On dualizing trellis-based APP decoding algorithms

The trellis of a finite Abelian group code is locally (i.e., trellis section by trellis section) related to the trellis of the corresponding dual group code which allows one to express the basic operations of the a posteriori probability (APP) decoding algorithm (defined on a single trellis section of the primal trellis) in terms of the corresponding dual trellis section. Using this local approach, any algorithm employing the same type of operations as the APP algorithm can, thus, be dualized, even if the global dual code does not exist (e.g., nongroup codes represented by a group trellis). Given this, the complexity advantage of the dual approach for high-rate codes can be generalized to a broader class of APP decoding algorithms, including suboptimum algorithms approximating the true APP, which may be more attractive in practical applications due to their reduced complexity. Moreover, the local approach opens the way for mixed approaches where the operations of the APP algorithm are not exclusively performed on the primal or dual trellis. This is inevitable if the code does not possess a trellis consisting solely of group trellis sections as, e.g., for certain terminated group or ring codes. The complexity reduction offered by applying dualization is evaluated. As examples, we give a dual implementation of a suboptimum APP decoding algorithm for tailbiting convolutional codes, as well as dual implementations of APP algorithms of the sliding-window type. Moreover, we evaluate their performance for decoding usual tailbiting codes or convolutional codes, respectively, as well as their performance as component decoders in iteratively decoded parallel concatenated schemes.     

On the Viterbi decoding algorithm

A new interpretation of the Viterbi decoding algorithm based on the state-space approach to dyamical systems is presented. In this interpretation the optimum decoder solves a generalized regulator control problem by dynamic programming techniques.     

On the decoding of algebraic-geometric codes

A decoding algorithm for algebraic-geometric codes arising from arbitrary algebraic curves is presented. This algorithm corrects any number of errors up to [(d-g-1)/2], where d is the designed distance of the code and g is the genus of the curve. The complexity of decoding equals σ(n³) where n is the length of the code. Also presented is a modification of this algorithm, which in the case of elliptic and hyperelliptic curves is able to correct [(d-1)/2] errors. It is shown that for some codes based on plane curves the modified decoding algorithm corrects approximately d/2-g/4 errors. Asymptotically good q-ary codes with a polynomial construction and a polynomial decoding algorithm (for q⩾361 on some segment their parameters are better than the Gilbert-Varshamov bound) are obtained. A family of asymptotically good binary codes with polynomial construction and polynomial decoding is also obtained, whose parameters are better than the Blokh-Zyablov bound on the whole interval 0<σ<1/2     

On the capacity loss due to separation of detection and decoding

The performance loss due to separation of detection and decoding on the binary-input additive white Gaussian noise (AWGN) channel is quantified in terms of mutual information. Results are reported for both the code-division multiple-access (CDMA) channel in the large system limit and the intersymbol interference (ISI) channel. The results for CDMA rely on the replica method developed in statistical mechanics. It is shown that a previous result of Shamai and Verdu found for Gaussian input alphabet holds also for binary input alphabets. For the ISI channel, the performance loss is calculated via the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. Comparisons are made to the capacity of separate detection and decoding using suboptimum detectors such as a decision-feedback equalizer.     

A low latency SISO with application to broadband turbo decoding

The standard algorithm for computing the soft-inverse of a finite-state machine [i.e., the soft-in/soft-out (SISO) module] is the forward-backward algorithm. These forward and backward recursions can be computed in parallel, yielding an architecture with latency 𝒪(N), where N is the block size. We demonstrate that the standard SISO computation may be formulated using a combination of prefix and suffix operations. Based on well-known tree-structures for fast parallel prefix computations in the very large scale integration (VLSI) literature (e.g., tree adders), we propose a tree-structured SISO that has latency 𝒪(log₂N). The decrease in latency comes primarily at a cost of area with, in some cases, only a marginal increase in computation. We discuss how this structure could be used to design a very high throughput turbo decoder or, more generally, an iterative detector. Various subwindowing and tiling schemes are also considered to further improve latency     

On decoding of Reed-Solomon codes

It is shown how nonsystematic Reed-Solomon (RS) codes encoded by means of the Chinese remainder theorem can be decoded using the Berlekamp algorithm. The Chien search and calculation of error values are not needed but are replaced by a polynomial division and added calculation in determining the syndrome. It is shown that for certain cases of low-rate RS codes, the total decoding computation may be less than the usual method used with cyclic codes. Encoding and decoding for shorter length codes is presented.     

On the iterative decoding of multilevel codes

Iterative decoding of multilevel coded modulation is discussed. Despite its asymptotic optimality with proper design, the error correcting capability of multilevel codes may not be fully exploited for finite block length with conventional multistage decoding. This fact stems from the suboptimality of multistage decoding giving rise to increased error multiplicity at lower index stages and the associated error propagation to higher stages. Such problems can be overcome in many situations by introducing iterative decoding which often significantly compensates the suboptimality of a staged decoder. The class of multilevel codes achieving practically important bit-error performance near the Shannon limit becomes far wider with iterative decoding     

移动图书馆APP应用的探讨

随着信息技术的迅速发展和移动设备的广泛普及,越来越多的图书馆开通了移动图书馆服务,移动图书馆APP的推广与应用也相应增加。分析了当前我国移动图书馆APP的应用现状,指出存在的问题,并提出建立通用移动图书馆APP系统的建议。     

Joint source-channel decoding for variable-length encoded data byexact and approximate MAP sequence estimation

