OFDM receiver design with iterative techniques

Abstract

Recent advances in iterative signal processing have allowed communication systems to obtain near optimal performance with manageable complexity. The idea of iteratively exchanging the reliability information among the components within a receiver to improve overall performance is known as the turbo concept or turbo processing. Based on the principle of turbo processing, this thesis investigates the key issues in designing a receiver for high data rate multicarrier wireless systems. The particular focus is on the orthogonal frequency division multiplexing (OFDM) technique which can be potentially targeted for the 4th generation communication systems. The first part of the thesis addresses the primary issues in an OFDM receiver such as channel estimation, carrier frequency offset (CFO) compensation, and decoding. Since the optimal solutions require a high load of computation, iterative algorithms are generally desirable. The soft information from the decoder/detector can be efficiently incorporated into the channel estimator/CFO compensator, which consequently results in better performance of the receiver. The thesis provides a framework of iterative algorithms for OFDM receivers in which the converged performances are close to those of the optimal solutions. In the second part of the thesis, the iterative algorithms for the spatial diversity channels, or in other words, multiple input multiple output (MIMO) channels, are investigated. Together with capacity potential, MIMO channels bring in some new challenges. With a number of antennas on both the transmitting and receiving sides, inter-antenna and co-antenna interference is the arising concern in addition to the conventional intersymbol interference problem. Also, most of the optimal signal processing algorithms within a receiver have complexities which are at least proportionally if not exponentially increasing with the number of antennas. This creates challenges for implementing signal processing algorithms at the receiver. We therefore investigate and design manageable-complexity iterative algorithms for spatial diversity channels. In particular, we develop novel decision feedback detectors for the single user scenario, and then propose a jointly iterative multiuser detection and cell-related interference cancellation scheme for the multiuser scenario. Again, it is verified that the iterative algorithms can be effectively used as near-optimal solutions for OFDM system with spatial diversity channels.