Potential for improved performance through joint detection of multiuser signals, coupled with associated challenges in achieving this potential at affordable receiver complexity, has motivated significant amount of research to be carried out in the area of multiuser detection (MUD) in the past two decades. Much of the early research in this important area has been centered around systems employing code division multiple access (CDMA) promising capacity improvement in terms of the number of simultaneous users supported in the system. The optimum MUD complexity, which is exponential in the number of users, has inspired a considerable effort toward the development of low-complexity, suboptimal alternatives capable of resolving the detrimental effects of multiple-access interference. Interference cancellation strategies have received particular attention, due to their competitive performance at low complexity and simple modular structure. Their performances, however, are still far from the optimum maximum-likelihood (ML) performance. Iterative methods based on soft-decision cancellation have been shown to achieve near-ML performance. Since most practical communication systems use coding, iterative multiuser decoding of coded CDMA signals has received considerable research attention, and so has the topic of joint multiuser channel estimation and decoding.
展开▼
