Local Maximum Likelihood Multiuser Detection for CDMA Communications

Third-generation mobile radio networks have been under intense research. Code division multiple access (CDMA) has emerged as the mainstream air interface solution for the third-generation networks. As the demand of usable bandwidth is ever increasing, multiuser detection is a necessary means for CDMA systems to reduce effect of multiple access interference and hence increase system capacity. The global maximum likelihood (GML) multiuser detector achieves the minimum error probability of joint user detection as well as optimum near-far resistance. However, the complexity of the GML detector grows exponentially with the number of users and is infeasible for practical systems. There have been many suboptimum multiuser detectors each achieving some performance-complexity tradeoff. However, none of them achieves a local maximum likelihood (LML) solution with an arbitrary neighborhood size. Moreover, most of the existing suboptimum multiuser detectors are ad hoc developed. They have low ratio of performance to computational complexity. In this project, we will develop local maximum likelihood detectors with an arbitrary neighborhood size. These LML multiuser detectors can provide a broad spectrum of performance-complexity tradeoff. Their error performance spans from that comparable to the conventional detector, MMSE receiver, MMSE-DF receiver, superior to MMSE-DF receiver, etc., up to that of the GML detector and their computational complexity spans from linear, quadratic, etc., up to exponential in the number of users. Furthermore, these LML multiuser detectors achieve high ratio of performance to computational complexity as demonstrated in preliminary simulations. Specifically, we will develop a family of linear-complexity likelihood ascent search (LAS) multiuser detectors in some combinations of the following conditions: wireless multipath fading channels, on-the-move (Doppler), known and unknown interference users (group blind), broadband and multirate data, power control, adaptive modulation, turbo coded data, space-time coding, and large systems in CDMA networks with direct sequence, frequency hopping, and multicarrier modulation. Another family of local maximum likelihood LAS (LMLAS) multiuser detectors achieving LML detection with an arbitrary neighborhood size will also be developed in the above various cases. The both families of LAS and LMLAS detectors with soft intermediate decision will be investigated. We will study strategies to determine the optimum order of bit update. Performance analysis will include the characterization of local maximum likelihood points with an arbitrary neighborhood size, the dynamical stability, monotonic likelihood ascent characterization, expected computational complexity, error probability, asymptotic multiuser efficiency, near-far resistance, optimum power control, and spectral efficiency. The proposed investigation on LML detection will impact basic research in nonlinear signal processing for multiuser communications, and is expected to benefit directly applications to third and fourthgeneration wireless mobile communications systems. This project will also contribute new knowledge to theories of the fields of multiuser detection, hypothesis testing, wireless communications, image processing, and neural networks. This project will help set up a strong program in communications in this department and provide new research opportunities for both graduate and undergraduate students, and in particular the minority students. The increased minority students’ research activities in modern communications will strengthen the traditional diversity environment of this collage.