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Entropy 2018, 20(4), 269;

A Decentralized Receiver in Gaussian Interference

School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA
MIT Lincoln Laboratory, Lexington, MA 02421, USA
Author to whom correspondence should be addressed.
Received: 1 February 2018 / Revised: 6 April 2018 / Accepted: 9 April 2018 / Published: 11 April 2018
(This article belongs to the Section Information Theory, Probability and Statistics)
PDF [410 KB, uploaded 3 May 2018]


Bounds are developed on the maximum communications rate between a transmitter and a fusion node aided by a cluster of distributed receivers with limited resources for cooperation, all in the presence of an additive Gaussian interferer. The receivers cannot communicate with one another and can only convey processed versions of their observations to the fusion center through a Local Array Network (LAN) with limited total throughput. The effectiveness of each bound’s approach for mitigating a strong interferer is assessed over a wide range of channels. It is seen that, if resources are shared effectively, even a simple quantize-and-forward strategy can mitigate an interferer 20 dB stronger than the signal in a diverse range of spatially Ricean channels. Monte-Carlo experiments for the bounds reveal that, while achievable rates are stable when varying the receiver’s observed scattered-path to line-of-sight signal power, the receivers must adapt how they share resources in response to this change. The bounds analyzed are proven to be achievable and are seen to be tight with capacity when LAN resources are either ample or limited. View Full-Text
Keywords: distributed reception; communications networks; channel capacity; relay channels; interference mitigation distributed reception; communications networks; channel capacity; relay channels; interference mitigation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Chapman, C.D.; Mittelmann, H.; Margetts, A.R.; Bliss, D.W. A Decentralized Receiver in Gaussian Interference. Entropy 2018, 20, 269.

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