A joint ML estimation technique for timing, CFO and channel for OFDMA uplink transmissions

Abstract

This paper addresses the issue of joint maximum-likelihood (ML) estimation of carrier frequency offset (CFO), timing error and channel response for OFDMA uplink transmissions. A pilot preamble-based approach is proposed that makes use of the concept of signal decomposition. Earlier works have demonstrated that it is possible to decompose the multidimensional optimization involved in this joint estimation into a series of one-dimensional searches. The alternating projection (AP) algorithm is effectively used to determine the ML solution to this problem in many earlier works. In this work, we propose a new method of signal decomposition that can be combined with the conventional AP method to arrive at better parameter estimates. It achieves better performance in lesser number of estimation cycles and hence with lesser computational load. Another advantage is that it offers the flexibility of application to any generalized subcarrier assignment scheme in OFDMA systems. The performance advantages of this new method are substantiated through simulation studies.