On Scaling Laws of Diversity Schemes in Decentralized Estimation
Alex S. Leong, Subhrakanti Dey

TL;DR
This paper analyzes the asymptotic performance of diversity schemes in decentralized Gaussian source estimation, highlighting their slower decay rate of expected distortion compared to multi-access and orthogonal schemes, and explores optimal power allocation.
Contribution
It derives asymptotic expressions for expected distortion in diversity schemes and compares them with other access schemes, also optimizing power allocation and transmission probability.
Findings
Expected distortion decays as 1/ln(M) for diversity schemes.
Coherent and orthogonal schemes achieve a 1/M decay rate.
Tradeoff identified between simplicity of diversity schemes and synchronization/bandwidth requirements.
Abstract
This paper is concerned with decentralized estimation of a Gaussian source using multiple sensors. We consider a diversity scheme where only the sensor with the best channel sends their measurements over a fading channel to a fusion center, using the analog amplify and forwarding technique. The fusion centre reconstructs an MMSE estimate of the source based on the received measurements. A distributed version of the diversity scheme where sensors decide whether to transmit based only on their local channel information is also considered. We derive asymptotic expressions for the expected distortion (of the MMSE estimate at the fusion centre) of these schemes as the number of sensors becomes large. For comparison, asymptotic expressions for the expected distortion for a coherent multi-access scheme and an orthogonal access scheme are derived. We also study for the diversity schemes, the…
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks · Wireless Communication Security Techniques
