@article {10.3844/jmssp.2017.325.329,
article_type = {journal},
title = {Large Deviation, Basic Information Theory for Wireless Sensor Networks},
author = {Doku-Amponsah, Kwabena},
volume = {13},
year = {2017},
month = {Oct},
pages = {325-329},
doi = {10.3844/jmssp.2017.325.329},
url = {https://thescipub.com/abstract/jmssp.2017.325.329},
abstract = {In this research paper, we establish Shannon-McMillan-Breiman Theorem for Wireless Sensor Networks modelled as Coloured Geometric Random Networks. For, large n we show that a Wireless Sensor Network consisting of n sensors in [0; 1]d linked by an expected number of edges of order n log n can be transmitted by approximately [n(log n)2 πd/2/(d/2)!] H bits, where H is an entropy defined explicitly from the parameters of the Coloured Geometric Random Network. In the process, we derive a joint Large Deviation Principle (LDP) for the empirical sensor measure and the empirical link measure of coloured random geometric network models.},
journal = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}