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BROADBAND BEAMFORMING PowerPoint PPT Presentation


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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

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BROADBAND BEAMFORMING

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Broadband beamforming l.jpg

BROADBAND BEAMFORMING

Presented by:

Kalpana Seshadrinathan


Introduction l.jpg

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


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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


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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


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Koca and Levy, 2002


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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]


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EFFECT OF OVERSAMPLING

Oversampling in the receive filter colors the noise


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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


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RESULTS


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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


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