Semi-blind joint maximum likelihood channel estimation and data detection for MIMO systems

Semi-blind joint maximum likelihood (ML) channel estimation and data detection is proposed for multiple-input multiple-output (MIMO) systems. The joint ML optimization over channel and data is decomposed into an iterative two-level optimization loop. An efficient optimization search algorithm referred to as the repeated weighted boosting search (RWBS) is employed at the upper level to identify the unknown MIMO channel while an enhanced ML sphere detector termed as the optimized hierarchy reduced search algorithm is used at the lower level to perform ML detection of the transmitted data. Only a minimum pilot overhead is required to aid the RWBS channel estimator’s initial operation,which not only speeds up convergence but also avoids ambiguities inherent in blind joint estimation of both the channel and data

Symmetric Radial Basis Function Assisted Space-Time Equalisation for Multiple Receive-Antenna Aided Systems

This constribution considers nonlinear space-time equalisation (STE) designed for single-input multiple-output (SIMO) systems. By exploiting the inherent symmetry of the underlying optimal Bayesian STE solution, a novel symmetric radial basis function (RBF) based STE scheme is proposed, which is capable of achieving the optimal Bayesian equalisation performance. The adaptive adjustment of the STE taps of this symmetric RBF (SRBF) based STE can be achieved by estimating the SIMO channel encountered using the classic least mean square channel estimator and computing the optimal RBF centres from the resultant SIMO channel matrix estimate. Our simulation results demonstrate that the performance of this SRBF based STE is robust with respect to the choice of the algorithmic parameters

Contrasting space-time schemes for MIMO FSO systems with non-coherent modulation

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Adaptive MBER space-time DFE assisted multiuser detection for SDMA systems

In this contribution we propose a space-time decision feedback equalization (ST-DFE) assisted multiuser detection (MUD) scheme for multiple antenna aided space division multiple access systems. A minimum bit error rate (MBER) design is invoked for the MUD, which is shown to be capable of improving the achievable bit error rate performance over that of the minimum mean square error (MMSE) design. An adaptive MBER ST-DFE-MUD is proposed using the least bit error rate algorithm, which is demonstrated to consistently outperform the least mean square (LMS) algorithm, while achieving a lower computational complexity than the LMS algorithm for the binary signalling scheme. Simulation results demonstrate that theMBER ST-DFE-MUD is more robust to channel estimation errors as well as to error propagation imposed by decision feedback errors, compared to the MMSE ST-DFE-MUD

Antennes co-localisées reconfigurables en fréquence pour systèmes MIMO

National audienceCe papier présente trois antennes co-localisées dont les accès présentent un découplage de l'ordre de 30dB en simulation. La diversité entre chaque antenne est assurée par une combinaison de diversité de polarisation et de rayonnement. Le dispositif a été dimensionné pour fonctionner autour de 5.25GHz avec une largeur de bande d'environ 9.8%. Toutefois, afin de répondre aux besoins actuels concernant la multiplication de fonctions au sein d'un même dispositif, une agilité en fréquence a été introduite via l'utilisation de courts-circuits étendant ainsi la bande à 33%, de 5GHz à 7GHz. La faisabilité pratique d'une telle antenne et la fiabilité des choix des différents paramètres de simulation ont été démontrés précédemment dans le cas d'une antenne cube du même type excitée par un seul monopôle

BER Performance Analysis of MIMO Systems Using Equalization Techniques

The mobile data applications has increased the demand for wireless communication systems offering high throughput, wide coverage, and improved reliability. The main challenges in the design of wireless communication systems are the limited resources, such as constrained transmission power, scarce frequency bandwidth, and limited implementation complexity—and the impairments of the wireless channels, including noise, interference, and fading effects. Multiple-Input Multiple-Output (MIMO) communication has been shown to be one of the most promising emerging wireless technologies that can efficiently boost the data transmission rate, improve system coverage, and enhance link reliability. By employing multiple antennas at transmitter and receiver sides, MIMO techniques enable a new dimension – the spatial dimension – that can be utilized in different ways to combat the impairments of wireless channels. This article focuses on Equalization techniques, for Rayleigh Flat fading channel. Equalization is a well known technique for combating intersymbol interference; moreover equalization is the filtering approach which minimizes the error between actual output and desired output by continuous updating its filter coefficients. In this paper, different equalization techniques are investigated for the analysis of BER in MIMO Systems. In this article we have discussed different types of equalizer like ZF, MMSE, ZF-SIC, MMSE-SIC, ML and Sphere decoder. The results are decoded using the ZF, MMSE, ZF-SIC, MMSE-SIC, ML and Sphere decoder (SD) technique. The successive interference methods outperform the ZF and MMSE however their complexity is higher due to iterative nature of the algorithms. ML provides the better performance in comparison to others. Sphere decoder provides the best performance and the highest decoding complexity as compare to ML. We can clearly observe that Sphere decoder gives us high performance in comparison to ML, MMSE-SC, ZF-SIC, MMSE and ZF.   Keywords: Quadrature Amplitude Modulation (QAM), Quadrature Phase Shift Key (QPSK), Binary Phase Shift Key (BPSK), Minimum mean-squared error (MMSE), Maximum likelihood (ML),Bit error rate (BER), Independent identical distributed (i.i.d. ), Intersymbol interference (ISI). Successive interference cancellation (SIC), Sphere Decoder (SD), zero Forcing (ZF)