Raptor codes on binary memoryless symmetric channels

In this paper, we will investigate the performance of Raptor codes on arbitrary binary input memoryless symmetric channels (BIMSCs). In doing so, we generalize some of the results that were proved before for the erasure channel. We will generalize the stability condition to the class of Raptor codes. This generalization gives a lower bound on the fraction of output nodes of degree 2 of a Raptor code if the error probability of the belief-propagation decoder converges to zero. Using information-theoretic arguments, we will show that if a sequence of output degree distributions is to achieve the capacity of the underlying channel, then the fraction of nodes of degree 2 in these degree distributions has to converge to a certain quantity depending on the channel. For the class of erasure channels this quantity is independent of the erasure probability of the channel, but for many other classes of BIMSCs, this fraction depends on the particular channel chosen. This result has implications on the "universality" of Raptor codes for classes other than the class of erasure channels, in a sense that will be made more precise in the paper. We will also investigate the performance of specific Raptor codes which are optimized using a more exact version of the Gaussian approximation technique.     

EXIT functions for binary input memoryless symmetric channels

Use of extrinsic information transfer (EXIT) functions, characterizing the amplification of mutual information between the input and output of the maximum a posteriori (MAP) decoder, significantly facilitates analysis of iterative coding schemes. Previously, EXIT functions derived for binary erasure channels (BECs) were used as an approximation for other channels. Here, we improve on this approach by introducing more accurate methods to construct EXIT functions for binary-input memoryless symmetric (BMS) channels. By defining an alternative pseudo-MAP decoder coinciding with the MAP decoder over BEC, we provide an expression for the EXIT functions of block codes over BEC. Furthermore, we draw a connection between the EXIT function over BEC and the EXIT function over the BMS channel under certain conditions. This is used for deriving accurate or approximate expressions of EXIT functions over BMS channels in certain scenarios.     

Iterative decoding of low-density Parity-check codes over compound channels

We present a setting for decoding of low-density parity-check (LDPC) codes jointly with channel estimation, which is suitable for transmission over memoryless compound channels. We show that the performance of the combined scheme can be rigorously evaluated by means of density evolution, and focus on density evolution as a tool for designing a channel estimator that matches not only to the channel, but also to the LDPC ensemble, as well. The utility of the concept is exemplified for a compound binary symmetric channel and an unknown phase additive white Gaussian channel.     

Turbo codes for nonuniform memoryless sources over noisy channels

This work addresses the problem of designing turbo codes for nonuniform binary memoryless or independent and identically distributed (i.i.d.) sources over noisy channels. The extrinsic information in the decoder is modified to exploit the source redundancy in the form of nonuniformity; furthermore, the constituent encoder structure is optimized for the considered nonuniform i.i.d. source to further enhance the system performance. Some constituent encoders are found to substantially outperform Berrou's (1996) (37, 21) encoder. Indeed, it is shown that the bit error rate (BER) performance of the newly designed turbo codes is greatly improved as significant coding gains are obtained     

An analytical method for approximate performance evaluation of binary linear block codes

An analytical method for approximate performance evaluation of binary linear block codes using an additive white Gaussian noise channel model with binary phase-shift keying modulation is presented. We focus on the probability density function of the bit log-likelihood ratio (LLR), which is expressed in terms of the Gram-Charlier series expansion. This expansion requires knowledge of the statistical moments of the bit LLR. We introduce an analytical method for calculating these moments. This is based on some recursive calculations involving certain weight enumerating functions of the code. It is proved that the approximation can be as accurate as desired, if we use enough terms in the Gram-Charlier series expansion. Numerical results are provided for some examples, which demonstrate close agreement with simulation results.     

Comparison of decoding algorithms of binary linear block codes inRayleigh fading channels with diversity reception

The word error probability of binary linear block codes is evaluated in Rayleigh fading channels with diversity reception for three decoding algorithms: error correction (EC), error/erasure correction (EEC), and maximum likelihood (ML) soft decoding algorithms. The performance advantage of EEC over EC in the required average SNR decreases as the number of diversity channels increases. The performance advantage of EEC over EC does not depend on the specific value of word error probability although the advantage of ML soft decoding over EC increases for lower word error probability     

Some new results on binary linear block codes

Certain properties of the parity-check matrix H of (n, k) linear codes are used to establish a computerised search procedure for new binary linear codes. Of the new error-correcting codes found by this procedure, two codes were capable of correcting up to two errors, three codes up to three errors, four codes up to four errors and one code up to five errors. Two meet the lower bound given by Helgert and Stinaff, and seven codes exceed it. In addition, one meets the upper bound. Of the even-Hamming-distance versions of these codes, eight meet the upper bound, and the remaining two exceed the lower bound.     

Decoding binary block codes onQ-ary output channels

This paper presents an algebraic technique for decoding binary block codes in situations where the demodulator quantizes the received signal space intoQ > 2regions. The method, referred to as weighted erasure decoding (WED), is applicable in principle to any block code for which a binary decoding procedure is known.     

Compression of binary memoryless sources using punctured turbo codes

In this letter, we propose the use of punctured turbo codes to perform near-lossless compression and joint source-channel coding of binary memoryless sources. Compression is achieved by puncturing the turbo code to the desired rate. No information about the source distribution is required in the encoding process. Moreover, the source parameters do not need to be known in the decoder, since they can be estimated jointly with the iterative decoding process.     

