Channel Training and Coherent Decodings in Amplify-and-Forward Relay Network

In this paper, channel training and coherent decodings with channel estimation errors are investigated in a relay network with one single-antenna transmitter, two single-antenna relays, and one double-antenna receiver. A two-stage training scheme is proposed to estimate both the relay-receiver and transmitter-relay channels at the receiver. We use distributed space-time coding (DSTC) for data transmission and investigate the effect of channel estimation errors on the diversity. Two coherent decodings are considered: mismatched decoding in which the channel estimations are treated as if perfect, and matched decoding which takes into account the estimation errors. We show that for full diversity, mismatched decoding requires at least 6 symbol intervals for training, while 4 symbol intervals for training are enough for matched decoding. On the other hand, the complexity of matched decoding is much higher. To achieve a balance between performance and complexity, an adaptive decoding scheme is proposed. Simulated network error rates are shown to justify the analytical results.