MIMO equalization.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.In recent years, space-time block co'des (STBC) for multi-antenna wireless systems have emerged as attractive encoding schemes for wireless communications. These codes provide full diversity gain and achieve good performance with simple receiver structures without the additional increase in bandwidth or power requirements. When implemented over broadband channels, STBCs can be combined with orthogonal frequency division multiplexing (OFDM) or single carrier frequency domain (SC-FD) transmission schemes to achieve multi-path diversity and to decouple the broadband frequency selective channel into independent flat fading channels. This dissertation focuses on the SC-FD transmission schemes that exploit the STBC structure to provide computationally cost efficient receivers in terms of equalization and channel estimation. The main contributions in this dissertation are as follows: • The original SC-FD STBC receiver that bench marks STBC in a frequency selective channel is limited to coherent detection where the knowledge of the channel state information (CSI) is assumed at the receiver. We extend this receiver to a multiple access system. Through analysis and simulations we prove that the extended system does not incur any performance penalty. This key result implies that the SC-FD STBC scheme is suitable for multiple-user systems where higher data rates are possible. • The problem of channel estimation is considered in a time and frequency selective environment. The existing receiver is based on a recursive least squares (RLS) adaptive algorithm and provides joint equalization and interference suppression. We utilize a system with perfect channel state information (CSI) to show from simulations how various design parameters for the RLS algorithm can be selected in order to get near perfect CSI performance. • The RLS receiver has two modes of operation viz. training mode and direct decision mode. In training mode, a block of known symbols is used to make the initial estimate. To ensure convergence of the algorithm a re-training interval must be predefined. This results in an increase in the system overhead. A linear predictor that utilizes the knowled~e of the autocorrelation function for a Rayleigh fading channel is developed. The predictor is combined with. the adaptive receiver to provide a bandwidth efficient receiver by decreasing the training block size.· The simulation results show that the performance penalty for the new system is negligible. • Finally, a new Q-R based receiver is developed to provide a more robust solution to the RLS adaptive receiver. The simulation results clearly show that the new receiver outperforms the RLS based receiver at higher Doppler frequencies, where rapid channel variations result in numerical instability of the RLS algorithm. The linear predictor is also added to the new receiver which results in a more robust and bandwidth efficient receiver

Advanced receivers for distributed cooperation in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato