BROADBAND BEAMFORMING Presented by: Kalpana Seshadrinathan.

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Presentation transcript:

BROADBAND BEAMFORMING Presented by: Kalpana Seshadrinathan

INTRODUCTION Equalization Distortion caused by the channel results in Inter- Symbol Interference (ISI) which has to be compensated for to reduce the probability of error Such a compensator is called an equalizer Problem in Broadband Communications High Data Rates are transmitted and multipath distortion is more severe Low complexity equalizers required without sacrificing too much in ISI mitigation

TYPES OF EQUALIZERS Maximum Likelihood Sequence Estimation (MLSE) Optimal in terms of probability of error Disadvantage: Exponential increase in computation requirements with increase in channel memory Linear equalizers Sub-optimal approach Used when computational complexity of MLSE is prohibitive Commonly used optimality criteria for choosing filter coefficients include mean-squared error and peak distortion

BROADBAND BEAMFORMERS MLSE is not implementable in the broadband case due to computational complexity A broadband beamformer reduces the ISI to narrowband levels in the receiver The space-time receiver is made up of an antenna array followed by an FIR filter bank Optimal MAP equalization is then performed on the beamformer output

Koca and Levy, 2002

POWER COMPLEMENTARITY Noise at the filter output is colored and cannot be applied to a trellis-based equalizer Filter coefficients are hence chosen to satisfy the power complementarity property to ensure white noise at receiver output [Koca and Levy, 2002] Power Complementarity property of an N-channel filterbank is defined by [Vaidyanathan, 1993]

EFFECT OF OVERSAMPLING Oversampling in the receive filter colors the noise

BEAMFORMER DESIGN The channel is modeled by an L-ray complex baseband impulse response with Additive White Gaussian Noise Filter coefficients are designed using Lagrangian optimization Objective function is the mean-squared error at the beamformer output The power complementarity constraint is imposed with suitable modifications to account for oversampling

RESULTS

CONCLUSIONS AND FUTURE WORK The impulse response of the channel is seen to be shortened effectively by the beamformer ISI is reduced to about 3 baud intervals and MAP equalization can be performed on the beamformer output Future work may incorporate co-channel interference suppression in the beamformer design