Turbo Decoding and Detection for Wireless Applications

A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted

An Iterative Joint Linear-Programming Decoding of LDPC Codes and Finite-State Channels

In this paper, we introduce an efficient iterative solver for the joint linear-programming (LP) decoding of low-density parity-check (LDPC) codes and finite-state channels (FSCs). In particular, we extend the approach of iterative approximate LP decoding, proposed by Vontobel and Koetter and explored by Burshtein, to this problem. By taking advantage of the dual-domain structure of the joint decoding LP, we obtain a convergent iterative algorithm for joint LP decoding whose structure is similar to BCJR-based turbo equalization (TE). The result is a joint iterative decoder whose complexity is similar to TE but whose performance is similar to joint LP decoding. The main advantage of this decoder is that it appears to provide the predictability of joint LP decoding and superior performance with the computational complexity of TE.Comment: To appear in Proc. IEEE ICC 2011, Kyoto, Japan, June 5-9, 201

Turbo codes and turbo algorithms

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding

Serially Concatenated Continuous Phase Modulation with SOVA Turbo Decoding

For a Serially Concatenated Continuous Phase Modulation (SCCPM) system that concatenates a rate of 1/2 Convolutional Code (CC) and an M-ary full response continuous phase modulation (CPM) signal, we design a turbo decoding scheme using the Soft Output Viterbi algorithm (SOVA) and study the system performance. A decomposition model is used in CPM to reduce the number of states and separate the continuous phase encoder (CPE) with the modulator. As a soft-input soft-output (SISO) decoding algorithm, SOVA is used to generate and update the soft information of decoded signal symbols during the iterative process for both the CPM signal and the CC. Newly generated soft information from one component decoder will be used by the other component decoder to constitute an iterative, i.e., turbo, decoding process. Simulation results show that a decoding gain of at least 1 dB can be obtained by using turbo decoding compared to that without turbo decoding