Distributed Space-Time Coding Techniques with Limited Feedback in Cooperative MIMO Networks

Multi-input multi-output (MIMO) wireless networks and distributed MIMO relaying wireless networks have attracted significant attention in current generation of wireless communication networks, and will play a key role in the next generation of wireless net- works. The improvement of network capacity, data rate and reliability can be achieved at the cost of increasing computational complexity of employing space-time coding (STC) and distributed STC (DSTC) in MIMO and distributed MIMO relaying networks, respectively. Efficient designs and algorithms to achieve high diversity and coding gains with low computational complexity in encoding and decoding of STC and DSTC schemes are essential. In this thesis, DSTC designs with high diversity and coding gains and efficient detection and code matrices optimization algorithms in cooperative MIMO networks are proposed. Firstly, adaptive power allocation (PA) algorithms with different criteria for a coop- erative MIMO network equipped with DSTC schemes are proposed and evaluated. Joint constrained optimization algorithms to determine the PA parameters and the receive filters are proposed for each transmitted symbol in each link, as well as the channel coefficients matrices. Linear receive filter and maximum likelihood (ML) detection are considered with amplify-and-forward (AF) and decode-and-forward (DF) cooperation strategies. In the proposed algorithms, the elements in the PA matrices are optimized at the destination node and then transmitted back to the relay nodes via a feedback channel. The effects of the feedback errors are considered. Linear minimum mean square error (MMSE) expressions and the PA matrices depend on each other and are updated iteratively. Stochastic gradient (SG) algorithms are developed with reduced detection complexity. Simulation results show that the proposed PA algorithms obtain significant performance gains as compared to existing power allocation schemes. Secondly, an DSTC scheme is proposed for two-hop cooperative MIMO networks. Linear MMSE receive filter and adjustable code matrices are considered subject to a power constraint with an AF cooperation strategy. In the proposed adaptive DSTC scheme, an adjustable code matrix obtained by a feedback channel is employed to transform the space-time coded matrix at the relay node. The effects of the limited feedback and the feedback errors are assessed. Linear MMSE expressions are devised to compute the parameters of the adjustable code matrix and the linear receive filters. SG and least-squares (LS) algorithms are also developed with reduced computational complexity. An upper bound on the pairwise error probability analysis is derived and indicates the advantage of employing the adjustable code matrices at the relay nodes. An alternative optimization algorithm for the adaptive DSTC scheme is also derived in order to eliminate the need for feedback. The algorithm provides a fully distributed scheme for the adaptive DSTC at the relay node based on the minimization of the error probability. Thirdly, an adaptive delay-tolerant DSTC (DT-DSTC) scheme is proposed for two-hop cooperative MIMO networks. An ML receiver and adjustable code matrices are consid- ered for different DSTC configuration schemes subject to a power constraint with a DF cooperation strategy. In the proposed DT-DSTC scheme, an adjustable code matrix is employed to transform the space-time coded matrix at the relay nodes. An upper bound on the pairwise error probability and rank criteria analysis are derived and indicates the advantage of the proposed coding algorithm. The adaptive DT-DSTC algorithms are ex- tended to the cooperative MIMO systems using AF strategy and opportunistic relaying algorithms in order to achieve a delay-tolerant coding scheme combined with the optimal power allocation strategies.