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Optimal Data Detection and Signal Estimation in Systems with Input Noise

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Document pages: 18 pages

Abstract: Practical systems often suffer from hardware impairments that already appearduring signal generation. Despite the limiting effect of such input-noiseimpairments on signal processing systems, they are routinely ignored in theliterature. In this paper, we propose an algorithm for data detection andsignal estimation, referred to as Approximate Message Passing with Input noise(AMPI), which takes into account input-noise impairments. To demonstrate theefficacy of AMPI, we investigate two applications: Data detection in largemultiple-input multiple output (MIMO) wireless systems and sparse signalrecovery in compressive sensing. For both applications, we provide preciseconditions in the large-system limit for which AMPI achieves optimalperformance. We furthermore use simulations to demonstrate that AMPI achievesnear-optimal performance at low complexity in realistic, finite-dimensionalsystems.

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