Multiuser cooperative transmission through superposition modulation based on braid coding

This paper investigates a cooperative transmission scheme for a multi-source single-destination system through signal-superposition-based braid coding. The source nodes take turns to transmit, and each time, a source “overlays” its new data together with (some or all of) what it overhears from its partner(s) using signal superposition, in a way similar to French-braiding the hair. We demonstrate how the resultant braid coding can be effectively employed in M-to-1 data collection networks to achieve progressive cooperation. We analyze two subclasses of braid coding, the nonregenerative and the regenerative cases, and, using the pairwise error probability (PEP) as a figure of merit, derive the optimal weight parameters theoretically for each class. For the regenerative case, a modified Viterbi maximum-likelihood (ML) estimator is proposed, whose complexity is linear to the message length. We compute the (Euclidean) free distance, and identify the memory size that strikes the best balance between performance and complexity. The proposed cooperative framework based on braid coding is general and subsumes several previous superposition modulation-based cooperative schemes as its special case. Simulations confirm the efficiency of the proposed schemes.