Rapid prototyping of a fixed-complexity sphere decoder and its application to iterative decoding of turbo-MIMO systems

• Main Author: Barbero Liñan, Luis G.
• Published: University of Edinburgh 2007
• Subjects: 621.382
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.641290

This thesis concentrates on the analysis of the sphere decoder (SD) for MIMO detection. It provides optimal maximum likelihood (ML) performance with reduced complexity compared to the maximum likelihood detector (MLD). However, a field-programmable gate array (FPGA) implementation of the algorithm presents several disadvantages due to its variable complexity and the sequential nature of its tree search. This research proposes a fixed-complexity sphere decoder (FSD) to overcome the drawbacks of the SD. It provides a fixed complexity and achieves quasi-maximum likelihood (ML) performance, combining a search through a small subset of the transmitted constellation with a novel channel matrix ordering. This represents a novel approach compared to most optimizations of the SD in the literature, which concentrate on reducing the average complexity of the algorithm. As a result, an implementation of the FSD is shown to provide the same error performance using less FPGA resources and achieving a considerably higher (and constant) throughput compared to previous SD hardware implementations. The same FSD concept is applied to a large MIMO system with 4 antennas at both ends of the link and 64-quadrature amplitude modulation (QAM). A list extension of the FSD (LFSD) combines the same channel matrix ordering and an extended fixed search to generate a list of candidates for short-value calculation. Depending on the size of the extended search, different levels of performance and complexity can be achieved making the algorithm suitable for reconfigurable architectures. Its FPGA implementation shows how soft-value information can be obtained with a fully pipelined architecture. It provides a constant throughput which is considerably higher than previously presented soft-MIMO detector implementations.