SigSag: Iterative detection through soft message-passing

The multiple-access framework of ZigZag decoding is a useful technique for combating interference via multiple repeated transmissions, and is known to be compatible with distributed random access protocols. However, in the presence of noise this type of decoding can magnify errors, particularly when packet sizes are large. We present a simple soft-decoding version, called SigSag, that improves performance. We show that for two users, collisions result in a cycle-free factor graph that can be optimally decoded via belief propagation. For collisions between more than two users, we show that if a simple bit-permutation is used then the graph is locally tree-like with high probability, and hence belief propagation is near optimal. Through simulations we show that our scheme performs better than coordinated collision-free time division multiple access (TDMA) and the ZigZag decoder.