Joint source-channel decoding based on residual source redundancy is an effective paradigm for error-resilient data compression. While previous work only considered fixed-rate systems, the extension of these techniques for variable-length encoded data was independently proposed by the authors and by Demir and Sayood (see Proc. Data Comp. Conf., Snowbird, UT, p.139-48, 1998). We describe and compare the performance of a computationally complex exact maximum a posteriori (MAP) decoder, its efficient approximation, an alternative approximate decoder, and an improved version of this decoder are suggested. Moreover, we evaluate several source and channel coding configurations. The results show that our approximate MAP technique outperforms other approximate methods and provides substantial error protection to variable-length encoded data     

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     

蒙特卡罗法在数字调频信号解码中的应用

通过混有强线性调频干扰信号的数字调频信号进行解码的方案,应用蒙特卡罗法模拟仿真采估计该解码方法的误码率,并且进行了讨论分析.使用随机抽样统计来估算数学函教的计算方法,它需要一个良好的随机教源在数字通信中,对于一个混有强线性调频干扰信号的数字调频信号进行解码.     

浅谈变电站综合自动化到数字化的过渡

本文从变电站远动技术发展史角度阐述笔者对目前综合自动化工作的一些感想,并设想了数字化变电站的发展远景。     

On list sequence turbo decoding

An algorithm for decoding Turbo codes that combines conventional Turbo decoding and list sequence maximum a posteriori probability decoding is presented and evaluated. Compared to previous results on this theme, performance improvements in the order of 0.7 dB are obtained for Turbo codes with 514-b pseudorandom interleaving at a frame error rate of 10/sup -4/ on the additive white Gaussian noise channel.     

短波数字电台PACTOR协议解码的研究与实现

HF数字通信电台协议识别与分析作为现代通信对抗和无线电监测的一项关键技术,受到越来越多的重视。通过基于滑动窗口的协议数据解码算法,根据协议的coding方式,利用VC++和MySQL数据库平台,对短波电台PACTOR协议进行了解码分析和验证。     

数字调制下的极化码译码性能分析

在研究了针对极化码而提出的连续删除列表译码原理的基础上,探讨了在常用数字调制下极化码译码性能。通过Matlab完成多种调制系统下的仿真,并对它们进行比较、分析,以便理解其优缺点及适用场合,实验结果表明,上述调制方式以较低的代价在不同程度上改进了极化码的译码性能,为后续的应用研究提供参考。     

On turbo decoding of nonbinary codes

Symbol-by-symbol maximum a posteriori (MAP) decoding algorithms for nonbinary block and convolutional codes over an extension field GF(p ^a) are presented. Equivalent MAP decoding rules employing the dual code are given which are computationally more efficient for high-rate codes. It is shown that these algorithms meet all requirements needed for iterative decoding as the output of the decoder can be split into three independent estimates: soft channel value, a priori term and extrinsic value. The discussed algorithms are then applied to a parallel concatenated coding scheme with nonbinary component codes in conjunction with orthogonal signaling     

React Native在APP开发中的应用研究

目前,APP开发是移动互联网发展的重要内容,进行移动开发的方法也非常的多,如IOS,Android。文章介绍了一种新型的开发框架—React Native,用Java语言就能同时编写IOS,Android以及后台应用程序。相对传统开发方式,这种方式更加简单、便捷,且学习成本低廉。     

Polynomial-complexity noncoherent symbol-by-symbol detection with application to adaptive iterative decoding of turbo-like codes

The problem of generating symbol-by-symbol soft decision metrics (SbSSDMs) in the presence of unknown channel parameters is considered. The motivation for this work lies in its application to iterative decoding of high-performance turbo-like codes, transmitted over channels that introduce unknown parameters in addition to Gaussian noise. Traditional methods for the exact evaluation of SbSSDMs involve exponential complexity in the sequence length. A class of problems is identified for which the SbSSDMs can be exactly evaluated with only polynomial complexity with respect to the sequence length. Utilizing the close connection between symbol-by-symbol and sequence detection, it is also shown that for the aforementioned class of problems, detection of an uncoded data sequence in the presence of unknown parameters can be performed with polynomial complexity. The applicability of this technique is demonstrated by considering the problem of iterative detection of low-density parity-check codes in the presence of unknown and time-varying carrier-phase offset. Finally, based on the proposed exact schemes, an ultra-fast approximate algorithm for performing joint iterative decoding and phase estimation is derived that is well suited for hardware implementation.     

Using equalizers to offset the deterioration in SCM videotransmission due to fiber dispersion and EDFA gain tilt

The carrier-to-noise ratio (CNR) and distortion of a 1.55 μm amplitude-modulated subcarrier-multiplexed (AM-SCM) video transmission system are worsened by the dispersion of the 1.3 μm zero-dispersion fiber. Distortion is also increased by the EDFA gain tilt. Both problems are shown to be corrected by the use of dispersion equalizers and gain tilt equalizers. The application of the equalizers to SCM video transmission systems is proposed     

Joint encoding and decoding methods for digital audio broadcasting of multiple programs

We introduce new methods for increasing the performance of multiprogram digital audio broadcast systems, e.g., satellite digital audio broadcasting. Joint multiprogram encoding is an attractive possibility for parallel broadcasting of a large number of programs. Joint coding extended over multiple audio frames in time give further improvements. The benefits of this kind of statistical multiplexing yield improved audio quality and/or higher capacity in terms of number of programs. We describe the new Joint Multiple Program Encoding Technique in the context of the perceptual audio coding (PAC) type of algorithms. We also describe methods for multi-program transmission including Equal Error Protection (EEP) as well as Unequal Error Protection (UEP) and improved error concealment for multiple program transmission. Some of the techniques described in this paper, are currently being used in satellite digital audio broadcasting in the United States.