Optimum Vector Perturbation Minimizing Total MSE in Multiuser MIMO Downlink
ABSTRACT We propose a new vector precoding for the down-link of multiuser multiple-input multiple-output (MIMO) systems. The proposed scheme can be thought as the minimum mean square error (MMSE) version of the vector perturbation technique. We generalize the vector perturbation by allowing the data vector to be perturbed by an arbitrary vector. After the modulo operation at receivers, the remaining part of the perturbation is dealt with as the co-channel interference. We derive the total mean square error (MSE) of the received signal, and find the optimum perturbation vector that minimizes the total MSE. Simulation results show that our scheme outperforms the other compared schemes at all signal-to-noise ratios (SNRs), while the computational complexity is not increased.
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ABSTRACT: We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas communicates with single-receiving-antenna mobile station (MS) receivers each having a modulo device. Given the knowledge of the channel state information and the current information symbol vector to be transmitted, our scheme directly generates the effective symbol vector based on the MBER criterion using the particle swarm optimization (PSO) algorithm. The proposed PSO-aided generalized MBER VP scheme is shown to outperform the powerful minimum mean-square-error (MMSE) VP and improved MMSE-VP benchmarks, particularly for rank-deficient systems, where the number of BS transmitting antennas is lower than the number of MSs supported.IEEE Transactions on Vehicular Technology 03/2011; · 2.06 Impact Factor
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ABSTRACT: Bio-inspired computational methods have found wide-ranging applications in signal processing and other walks of engineering. The main attraction of adopting bio-inspired computational intelligence algorithms is that they may facilitate global or near global optimal designs with affordable computational costs. In this contribution, particle swarm optimisation (PSO) is invoked for designing optimal multiuser transmission (MUT) schemes for multiple-input multiple-output communication. Specifically, we consider the minimum bit-error-rate (MBER) linear MUT using PSO and we design a PSO aided MBER generalised vector precoding for nonlinear MUT. These PSO aided MUT techniques compare favourably with the state-of-the-art conventional schemes, in terms of performance and complexity.Journal of Computational and Theoretical Nanoscience 01/2012; 9(2):266-275. · 0.67 Impact Factor
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ABSTRACT: A generalised vector precoding (VP) design based on the minimum bit error rate (MBER) criterion is proposed for multiuser transmission in the downlink of a multiuser system where the base station (BS) equipped with multiple transmit antennas communicates with single-receive-antenna mobile station (MS) receivers each having a modulo detection device. Our transmit preprocessing scheme generates the effective symbol vector based on the MBER criterion, given the knowledge of the channel state information and the current information symbol vector to be transmitted. The proposed MBER based generalised VP algorithm is shown to outperform even the powerful minimum mean-square-error VP benchmark, particularly for rank-deficient systems where the number of BS's transmit antennas is smaller than the number MSs supported.Vehicular Technology Conference Fall (VTC 2010-Fall), 2010 IEEE 72nd; 10/2010