channel. The decoder is optimal according to the mean-square error criterion, and Hadamard-based in the sense that a Hadamard transform representation of the vector quantizer is utilized in the implementation of the decoder. An efficient algorithm for optimal decoding is derived. We furthermore investigate suboptimal versions of the decoder, providing good performance at lower complexity. The issue of joint encoder-decoder design is considered both for optimal and suboptimal decoding. Results regarding the channel distortion and the structure of a channel robust code are also provided. Through numerical simulations, soft decoding is demonstrated to outperform hard decoding in several aspects     

Comparison of two convolutional orthogonal coding techniques forCDMA radio communications systems

For CDMA (code-division multiple-access) wireless communications systems, orthogonal signaling with noncoherent detection has been proposed when a reference phase is not available. In this paper, orthogonal signaling using Walsh signals is considered. Performance of the channel using error-correcting coding together with 1) bit-by-bit interleaving or 2) Walsh word-by-word interleaving is investigated. Simulation results show that for several types of fading and non-fading channels with practical amounts of interleaving and with practical power control, the second technique with complete soft decision decoding that has added complexity in the decoder gives significant reduction in the required signal to interference ratio (SIR) over the first technique     

一种频选衰落信道下的Turbo多用户检测算法

联合MAP多用户检测与信道解码的迭代多用户检测(MUD)技术可显著提高宽带移动CDMA系统的容量和性能.在多径时变衰落的编码信道下,提出一种迭代实现干扰抑制、符号估计、信道解码的Turbo多用户检测算法.在每次迭代中,MUD自适应地实现干扰抑制并输出符号估计的软信息,软输入软输出的信道解码器使用LOG MAP方法实现信道解码并反馈符号估计的软信息作为下一次TurboMUD迭代的先验信息.仿真结果证实了该算法在频选衰落信道下经两次迭代就能逼近单用户编码CDMA系统的接收性能.     

Joint Source and Channel Coding using Punctured Ring Convolutional Coded CPM

In this paper, a novel trellis source encoding scheme based on punctured ring convolutional codes is presented. Joint source and channel coding (JSCC) using trellis coded continuous phase modulation (CPM) with punctured convolutional codes over rings is investigated. The channels considered are the additive white gaussian noise (AWGN) channel and the Rayleigh fading channel. Optimal soft decoding for the proposed JSCC scheme is studied. The soft decoder is based on the a posteriori probability (APP) algorithm for trellis coded CPM with punctured ring convolutional codes. It is shown that these systems with soft decoding outperform the same systems with hard decoding especially when the systems operate at low to medium signal-to-noise ratio (SNR). Furthermore, adaptive JSCC approaches based on the proposed source coding scheme are investigated. Compared with JSCC schemes with fixed source coding rates, the proposed adaptive approaches can achieve much better performance in the high SNR region. The novelties of this work are the development of a trellis source encoding method based on punctured ring convolutional codes, the use of a soft decoder, the APP algorithm for the combined systems and the adaptive approaches to the JSCC problem.     

Analysis of an adaptive rate convolutionally coded multicarrierDS/CDMA system

The analysis of an adaptive rate convolutionally coded multicarrier direct sequence code division multiple-access (DS/CDMA) system is considered. In order to accommodate a number of coding rates easily and make the encoder and decoder structure simple, we use the rate-compatible punctured convolutional (RCPC) code. We obtain data throughputs at several coding rates, and choose the coding rate that has the highest data throughput in the signal-to-interference and noise ratio (SINR) sense. To achieve maximum data throughput, a rate adaptive system is proposed based on the channel state information (the SINR estimate). The SINR estimate is obtained by the soft decision Viterbi decoding metric. We show that the proposed rate adaptive convolutionally coded multicarrier DS/CDMA system can enhance the spectral efficiency and provide frequency diversity     

Iterative decoding of serially concatenated arithmetic and channel codes with JPEG 2000 applications.

In this paper, an innovative joint-source channel coding scheme is presented. The proposed approach enables iterative soft decoding of arithmetic codes by means of a soft-in soft- out decoder based on suboptimal search and pruning of a binary tree. An error-resilient arithmetic coder with a forbidden symbol is used in order to improve the performance of the joint source/channel scheme. The performance in the case of transmission across the AWGN channel is evaluated in terms of word error probability and compared to a traditional separated approach. The interleaver gain, the convergence property of the system, and the optimal source/channel rate allocation are investigated. Finally, the practical relevance of the proposed joint decoding approach is demonstrated within the JPEG 2000 coding standard. In particular, an iterative channel and JPEG 2000 decoder is designed and tested in the case of image transmission across the AWGN channel.     

Soft-input decoder for decoding of internally channel coded fiber-optic CDMA communication systems

We propose using a soft-input decoder for the decoding of internally convolutional coded Poisson noise-dominated fiber-optic code-division multiple-access (CDMA) communication systems using optical orthogonal codes. We first compute the coded symbol log-likelihoods at the output of the Poisson noise-dominated channel, which is then used by a soft-input maximum-likelihood decoder, for a fiber-optic CDMA system assuming both on-off keying and binary pulse position modulation schemes. Furthermore, we develop a discrete soft-output channel model for a Poisson noise-dominated channel, with which we evaluate the upper bound on the bit error probability of the internally coded Poisson noise-dominated fiber-optic CDMA system using a soft-input decoder. It is shown that the soft-input decoder significantly outperforms the hard-input decoder. Furthermore, the performance of the soft-input decoder is also evaluated in the presence of different values of dark current.     

