Iterative detection and frequency synchronization for OFDMA uplink transmissions
The problem of frequency synchronization, channel estimation, and data detection for all active users in the uplink of an OFDMA system is investigated in this work. Since the exact maximum likelihood (ML) solution to this problem turns out to be too complex for practical purposes, we derive an alternative scheme that operates in an iterative fashion. At each step, the superimposed signals arriving at the base station (BS) are separated by means of the space-alternating generalized expectation-maximization (SAGE) algorithm. Each separated signal is then passed to an expectation-conditional maximization (ECM)-based processor that updates frequency estimates and performs channel estimation and data detection for each user. The resulting architecture is reminiscent of the parallel interference cancellation (PIC) receiver, where interference is generated and removed from the received signal to improve the system performance. Simulations indicate that the proposed scheme outperforms other benchmark solutions at the price of increased computational complexity