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Related Experiment Video

Updated: Nov 27, 2025

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

Published on: August 12, 2013

A Decentralized Receiver in Gaussian Interference.

Christian D Chapman¹, Hans Mittelmann², Adam R Margetts³

¹School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA.

Entropy (Basel, Switzerland)

|December 3, 2020

Summary

This summary is machine-generated.

Distributed receivers with limited cooperation can achieve high communication rates, even with strong interference. Effective resource sharing enables simple strategies to overcome significant signal degradation in wireless networks.

Keywords:

channel capacity communications networks distributed reception interference mitigation relay channels

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Area of Science:

Information Theory
Wireless Communications
Signal Processing

Background:

Distributed receivers face resource limitations and interference in cooperative networks.
Fusion nodes require efficient data aggregation from multiple sources.
Limited throughput in local area networks (LANs) poses a challenge for cooperative communication.

Purpose of the Study:

To develop bounds on the maximum communication rate in a cooperative network with distributed receivers and interference.
To assess strategies for mitigating strong interferers using limited receiver resources.
To analyze the impact of resource sharing and channel conditions on achievable communication rates.

Main Methods:

Developing theoretical bounds for communication rates.
Analyzing cooperative strategies like quantize-and-forward.
Simulating performance using Monte-Carlo experiments across various channel models (e.g., spatially Ricean).

Main Results:

Effective resource sharing allows quantize-and-forward to mitigate interferers significantly stronger than the signal.
Achievable rates remain stable despite variations in signal power ratios.
Receiver resource allocation must adapt to changing channel conditions.

Conclusions:

Theoretical bounds are achievable and tight under varying LAN resource availability.
Cooperative communication systems can effectively manage interference with optimized resource sharing.
Adaptive resource allocation is crucial for robust performance in diverse channel environments.