Iterative Maximum Likelihood Detection for Initial Ranging Process in 802.16 OFDMA Systems

An iterative maximum likelihood detection (IMLD) algorithm is proposed for the contention based orthogonal frequency-division multiple access (OFDMA) initial ranging (IR) process compliant with the IEEE 802.16 specifications. In contrast to the existing successive interference cancellation (SIC) based algorithms, which suffer both the impacts of channel estimation errors as well as uncanceled multiple access interference (MAI), the proposed IMLD cancels the reconstructed MAI from the received signal by iteratively constructing an objective function derived from the EM algorithm. This approach could implement the maximum likelihood detection in an adaptive way with the MAI decreasing over iterations. Theoretical analyses and Cramër-Rao lower bounds (CRLBs) to the accuracy of parameters estimation are also provided. Simulation results show that the IMLD is of quick convergence, and significantly improves the performance of multiuser detection and parameters estimation with lower complexity compared to available algorithms.