A Combined Method of Multi-user Detection in Dynamic Environment

In mobile multiple-access communications, not only the location of active users, but also their number varies with time. In typical analysis, multiuser detection theory has been developed under the assumption that the number of active users is constant and known at the receiver, which coincides with the maximum number of users entitled to access the system. This assumption is often overly pessimistic, since many users might be inactive at any given time, and detection under the assumption of the number of users larger than the real one may impair performance. To identify active users and estimating their parameters and data in a random-access system where users are continuously entering and leaving the system, the method based on the combination of random-set theory (RST) and multi-valued particle swarm optimization (PSO) algorithm is proposed. A ternary PSO algorithm is presented firstly. The simulated results of proposed method based on RST and ternary PSO show how joint channel sensing and user demodulation can be advantageous when the number of active users is unknown as a priori.