Evaluation of Word Length Effects on Multistandard Soft Decision Viterbi Decoding

Abstract: There have been proposals of many parity inducing techniques like Forward ErrorCorrection (FEC) which try to cope the problem of channel induced errors to alarge extent if not completely eradicate. The convolutional codes have been widelyidentified to be very efficient among the known channel coding techniques. Theprocess of decoding the convolutionally encoded data stream at the receiving nodecan be quite complex, time consuming and memory inefficient.This thesis outlines the implementation of multistandard soft decision viterbidecoder and word length effects on it. Classic Viterbi algorithm and its variantsoft decision viterbi algorithm, Zero-tail termination and Tail-Biting terminationfor the trellis are discussed. For the final implementation in C language, the "Zero-Tail Termination" approach with soft decision Viterbi decoding is adopted. Thismemory efficient implementation approach is flexible for any code rate and anyconstraint length.The results obtained are compared with MATLAB reference decoder. Simulationresults have been provided which show the performance of the decoderand reveal the interesting trade-off of finite word length with system performance.Such investigation can be very beneficial for the hardware design of communicationsystems. This is of high interest for Viterbi algorithm as convolutional codes havebeen selected in several famous standards like WiMAX, EDGE, IEEE 802.11a,GPRS, WCDMA, GSM, CDMA 2000 and 3GPP-LTE.