The Research On Soft Decision Decoding Techniques Of Reed-Solomon Codes

RS(Reed-Solomon)code is important linear block codesin error control field.Because of its superior error correction capability,it is widely used in various error control system to meet requirements of the reliability of data transmission channels.This thesis is mainly on the soft decision decoding of RS codes. Firstly, we systemically introduce recent soft decision decoding algorithms, such as algebraic soft decision decoding (ASD) algorithm proposed by Koetter and Vardy, adaptive belief propagation(ABP) algorithm proposed by Jing Jiang and Narayanan and concatenated algorithm proposed by Mostafa and McEliece.After this, we will switch our research to concatenation SDD decoding algorithms of RS code which can provide better performance than non-concatenated SDD. Enlightened by those existed algorithms, Multiple biases based on box and match decoding algorithm (BMA), are applied to the soft decision decoding of Reed-Solomon (RS) codes, which is termed BIAS-BMA. And the simulations are given. We compare its decoding performance with BMA, ABP and KV. The simulation results show that BIAS-BMA has a better performance over BMA, ABP and KV.Moreover, Moreover we propose a symbol-based belief propagation(BP)algorithm for iterative soft decision decoding of Reed-Solomon(RS)codes.Complexity reduction is achieved by using a fast Fourier transform(FFT) based BP algorithm. Parity-check matrix adaptation based on the reliability of the codeword symbols is an essential step to make the BPalgorithm effective on high-density parity-check matrices characteristic of RS codes.The matrix adaptation,as well as all other operations, is performed at symbol level such that bit-to-symbol and symbol-to-bit conversions are avoided. A moderate coding gain over algebraic hard-decision decoding is achieved on additive white Gaussian noise channels.