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: In this paper, we propose an advanced joint transceiver design for block-diagonal geometric-mean-decomposition (BD-GMD) based multiuser multiple-input-multiple-output (MIMO) systems. First, we use the lattice reduction (LR) method to design the BD-GMD-based advanced detection and precoding for an uplink and a downlink, respectively. Then, we exploit the vector perturbation (VP) technique to further improve the system performance of the multiuser downlink. To directly reduce the high complexity of VP by a sphere encoder, we provide an LR-based sphere encoder and LR-based approximations for perturbation symbols. Performance and complexity analyses are given to show the advantages of the proposed schemes. Particularly, the diversity-gain analysis shows some insights of the existing and proposed schemes. Simulation results verify the performance improvement as well as the theoretical analysis.IEEE Transactions on Vehicular Technology 03/2010; · 2.06 Impact Factor
Conference Paper: Improved MMSE Vector Precoding Based on the MBER Criterion[Show abstract] [Hide abstract]
ABSTRACT: A novel vector precoding scheme is proposed for the downlink of a multiuser system equipped with multiple antennas transmitting to single-antenna aided mobile receivers. Our transmit preprocessing scheme first invokes a regularized channel inversion and then superimposes a perturbation vector to directly minimize the bit error ratio (BER) of the system as an improvement to the well-known minimum mean-square-error (MMSE) vector precoding scheme. Our simulation results demonstrate that the proposed vector precoding scheme achieves the same BER performance as the MMSE vector precoding at the same complexity, when only discrete vector perturbations are allowed. However, the performance of the proposed vector precoding scheme can be further improved based on the MBER criterion, when continuous-valued vector perturbations are carried out.Vehicular Technology Conference, 2009. VTC Spring 2009. IEEE 69th; 05/2009
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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. · 1.03 Impact Factor