Efficient Interference Suppression and Resource Allocation in MIMO and DS-CDMA Wireless Networks

Direct-sequence code-divisionmultiple-access (DS-CDMA) and multiple-inputmultipleoutput (MIMO) wireless networks form the physical layer of the current generation of mobile networks and are anticipated to play a key role in the next generation of mobile networks. The improvements in capacity, data-rates and robustness that these networks provide come at the cost of increasingly complex interference suppression and resource allocation. Consequently, efficient approaches to these tasks are essential if the current rate of progression in mobile technology is to be sustained. In this thesis, linear minimum mean-square error (MMSE) techniques for interference suppression and resource allocation in DS-CDMA and cooperative MIMO networks are considered and a set of novel and efficient algorithms proposed Firstly, set-membership (SM) reduced-rank techniques for interference suppression in DS-CDMA systems are investigated. The principals of SM filtering are applied to the adaptation of the projection matrix and reduced-rank filter in reduced-rank signal processing based on the method of joint iterative optimisation (JIO) of adaptive filters. The sparse updates and optimised step-sizes that form the basis of SM schemes are introduced to JIO in order to improve its convergence and complexity whilst maintaining its use of low-dimensionality filters. Analysis of the proposed schemes confirms their stability and establishes bounds on their performance. Through simulation in a DS-CDMA system, the proposed schemes are shown to outperform the existing JIO and reducedrank schemes whilst achieving a significant reduction in computational complexity. Secondly, resource allocation in multirelay cooperativeMIMO systems is addressed. Jointly operating iterative discrete stochastic algorithms (DSA) are utilised to form a low-complexity transmit diversity selection (TDS) scheme optimised by a parallel relay selection (RS) procedure. The proposed scheme is shown to converge to the optimal exhaustive solution of the combinatorial TDS problem and enhance the performance of existing interference suppression methods. RS based on DSA is extended to continuous adaptive power allocation to form a joint discrete-continuous optimisation procedure that augments conventional iterative MMSE power allocation. Lastly, an investigation into the use of bidirectional MMSE algorithms for interference suppression in DS-CDMA systems operating over severely fading channels is presented. The correlation present, even in fast fading environments, between 3 or more successive channel coefficients is exploited to enable improved reception and multiuser interference suppression (MUI) without tracking of the faded or unfaded symbols. A 2 set of adaptive mixing parameters is introduced to optimise the weighting of the correlation information from the considered channel coefficients in order to improve convergence and steady-state performance. An analysis of the proposed schemes is presented and the mechanisms behind their improved performance established. Accompanying signal-to-interference-plus-noise-ratio (SINR) analysis also provides analytical performance curves. The proposed schemes are compared to existing schemes and are shown to provide improved tracking and robustness, both in conventional and cooperative DSCDMA networks.