衰落信道上空频分组码的性能分析

对于任意抽头数的多输入多输出(MIMO)频率选择性Nakagami衰落信道,利用矩生成函数(MGF)方法和高斯Q函数的指数近似表达式,推导采用矩形M进制正交幅度调制(MQAM)的空频分组编码(SFBC)正交频分复用(OFDM)系统的平均误符号率(SER)性能的精确和近似解析表达式。数值计算和仿真结果证明了理论分析的正确性和近似分析的准确性。     

频率选择信道下的空时分组码盲识别

在单接收天线下,针对频率选择性衰落信道下空时分组码( STBC)的盲识别问题,提出了一种基于Kolmogorov-Smirnov( K-S)检测的有效算法。该算法以经验累积分布函数作为特征函数,通过K-S检测经验累积分布函数之间的距离,达到识别空时分组码的目的。在不同调制方式、采样因子和置信区间的条件下分别对算法进行仿真并讨论其性能,结果表明,该算法性能较好,在信噪比大于6 dB时可达到90%以上的正确识别概率,在非合作通信方面具有一定的实用价值。     

On the Voronoi neighbor ratio for binary linear block codes

Soft-decision decoding of block codes is regarded as the geometrical problem of identifying the Voronoi region within which a given input vector lies. A measure, called the neighbor ratio, is proposed to characterize how many facets a Voronoi region has. Theory and algorithms are presented to determine the neighbor ratio for binary linear block codes and results are given for several types of codes. An asymptotic analysis for long codes reveals that the neighbor ratio depends on whether the code rate is less than 1/2 or not. For rates below this threshold, all pairs of codewords tend to share a Voronoi facet; for higher rates, a relatively small fraction of them do     

Waterfall performance analysis of finite-length LDPC codes on symmetric channels

An efficient method for analyzing the performance of finite-length low-density parity-check (LDPC) codes in the waterfall region, when transmission takes place on a memoryless binary-input output-symmetric channel is proposed. This method is based on studying the variations of the channel quality around its expected value when observed during the transmission of a finite-length codeword. We model these variations with a single parameter. This parameter is then viewed as a random variable and its probability distribution function is obtained. Assuming that a decoding failure is the result of an observed channel worse than the code?s decoding threshold, the block error probability of finite-length LDPC codes under different decoding algorithms is estimated. Using an extrinsic information transfer chart analysis, the bit error probability is obtained from the block error probability. Different parameters can be used for modeling the channel variations. In this work, two of such parameters are studied. Through examples, it is shown that this method can closely predict the performance of LDPC codes of a few thousand bits or longer in the waterfall region.     

Decoding of low-density parity-check codes over finite-state binary Markov channels

We propose a modified algorithm for decoding of low-density parity-check codes over finite-state binary Markov channels. The proposed approach clearly outperforms systems in which the channel statistics are not exploited in the decoding, even when the channel parameters are not known a priori at the decoder.     

Error probability for block codes over channels with blockinterference

A methodology is presented to evaluate analytically the error probability for block codes over block interference channels. The proposed analysis is based on the knowledge of the moments of the bit-error probability over the interference, thus allowing, for instance, fast performance evaluation of block-coded slow frequency hopping (SFH) systems with antenna diversity over fading channels. As an example of application, slow frequency hopping multiple access (SFHMA) systems with nonideal interleaving are analyzed in the presence of fading, cochannel interference, and additive Gaussian noise     

Asymptotic performance of space-frequency codes over broadband channels

We show that when the number of receive antennas is large, the Euclidean distance among codewords dominates the performance of space-frequency codes, the same result as for space-time codes. Therefore, in the presence of a large number of receive antennas, space-frequency codes can be optimized by using the Euclidean-distance criterion valid for additive white Gaussian noise channels. Simulation results show that this conclusion is also valid when the number of antennas is small.     

The capacity of binary channels that use linear codes and decoders

This paper analyzes the performance of concatenated coding systems operating over the binary-symmetric channel (BSC) by examining the loss of capacity resulting from each of the processing steps. The techniques described in this paper allow the separate evaluation of codes and decoders and thus the identification of where loss of capacity occurs. They are, moreover, very useful for the overall design of a communications system, e.g., for evaluating the benefits of inner decoders that produce side information. The first two sections of this paper provide a general technique (based on the coset weight distribution of a binary linear code) for calculating the composite capacity of the code and a BSC in isolation. The later sections examine the composite capacities of binary linear codes, the BSC, and various decoders. The composite capacities of the (8,4) extended Hamming, (24, 12) extended Golay, and (48, 24) quadratic residue codes appear as examples throughout the paper. The calculations in these examples show that, in a concatenated coding system, having an inner decoder provide more information than the maximum-likelihood (ML) estimate to an outer decoder is not a computationally efficient technique, unless generalized minimum-distance decoding of an outer code is extremely easy. Specifically, for the (8,4) extended Hamming and (24, 12) extended Golay inner codes, the gains from using any inner decoder providing side information, instead of a strictly ML inner decoder, are shown to be no greater than 0.77 and 0.34 dB, respectively, for a BSC crossover probability of 0.1 or less, However, if computationally efficient generalized minimum distance decoders for powerful outer codes, e.g., Reed-Solomon codes, become available, they will allow the use of simple inner codes, since both simple and complex inner codes have very similar capacity losses     

Soft-decision decoding of binary linear block codes using reducedbreadth-first search algorithms

The article discusses soft-decision decoding of binary linear block codes using the t-algorithm and its variants. New variants of the basic algorithm are presented that reduce the decoding complexity using a threshold adaptive to the signal-to-noise ratio and address the variable decoding complexity by either limiting the memory or using a generalized M-algorithm with a nonconstant state profile