Efficient data augmentation techniques for some classes of state space models

Data augmentation improves the convergence of iterative algorithms, such as the EM algorithm and Gibbs sampler by introducing carefully designed latent variables. In this article, we first propose a data augmentation scheme for the first-order autoregression plus noise model, where optimal values of working parameters introduced for recentering and rescaling of the latent states, can be derived analytically by minimizing the fraction of missing information in the EM algorithm. The proposed data augmentation scheme is then utilized to design efficient Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of some non-Gaussian and nonlinear state space models, via a mixture of normals approximation coupled with a block-specific reparametrization strategy. Applications on simulated and benchmark real datasets indicate that the proposed MCMC sampler can yield improvements in simulation efficiency compared with centering, noncentering and even the ancillarity-sufficiency interweaving strategy.Comment: Keywords: Data augmentation, State space model, Stochastic volatility model, EM algorithm, Reparametrization, Markov chain Monte Carlo, Ancillarity-sufficiency interweaving strateg

Adaptive beamforming for binary phase shift keying communication systems

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On multi-user EXIT chart analysis aided turbo-detected MBER beamforming designs

Abstract—This paper studies the mutual information transfer characteristics of a novel iterative soft interference cancellation (SIC) aided beamforming receiver communicating over both additive white Gaussian noise (AWGN) and multipath slow fading channels. Based on the extrinsic information transfer (EXIT) chart technique, we investigate the convergence behavior of an iterative minimum bit error rate (MBER) multiuser detection (MUD) scheme as a function of both the system parameters and channel conditions in comparison to the SIC aided minimum mean square error (SIC-MMSE) MUD. Our simulation results show that the EXIT chart analysis is sufficiently accurate for the MBER MUD. Quantitatively, a two-antenna system was capable of supporting up to K=6 users at Eb/N0=3dB, even when their angular separation was relatively low, potentially below 20?. Index Terms—Minimum bit error rate, beamforming, multiuser detection, soft interference cancellation, iterative processing, EXIT chart

Iterative Multiuser Minimum Symbol Error Rate Beamforming Aided QAM Receiver

A novel iterative soft interference cancellation (SIC) aided beamforming receiver is developed for high-throughput quadrature amplitude modulation systems. The proposed SIC based minimum symbol error rate (MSER) multiuser detection scheme guarantees the direct and explicit minimization of the symbol error rate at the output of the detector. Adopting the extrinsic information transfer (EXIT) chart technique, we compare the EXIT characteristics of an iterative MSER multiuser detector (MUD) with those of the conventional minimum mean-squared error (MMSE) detector. As expected, the proposed SIC-MSER MUD outperforms the SIC-MMSE MUD. Index Terms—Beamforming, iterative multiuser detection, minimum symbol error rate, quadrature amplitude modulation

Symmetric complex-valued RBF receiver for multiple-antenna aided wireless systems

A nonlinear beamforming assisted detector is proposed for multiple-antenna-aided wireless systems employing complex-valued quadrature phase shift-keying modulation. By exploiting the inherent symmetry of the optimal Bayesian detection solution, a novel complex-valued symmetric radial basis function (SRBF)-network-based detector is developed, which is capable of approaching the optimal Bayesian performance using channel-impaired training data. In the uplink case, adaptive nonlinear beamforming can be efficiently implemented by estimating the system’s channel matrix based on the least squares channel estimate. Adaptive implementation of nonlinear beamforming in the downlink case by contrast is much more challenging, and we adopt a cluster-variationenhanced clustering algorithm to directly identify the SRBF center vectors required for realizing the optimal Bayesian detector. A simulation example is included to demonstrate the achievable performance improvement by the proposed adaptive nonlinear beamforming solution over the theoretical linear minimum bit error rate beamforming benchmark

Minimum Symbol Error Rate Turbo Multiuser Beamforming Aided QAM Receiver

This paper studies a novel iterative soft interference cancellation (SIC) aided beamforming receiver designed for highthroughput quadrature amplitude modulation systems communicating over additive white Gaussian noise channels. The proposed linear SIC aided minimum symbol error rate (MSER) multiuser detection scheme guarantees the direct and explicit minimisation of the symbol error rate at the output of the detector. Based on the extrinsic information transfer (EXIT) chart technique, we compare the EXIT characteristics of an iterative MSER multiuser detector (MUD) with those of the conventional minimum mean squared error (MMSE) detector. As expected, the proposed SICMSER MUD outperforms the SIC aided MMSE MUD