Cooperative communications based on trellis pruning

This paper introduces a new approach to cooperative communications. Consider a system wherein two partner nodes cooperate to convey their data to a common destination, each not only transmitting its own “local” data but also acting as a relay for its partner, thereby effecting spatial diversity. In the proposed scheme, each partner interleaves local data with relayed data and convolutionally encodes the resulting interleaved bitstream prior to transmission; the other partner then uses its knowledge of the relayed data to prune edges from the code trellis, thereby decoding at a lower (more robust) rate. The destination observes two versions of each source's data - one transmitted as local information, the other as relayed information - and employs iterative decoding, in effect decoding the data as if it were encoded via a “distributed” turbo code. The resulting performance is superior to those of cooperation schemes based on time sharing and signal space superposition, and it generalizes the algebraic superposition scheme of Xiao et al.