Bidirectional decoding of convolutional codes for wide-band TDMA indoor wireless channels

Bidirectional suboptimal breadth-first decoding of convolutional codes is an attractive technique for slowly-varying and quasistatic fading channels as it restricts the extent of decoding errors due to correct path loss to very heavy noise or interference regions. The paper compares the performance of such a decoding scheme to the Viterbi algorithm over wideband TDMA indoor radio links where equalization and space diversity are also used to combat dispersive fading and cochannel interference. It is shown that, with dual space diversity, Viterbi decoding and bidirectional decoding of convolutional codes are both attractive alternatives, in terms of outage rate, to increasing the space diversity order from two to three. On the basis of equal computational complexity, bidirectional decoding is also shown to be superior to Viterbi decoding. Furthermore, this advantage increases as the bit error rate performance criterion becomes more stringent which makes bidirectional decoding particularly attractive for data applications