Design of Optimal Quantizers for Distributed Source Coding
DCC '03 Proceedings of the Conference on Data Compression
SIAM Journal on Control and Optimization
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ACM Transactions on Sensor Networks (TOSN)
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IEEE Transactions on Communications
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IEEE Transactions on Information Theory - Part 2
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IEEE Transactions on Information Theory
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IEEE Transactions on Information Theory
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IEEE Transactions on Information Theory
Encoding of correlated observations
IEEE Transactions on Information Theory
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IEEE Transactions on Information Theory
IEEE Communications Magazine
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The paper considers a sensor network whose sensors observe a common quantity and are affected by arbitrary additive bounded noises with a known upper bound. During the experiment, any sensor can communicate only a finite and given number of bits of information to the decision center. The contributions of the particular sensors, the rules of data encoding, decoding, and fusion, as well as the estimation scheme should be designed to achieve the best overall performance in estimation of the observed quantity by the decision center. An optimal algorithm is obtained that minimizes the maximal feasible error. It is shown that it considerably outperforms the algorithm proposed in recent papers in the area and examined only in the idealized case of noiseless sensors.