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    Low-Complexity Approaches for MIMO Capacity with Per-Antenna Power Constraint


    Pham, Thuy M. and Farrell, Ronan and Tran, Le-Nam (2017) Low-Complexity Approaches for MIMO Capacity with Per-Antenna Power Constraint. In: IEEE VTC Spring 2017. IEEE. ISBN 978-1-5090-5932-4

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    Official URL: https://doi.org/10.1109/VTCSpring.2017.8108406


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    Abstract

    This paper proposes two low-complexity iterative algorithms to compute the capacity of a single-user multiple-input multiple-output channel with per-antenna power constraint. The first method results from manipulating the optimality conditions of the considered problem and applying fixed-point iteration. In the second approach, we transform the considered problem into a minimax optimization program using the well-known MAC- BC duality, and then solve it by a novel alternating optimization method. In both proposed iterative methods, each iteration involves an optimization problem which can be efficiently solved by the water-filling algorithm. The proposed iterative methods are provably convergent. Complexity analysis and extensive numerical experiments are carried out to demonstrate the superior performance of the proposed algorithms over an existing approach known as the mode-dropping algorithm.

    Item Type: Book Section
    Keywords: MIMO; Optimization; Signal processing algorithms; Complexity theory; Iterative methods; Matrix decomposition; Algorithm design and analysis; iterative methods; MIMO communication; minimax techniques; optimisation; wireless channels; low-complexity approaches; MIMO capacity; per-antenna power constraint; low-complexity iterative algorithms; optimality conditions; minimax optimization program; MAC- BC duality; novel alternating optimization method; iterative methods; optimization problem; water-filling algorithm; complexity analysis; mode-dropping algorithm; single-user multiple-input multiple-output channel; fixed-point iteration;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 11912
    Depositing User: Ronan Farrell
    Date Deposited: 28 Nov 2019 16:40
    Publisher: IEEE
    Refereed: Yes
    URI:

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