Design and implementation of a near maximum likelihood decoder for Cortex codes

International audienceThe Cortex codes form an emerging family among the rate-1/2 self-dual systematic linear block codes with good distance properties. This paper investigates the challenging issue of designing an efficient Maximum Likelihood (ML) decoder for Cortex codes. It first reviews a dedicated architecture that takes advantage of the particular structure of this code to simplify the decoding. Then, we propose a technique to improve the architecture by the generation of an optimal list of binary vectors. An optimal stopping criterion is also proposed. Simulation results show that the proposed architecture achieves an excellent performance/complexity trade-off for short Cortex codes. The proposed decoder architecture has been implemented on an FPGA device for the (24,12,8) Cortex code. This implementation supports an information throughput of 225 Mb/s. At a signal-tonoise ratio Eb/No=8 dB, the Bit Error Rate equals 2 × 10^−10, which is close to the performance of the Maximum Likelihood decoder

Viterbi Decoded Linear Block Codes for Narrowband and Wideband Wireless Communication Over Mobile Fading Channels

Since the frantic race towards the Shannon bound [1] commenced in the early 1950’s, linear block codes have become integral components of most digital communication systems. Both binary and non-binary linear block codes have proven themselves as formidable adversaries against the impediments presented by wireless communication channels. However, prior to the landmark 1974 paper [2] by Bahl et al. on the optimal Maximum a-Posteriori Probability (MAP) trellis decoding of linear block codes, practical linear block code decoding schemes were not only based on suboptimal hard decision algorithms, but also code-specific in most instances. In 1978 Wolf expedited the work of Bahl et al. by demonstrating the applicability of a block-wise Viterbi Algorithm (VA) to Bahl-Cocke-Jelinek-Raviv (BCJR) trellis structures as a generic optimal soft decision Maximum-Likelihood (ML) trellis decoding solution for linear block codes [3]. This study, largely motivated by code implementers’ ongoing search for generic linear block code decoding algorithms, builds on the foundations established by Bahl, Wolf and other contributing researchers by thoroughly evaluating the VA decoding of popular binary and non-binary linear block codes on realistic narrowband and wideband digital communication platforms in lifelike mobile environments. Ideally, generic linear block code decoding algorithms must not only be modest in terms of computational complexity, but they must also be channel aware. Such universal algorithms will undoubtedly be integrated into most channel coding subsystems that adapt to changing mobile channel conditions, such as the adaptive channel coding schemes of current Enhanced Data Rates for GSM Evolution (EDGE), 3rd Generation (3G) and Beyond 3G (B3G) systems, as well as future 4th Generation (4G) systems. In this study classic BCJR linear block code trellis construction is annotated and applied to contemporary binary and non-binary linear block codes. Since BCJR trellis structures are inherently sizable and intricate, rudimentary trellis complexity calculation and reduction algorithms are also presented and demonstrated. The block-wise VA for BCJR trellis structures, initially introduced by Wolf in [3], is revisited and improved to incorporate Channel State Information (CSI) during its ML decoding efforts. In order to accurately appraise the Bit-Error-Rate (BER) performances of VA decoded linear block codes in authentic wireless communication environments, Additive White Gaussian Noise (AWGN), flat fading and multi-user multipath fading simulation platforms were constructed. Included in this task was the development of baseband complex flat and multipath fading channel simulator models, capable of reproducing the physical attributes of realistic mobile fading channels. Furthermore, a complex Quadrature Phase Shift Keying (QPSK) system were employed as the narrowband communication link of choice for the AWGN and flat fading channel performance evaluation platforms. The versatile B3G multi-user multipath fading simulation platform, however, was constructed using a wideband RAKE receiver-based complex Direct Sequence Spread Spectrum Multiple Access (DS/SSMA) communication system that supports unfiltered and filtered Complex Spreading Sequences (CSS). This wideband platform is not only capable of analysing the influence of frequency selective fading on the BER performances of VA decoded linear block codes, but also the influence of the Multi-User Interference (MUI) created by other users active in the Code Division Multiple Access (CDMA) system. CSS families considered during this study include Zadoff-Chu (ZC) [4, 5], Quadriphase (QPH) [6], Double Sideband (DSB) Constant Envelope Linearly Interpolated Root-of- Unity (CE-LI-RU) filtered Generalised Chirp-like (GCL) [4, 7-9] and Analytical Bandlimited Complex (ABC) [7, 10] sequences. Numerous simulated BER performance curves, obtained using the AWGN, flat fading and multi-user multipath fading channel performance evaluation platforms, are presented in this study for various important binary and non-binary linear block code classes, all decoded using the VA. Binary linear block codes examined include Hamming and Bose-Chaudhuri-Hocquenghem (BCH) codes, whereas popular burst error correcting non-binary Reed-Solomon (RS) codes receive special attention. Furthermore, a simple cyclic binary linear block code is used to validate the viability of employing the reduced trellis structures produced by the proposed trellis complexity reduction algorithm. The simulated BER performance results shed light on the error correction capabilities of these VA decoded linear block codes when influenced by detrimental channel effects, including AWGN, Doppler spreading, diminished Line-of-Sight (LOS) signal strength, multipath propagation and MUI. It also investigates the impact of other pertinent communication system configuration alternatives, including channel interleaving, code puncturing, the quality of the CSI available during VA decoding, RAKE diversity combining approaches and CSS correlation characteristics. From these simulated results it can not only be gathered that the VA is an effective generic optimal soft input ML decoder for both binary and non-binary linear block codes, but also that the inclusion of CSI during VA metric calculations can fortify the BER performances of such codes beyond that attainable by classic ML decoding algorithms.Dissertation (MEng(Electronic))--University of Pretoria, 2006.Electrical, Electronic and Computer Engineeringunrestricte