Universal decoding for frequency-selective fading channels

We address the problem of universal decoding in unknown frequency-selective fading channels, using an orthogonal frequency-division multiplexing (OFDM) signaling scheme. A block-fading model is adopted, where the bands' fading coefficients are unknown yet assumed constant throughout the block. Given a codebook, we seek a decoder independent of the channel parameters whose worst case performance relative to a maximum-likelihood (ML) decoder that knows the channel is optimal. Specifically, the decoder is selected from a family of quadratic decoders, and the optimal decoder is referred to as a quadratic minimax (QMM) decoder for that family. As the QMM decoder is generally difficult to find, a suboptimal QMM decoder is derived instead. Despite its suboptimality, the proposed decoder is shown to outperform the generalized likelihood ratio test (GLRT), which is commonly used when the channel is unknown, while maintaining a comparable complexity. The QMM decoder is also derived for the practical case where the fading coefficients are not entirely independent but rather satisfy some general constraints. Simulations verify the superiority of the proposed QMM decoder over the GLRT and over the practically used training sequence approach.     

基于TTCM的联合编码调制算法

提出了一种具有高频带利用率和高重建质量的联合编码调制算法.采用Turbo码网格编码调制TTCM作为编码调制(CM)方案,按"最小化端到端失真"准则最优化设计信源解码器,直接利用TTCM解码输出的软判决值进行信源译码.仿真表明,相对于硬判决分离译码,本文算法将重建信号的信噪比提高了约2dB.     

Joint Erasure Marking and Viterbi Decoding Algorithm for Unknown Impulsive Noise Channels

In many real-world communication systems, the extent of non-Gaussian impulsive noise (IN) rather than Gaussian noise poses practical limits on the achievable system performance. The decoding of IN-corrupted signals is complicated by the fact that accurate IN statistics are typically unavailable at the receiver. Without exploiting the IN statistics, the conventional method is to try to mark the IN-corrupted symbols as erasures preceding a Euclidean metric based decoder. In this work, a novel joint erasure marking and Viterbi algorithm (JEVA) is proposed to decode the convolutionally coded data transmitted over an unknown impulsive noise channel. Based on the Bernoulli-Gaussian IN model, it is empirically demonstrated that JEVA not only can offer significant performance improvement over the conventional separate erasure marking and Viterbi decoding method, but also can almost achieve the optimal performance of the maximum likelihood decoder that fully exploits the perfect knowledge of the IN probability density function. Various implementations of JEVA are proposed to provide different performance-complexity trade-offs.     

基于分层空时结构的多码CDMA系统中一种新的迭代均衡接收算法的研究

为了提高基于垂直结构的分层空时结构(V-BLAST, vertical bell-laboratories layered space-time)的多码 CDMA 系统的抗干扰能力与系统容量,文章提出了一种将 MMSE 均衡与 Turbo 译码联合运算进行的方法,得到了一种针对该系统的迭代均衡接收算法。该接收算法包含两个连续的软输入软输出模块,首先经过 MMSE 均衡后得到第一个软输出,然后从 Turbo 译码器得到第二个软输出。每一次迭代过程中,从均衡和译码中得到的外赋信息作为第二次迭代的先验信息。仿真结果表明,文章提出的迭代均衡接收算法相比较传统非迭代接收算法,性能有非常可观的改善。     

Near-optimum decoding of product codes: block turbo codes

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is an estimation of the log-likelihood ratio (LLR) of the binary decisions given by the Chase decoder. The theoretical justifications of this algorithm are developed and the method used for computing the soft output is fully described. The iterative decoding of product codes is also known as the block turbo code (BTC) because the concept is quite similar to turbo codes based on iterative decoding of concatenated recursive convolutional codes. The performance of different Bose-Chaudhuri-Hocquenghem (BCH)-BTCs are given for the Gaussian and the Rayleigh channel. Performance on the Gaussian channel indicates that data transmission at 0.8 dB of Shannon's limit or more than 98% (R/C>0.98) of channel capacity can be achieved with high-code-rate BTC using only four iterations. For the Rayleigh channel, the slope of the bit-error rate (BER) curve is as steep as for the Gaussian channel without using channel state information     

