PROJECT TITLE:

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

ABSTRACT:

An iterative maximum probability detection (IMLD) algorithm is proposed for the contention based orthogonal frequency-division multiple access (OFDMA) initial ranging (IR) method compliant with the IEEE 802.sixteen specifications. In distinction to the existing successive interference cancellation (SIC) based algorithms, that suffer each the impacts of channel estimation errors furthermore uncanceled multiple access interference (MAI), the proposed IMLD cancels the reconstructed MAI from the received signal by iteratively constructing an objective perform derived from the EM algorithm. This approach could implement the utmost chance detection in an adaptive manner with the MAI decreasing over iterations. Theoretical analyses and Cramër-Rao lower bounds (CRLBs) to the accuracy of parameters estimation also are provided. Simulation results show that the IMLD is of fast convergence, and considerably improves the performance of multiuser detection and parameters estimation with lower complexity compared to available algorithms.


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