Rate - Reliability - Complexity limits in ML and Lattice based decoding for MIMO, multiuser and cooperative communications

Abstract : In telecommunications, rate-reliability and encoding-decoding computational complexity (floating point operations - flops), are widely considered to be limiting and interrelated bottlenecks. For this reason, any attempt to significantly reduce complexity may be at the expense of a substantial degradation in error-performance. Establishing this intertwined relationship constitutes an important research topic of substantial practical interest. This dissertation deals with the question of establishing fundamental rate, reliability and complexity limits in general outage-limited multiple-input multiple-output (MIMO) communications, and its related point-to-point, multiuser, cooperative, two-directional, and feedback-aided scenarios. We explore a large subset of the family of linear lattice encoding methods, and we consider the two main families of decoders; maximum likelihood (ML) based and lattice-based decoding. Algorithmic analysis focuses on the efficient bounded-search implementations of these decoders, including a large family of sphere decoders. Specifically, the presented work provides high signal-to-noise (SNR) analysis of the minimum computational reserves (flops or chip size) that allow for a) a certain performance with respect to the diversity-multiplexing gain tradeoff (DMT) and for b) a vanishing gap to the uninterrupted (optimal) ML decoder or a vanishing gap to the exact implementation of (regularized) lattice decoding. The derived complexity exponent describes the asymptotic rate of exponential increase of complexity, exponential in the number of codeword bits.
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Arun Kumar Singh. Rate - Reliability - Complexity limits in ML and Lattice based decoding for MIMO, multiuser and cooperative communications. Networking and Internet Architecture [cs.NI]. Télécom ParisTech, 2012. English. ⟨NNT : 2012ENST0005⟩. ⟨tel-01230598⟩

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