QPSK Block-Modulation Codes for Unequal Error Protection

Unequal error protection (UEP) codes find applications in broadcast channels, as well as in other digital communication systems, where messages have different degrees of importance. Binary linear UEP (LUEP) codes combined with a Gray mapped QPSK signal set are used to obtain new efficient QPSK block-modulation codes for unequal error protection. Several examples of QPSK modulation codes that have the same minimum squared Euclidean distance as the best QPSK modulation codes, of the same rate and length, are given. In the new constructions of QPSK block-modulation codes, even-length binary LUEP codes are used. Good even-length binary LUEP codes are obtained when shorter binary linear codes are combined using either the well-known |u¯|u¯+v¯|-construction or the so-called construction X. Both constructions have the advantage of resulting in optimal or near-optimal binary LUEP codes of short to moderate lengths, using very simple linear codes, and may be used as constituent codes in the new constructions. LUEP codes lend themselves quite naturally to multistage decoding up to their minimum distance, using the decoding of component subcodes. A new suboptimal two-stage soft-decision decoding of LUEP codes is presented and its application to QPSK block-modulation codes for UEP illustrated

Coding for Parallel Channels: Gallager Bounds for Binary Linear Codes with Applications to Repeat-Accumulate Codes and Variations

This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error probability are derived. These bounds are applied to various ensembles of turbo-like codes, focusing especially on repeat-accumulate codes and their recent variations which possess low encoding and decoding complexity and exhibit remarkable performance under iterative decoding. The framework of the second version of the Duman and Salehi (DS2) bounds is generalized to the case of parallel channels, along with the derivation of their optimized tilting measures. The connection between the generalized DS2 and the 1961 Gallager bounds, addressed by Divsalar and by Sason and Shamai for a single channel, is explored in the case of an arbitrary number of independent parallel channels. The generalization of the DS2 bound for parallel channels enables to re-derive specific bounds which were originally derived by Liu et al. as special cases of the Gallager bound. In the asymptotic case where we let the block length tend to infinity, the new bounds are used to obtain improved inner bounds on the attainable channel regions under ML decoding. The tightness of the new bounds for independent parallel channels is exemplified for structured ensembles of turbo-like codes. The improved bounds with their optimized tilting measures show, irrespectively of the block length of the codes, an improvement over the union bound and other previously reported bounds for independent parallel channels; this improvement is especially pronounced for moderate to large block lengths.Comment: Submitted to IEEE Trans. on Information Theory, June 2006 (57 pages, 9 figures

Low-density MDS codes and factors of complete graphs

We present a class of array code of size n×l, where l=2n or 2n+1, called B-Code. The distances of the B-Code and its dual are 3 and l-1, respectively. The B-Code and its dual are optimal in the sense that i) they are maximum-distance separable (MDS), ii) they have an optimal encoding property, i.e., the number of the parity bits that are affected by change of a single information bit is minimal, and iii) they have optimal length. Using a new graph description of the codes, we prove an equivalence relation between the construction of the B-Code (or its dual) and a combinatorial problem known as perfect one-factorization of complete graphs, thus obtaining constructions of two families of the B-Code and its dual, one of which is new. Efficient decoding algorithms are also given, both for erasure correcting and for error correcting. The existence of perfect one-factorizations for every complete graph with an even number of nodes is a 35 years long conjecture in graph theory. The construction of B-Codes of arbitrary odd length will provide an affirmative answer to the conjecture