A Continuous Vector-Perturbation for Multi-Antenna Multi-User Communication

Chua, Wee Seng; Yuen, Chau; Chin, F.

doi:10.1109/vetecs.2007.375

Cited by 10 publications

(9 citation statements)

References 10 publications

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“…To reach the aim, several methods have been proposed such as processing VP with continuous-valued perturbation vector [6] or minimizing the bit-error ratio (BER) of generalized RCI-VP system as the optimization criterion [7]. Several schemes improve the RCI-VP performance by shaping the transmitted symbols with different lattice transformation techniques [8].…”

Section: Introductionmentioning

confidence: 99%

Introducing dual regularization parameters into regularized channel inversion (RCI)-based vector perturbation for modulo loss reduction

Hou

Tsukamoto

Yano

et al. 2014

16th International Conference on Advanced Communication Technology

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Abstract-This paper proposes a method to reduce the symbol error caused by modulo operator for regularized channel inversion (RCI)-based vector perturbation (RCI-VP). The proposed method introduces dual regularization parameters of RCI precoding matrix. First regularization parameter α1 is set so as to maximize the signal to interference plus noise ratio (SINR) value of each stream to find the optimal perturbation vector. The second regularization parameter α2 is set so as to minimize the total MSE between the transmitted perturbation vector and received perturbation vector to reduce the symbol error caused by modulo operator. The simulated results confirm that the proposed method can improve the performance of RCI-VP over i.i.d. MIMO channel and frequency-selective fading MIMO channel.

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Section: Introductionmentioning

confidence: 99%

Introducing dual regularization parameters into regularized channel inversion (RCI)-based vector perturbation for modulo loss reduction

Hou

Tsukamoto

Yano

et al. 2014

16th International Conference on Advanced Communication Technology

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show abstract

“…42 Specifically, the vector precoding (VP) algorithm [43][44][45][46][47] is capable of outperforming any linear pre-processing technique, in terms of the system's achievable BER, at the expense of an increased complexity. The performance gain of a VP based MUT over a linear MUT scheme is particularly significant in the rank-deficient senario where the number of the BS transmitter antennas is smaller than the number of MSs supported.…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimisation Aided MIMO Multiuser Transmission Designs

Wang¹,

Chen²,

Hanzo³

2012

Jnl of Comp & Theo Nano

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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.

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“…Nonlinear MUT techniques are capable of approaching the rate region of dirty paper coding [10]. The family of vector precoding (VP) schemes [11]- [14], where each receiver employs a modulo device, is capable of significantly outperforming linear MUT techniques. To elaborate a little further, the VP of [11] is based on the ZF criterion, while the powerful MMSE VP solution was derived in [12].…”

Section: Introductionmentioning

confidence: 99%

Generalised Vector Precoding Design Based on the MBER Criterion for Multiuser Transmission

Wang

Chen

Hanzo

2010

2010 IEEE 72nd Vehicular Technology Conference - Fall

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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 rankdeficient systems where the number of BS's transmit antennas is smaller than the number MSs supported.

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A Continuous Vector-Perturbation for Multi-Antenna Multi-User Communication

Cited by 10 publications

References 10 publications

Introducing dual regularization parameters into regularized channel inversion (RCI)-based vector perturbation for modulo loss reduction

Introducing dual regularization parameters into regularized channel inversion (RCI)-based vector perturbation for modulo loss reduction

Particle Swarm Optimisation Aided MIMO Multiuser Transmission Designs

Generalised Vector Precoding Design Based on the MBER Criterion for Multiuser Transmission

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