NDLI: Optimal Distortion-Power Tradeoffs in Gaussian Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Nan Liu Ulukus, S.
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Maryland Univ., College Park, MD (Nan Liu; Ulukus, S.)
Abstract	We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those measurement samples to a collector node in a cooperative multiple access channel with imperfect feedback, and reconstruct the entire random process at the collector node. We provide lower and upper bounds for the minimum achievable expected distortion when the underlying random process is Gaussian. In the case where the random process satisfies some general conditions, we evaluate the lower and upper bounds explicitly and show that they are of the same order for a wide range of sum power constraints. Thus, for these random processes, under these sum power constraints, we determine the achievability scheme that is order-optimal, and express the minimum achievable expected distortion as a function of the sum power constraint
Starting Page	1534
Ending Page	1538
File Size	183759
Page Count	5
File Format	PDF
ISBN	142440505X
DOI	10.1109/ISIT.2006.262125
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Random processes Distortion measurement Upper bound Feedback Random variables Gaussian processes Educational institutions Power measurement Gaussian noise Capacitive sensors
Content Type	Text
Resource Type	Article

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