Performance-complexity tradeoff of convolutional codes for broadband fixed wireless access systems

In this study, the authors investigate the performance-complexity tradeoff of convolutional codes for broadband fixed wireless access systems by considering the effects of quantisation and path metric memory in practical Viterbi decoding implementations. They show that in systems with limited antenna diversity, low-memory codes achieve a better error-rate performance compared to that of high-memory codes. Only in systems with considerable antenna diversity, can the performance of a convolutional code be improved by increasing its memory size. Nevertheless, the authors demonstrate that the coding advantage offered by the high-memory codes is not large enough to justify the significant increase in implementation complexity. In particular, memory-2 convolutional codes achieve a coding gain of up to 1.2 dB over their memory-8 counterparts in single-input single-output fixed wireless access systems. The situation is reversed when multiple antennas are used, but the decoder of memory-8 codes occupies at least 130 times more silicon area than that of memory-2 codes