The conditional metric merge algorithm for maximum likelihood multiuser-macrodiversity detection

The combination of macrodiversity reception with maximum likelihood (ML) multiuser detection has the capability to reduce the bit error rate (BER) for many users by several orders of magnitude compared with multiuser detectors that operate on each antenna separately. In this paper, we present the conditional metric merge (CMM) algorithm which reduces the computational complexity of the ML multiuser-macrodiversity detector by an enormous factor. The CMM algorithm can be viewed as a spatial variant of the Viterbi algorithm. It is a new algorithm and is the first of its kind as ML multiuser-macrodiversity detection (MUMD) is a relatively new area of research.