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Low-complexity near-optimum detection techniques for non-cooperative and cooperative MIMO systems

Record type: Thesis (Doctoral)

In this thesis, firstly we introduce various reduced-complexity near-optimum Sphere Detection (SD) algorithms, including the well-known depth-first SD, the K-best SD as well as the recently proposed Optimized Hierarchy Reduced Search Algorithm (OHRSA), followed by comparative studies of their applications, characteristics, performance and complexity in the context of uncoded non-cooperative Multiple-Input Multiple-Output (MIMO) systems using coherent detection. Particular attention is devoted to Spatial Division Multiple Accessing (SDMA) aided Orthogonal Frequency Division Multiplexing (OFDM) systems, which are considered to constitute a promising candidate for next-generation mobile communications.
It is widely recognized that the conventional List SD (LSD) employed in channel-coded iterative detection aided systems may still impose a potentially excessive complexity, especially when it is applied to high-throughput scenarios employing high-order modulation schemes and/or supporting a high number of transmit antennas/users. Hence, in this treatise three complexity-reduction schemes are devised specifically for LSD-aided iterative receivers in the context of high-throughput channel-coded SDMA/OFDM systems in order to maintain a near-optimum performance at a reduced complexity. Explicitly, based on the exploitation of the soft-bit-information fed back by the channel decoder, the iterative center-shifting and Apriori-LLR-Threshold (ALT) schemes are contrived, which are capable of achieving a significant complexity reduction. Additionally, a powerful three-stage serially concatenated scheme is created by intrinsically amalgamating our proposed center-shifting-assisted SD with the decoder of a Unity-Rate-Code (URC). For the sake of achieving a near-capacity performance, Irregular Convolutional Codes (IrCCs) are used as the outer code for the proposed iterative center-shifting SD aided three-stage system.
In order to attain extra coding gains along with transmit diversity gains for Multi-User MIMO (MU-MIMO) systems, where each user is equipped with multiple antennas, we contrive a multilayer tree-search based K-best SD scheme, which allows us to apply the Sphere Packing (SP) aided Space-Time Block Coding (STBC) scheme to the MU-MIMO scenarios, where a near Maximuma-Posteriori (MAP) performance is achieved at a low complexity.
An alternative means of achieving transmit diversity while circumventing the cost and size constraints of implementing multiple antennas on a pocket-sized mobile device is cooperative diversity, which relies on antenna-sharing amongst multiple cooperating single-antenna-aided users. We design a realistic cooperative system, which operates without assuming the knowledge of the Channel State Information (CSI) at transceivers by employing differentially encoded modulation at the transmitter and non-coherent detection at the receiver. Furthermore, a newMultiple-Symbol Differential Sphere Detection (MSDSD) is contrived in order to render the cooperative system employing either the Differential Amplify-and-Forward (DAF) or the Differential Decode-and-Forward (DDF) protocol more robust to the detrimental channel-envelope fluctuations of high-velocity mobility environments. Additionally, for the sake of achieving the best possible performance, a resource optimized hybrid relaying scheme is proposed for exploiting the complementarity of the DAF- and DDF-aided systems.
Finally, we investigate the benefits of introducing cooperative mechanisms into wireless networks from a pure channel capacity perspective and from the practical perspective of approaching the Discrete-input Continuous-output Memoryless Channel (DCMC) capacity of the cooperative network with the aid of our proposed Irregular Distributed Hybrid Concatenated Differential (Ir-DHCD) coding scheme.

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Wang, Li (2010) Low-complexity near-optimum detection techniques for non-cooperative and cooperative MIMO systems University of Southampton, School of Electronics and Computer Science, Doctoral Thesis , 311pp.

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Published date: January 2010
Organisations: University of Southampton


Local EPrints ID: 71971
PURE UUID: 2f7a1e30-858b-4143-b8a9-55b9a1903eeb

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Date deposited: 13 Jan 2010
Last modified: 18 Jul 2017 23:57

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Author: Li Wang
Thesis advisor: Lajos Hanzo
Thesis advisor: Soon Ng

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