Joint Maximum Likelihood Estimation of Channel and Preamble Sequence for WiMAX Systems

Abstract

This paper examines the detection problem of the preamble sequence index in the WiMAX system. The mobile station receiver knows all the possible preamble sequences and should estimate which preamble sequence has been transmitted from the base station. Since the preamble in the orthogonal frequency division multiplexing (OFDM) transmission is usually the first received symbol, the channel is unknown to the receiver, which makes the problem of preamble sequence estimation complicated. In this paper, this problem is addressed by developing the joint maximum likelihood (ML) estimator of the preamble sequence and the channel. A simple decoupled estimator and a minimum mean square error (MMSE) estimator are also presented as benchmarks for the joint ML estimator. Then it is shown how the joint ML estimator can be used for the segment detection. Since the joint ML estimator can be computationally complex in its general form, low-complexity algorithms are developed depending on the type of pilot subcarrier locations for general OFDM systems including WiMAX. The simulation results show that the joint ML estimator detects the preamble sequence index very well in the absence of the channel knowledge.