A gradient guided search algorithm for multiuser detection

Abstract

This paper introduces a new multiuser detection algorithm based on a gradient guided search that can achieve near-optimum performance while its implementation complexity is linear in the number of users. The new algorithm attempts to perform jointly optimum multiuser detection by updating one user's bit decision each iteration in the best possible way. When a decorrelating multiuser detector is employed to initialize the proposed algorithm, in all cases tested the gradient guided search converges to a solution with performance very close to optimum. Further, tests indicate that the proposed algorithm provides excellent performance for cases where other suboptimum algorithms perform poorly. Although we focus only on synchronous multiuser detection, the algorithm is equally applicable to asynchronous multiuser detection problems.