Distributed functional scalar quantization simplified
Files
First author draft
Date
2013-07
Authors
Sun, John Z.
Misra, Vinith
Goyal, Vivek K.
Version
First author draft
OA Version
Citation
John Z Sun, Vinith Misra, Vivek K Goyal. 2013. "Distributed Functional Scalar Quantization Simplified." IEEE Transactions on Signal Processing, Volume 61, Issue 14, pp. 3495 - 3508. https://doi.org/10.1109/tsp.2013.2259483
Abstract
Distributed functional scalar quantization (DFSQ) theory provides optimality conditions and predicts performance of data acquisition systems in which a computation on acquired data is desired. We address two limitations of previous works: prohibitively expensive decoder design and a restriction to source distributions with bounded support. We show that a much simpler decoder has equivalent asymptotic performance to the conditional expectation estimator studied previously, thus reducing decoder design complexity. The simpler decoder features decoupled communication and computation blocks. Moreover, we extend the DFSQ framework with the simpler decoder to source distributions with unbounded support. Finally, through simulation results, we demonstrate that performance at moderate coding rates is well predicted by the asymptotic analysis, and we give new insight on the rate of convergence.