Vector quantization with transmission energy allocation fortime-varying channels

This work is concerned with the problem of designing robust, vector quantizer (VQ)-based communication systems for operation over time-varying Gaussian channels. Transmission energy allocation to VQ codeword bits, according to their error sensitivities, is a powerful tool for improving robustness to channel noise. The power of this technique can be further enhanced by appropriately combining it with index assignment methods. We pose the corresponding joint optimization problem and suggest a simple iterative algorithm for finding a locally optimal solution. The susceptibility of the solution to poor local minima is significantly reduced by an enhanced version of the algorithm which invokes the method of noisy channel relaxation whereby the VQ system is optimized while gradually decreasing the assumed level of channel noise. In a series of experiments, the resulting combined technique is shown to outperform standard pseudo-Gray coding by up to 3.5 dB and to exhibit graceful degradation at mismatched channel conditions. Finally, we extend these ideas to the case where both the transmitter and the receiver have information on the current state of a time-varying channel. The proposed method is based on switched encoding and adaptive decoding. Experimental results show that the proposed system achieves close to optimal performance     

A combined soft-decision deinterleaver/decoder for the IS95 reverselink

The reverse link encoding steps of the IS95 cellular code-division multiple-access (CDMA) standard consist of convolutional encoding, block interleaving, and orthogonal Walsh function encoding. Deinterleaving individual symbol metrics obtained from the Walsh function matched filters followed by conventional Viterbi decoding produces suboptimal results, as unwanted intersymbol Walsh function correlation is introduced. We propose a combined deinterleaver/decoder with improved performance over existing decoders with little added overhead and no extra decoding delay. Applied to the IS95 reverse link, the proposed decoder has about 1.0-dB gain over soft-decision decoding with interleaved symbol metrics at a bit error rate (BER) of 10^-3     

Universal decoding for memoryless Gaussian channels with adeterministic interference

A universal decoding procedure is proposed for memoryless Gaussian channels with deterministic interfering signals from a certain class. The proposed decoder is universal in the sense that it is independent of the channel parameters and the unknown interfering signal, and, at the same time, attains the same random coding error exponent as the optimal maximum likelihood (ML) decoder, which utilizes full knowledge of the channel parameters and the interfering signal. The proposed decoding rule can be regarded as a continuous-alphabet version of the universal maximum mutual information decoder     

Prefiltered space-time M-BCJR equalizer for frequency-selectivechannels

This paper addresses the problem of soft equalization for space-time-coded transmissions over frequency-selective fading channels. The structure of the space-time code is embedded in the channel impulse response for efficient joint equalization and decoding. The proposed equalization/decoding approach uses a prefilter to concentrate the effective channel power in a small number of taps followed by a reduced-complexity maximum a posteriori probability (MAP) equalizer/decoder to produce soft decisions. The prefilter introduces residual intersymbol interference which degrades the performance of MAP when applied to the trellis of the shortened channel. However, the shape of the overall shortened channel impulse response allows the M-algorithm to approximate the prefiltered MAP performance with a small number of states. Based on this general framework, we investigate several enhancements such as using different prefilters for the forward and backward recursions, concatenating two trellis steps during decoding, and temporal oversampling. The performance is evaluated through simulations over the EDGE typical urban channel     

Iterative joint source-channel decoding of variable-length codes using residual source redundancy

We present a novel symbol-based soft-input a posteriori probability (APP) decoder for packetized variable-length encoded source indexes transmitted over wireless channels where the residual redundancy after source encoding is exploited for error protection. In combination with a mean-square or maximum APP estimation of the reconstructed source data, the whole decoding process is close to optimal. Furthermore, solutions for the proposed APP decoder with reduced complexity are discussed and compared to the near-optimal solution. When, in addition, channel codes are employed for protecting the variable-length encoded data, an iterative source-channel decoder can be obtained in the same way as for serially concatenated codes, where the proposed APP source decoder then represents one of the two constituent decoders. The simulation results show that this iterative decoding technique leads to substantial error protection for variable-length encoded correlated source signals, especially, when they are transmitted over highly corrupted channels.     

On the universality of the LZ-based decoding algorithm

A universal decoder for a family of channels is a decoder that can be designed without prior knowledge of the particular channel in the family over which transmission takes place, and it yet attains the same random-coding error exponent as the optimal decoder tuned to the channel in use. We study Ziv's (1985) decoding algorithm, which is based on Lempel-Ziv (1978) incremental string parsing, and demonstrate that while it was originally proposed as a universal decoder for the family of finite-state channels with deterministic (but unknown) transitions, it is in fact universal for the broader class of all finite-state channels. We also demonstrate that the generalized likelihood decoder may not be universal even for finite families for which a universal decoder always exists     

Soft-decision COVQ for turbo-coded AWGN and Rayleigh fadingchannels

A robust soft-decision channel-optimized vector quantization (COVQ) scheme for turbo coded additive white Gaussian noise (AWGN) and Rayleigh fading channels is proposed, The log likelihood ratio (LLR) generated by the turbo decoder is exploited via the use of a q-bit scalar soft-decision demodulator. The concatenation of the turbo encoder, modulator, AWGN channel or Rayleigh fading channel, turbo decoder, and q-bit soft-decision demodulator is modeled as an expanded discrete memoryless channel (DMC). A COVQ scheme for this expanded discrete channel is designed. Numerical results indicate substantial performance improvements over traditional tandem coding systems, COVQ schemes designed for hard-decision demodulated turbo coded channels (q=1), as well as performance gains over a recent soft decoding COVQ scheme by Ho (see IEEE Commun. Lett., vol.3, p.208-10, 1999)