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A novel approach to design of local quantizers for distributed estimation

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In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques

Abstract

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques

참고문헌 (13)

  1. A. O. Hero, "Sensor network source localization via projection onto convex sets (POCS)", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) (2005)
  2. Y. H. Kim, "Quantizer design optimized for distributed estimation", IEICE Trans. on information and systems, E97-D(6), pp.1639~1643 (2014)[DOI]
  3. 김윤학, "Cluster-Based Quantization and Estimation for Distributed Systems", Journal of Information and Communication Convergence Engineering, 14(4), pp.215~221 (2016), 한국정보통신학회[DOI]
  4. Y. H. Kim, "Encoding of quantisation partitions optimised for distributed estimation", Electronics Letters, 52(8), pp.611~613 (2016)[DOI]
  5. Y. H. Kim., "Quantizer design for source localization in sensor networks", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) (2005)
  6. Y. H. Kim., "Maximun a posteriori (MAP)-based algorithm for distributed source localization using quantized acoustic sensor readings", IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP) (2006)
  7. Y. H. Kim, "Distributed encoding algorithms for source localization in sensor networks", EURASIP Journal on Advances in Signal Processing, 2010, pp.1~13 (2010)[DOI]
  8. Y. H. Kim, "Quantizer design for energy-based source localization in sensor networks", IEEE Trans. on Signal Processing, 59(11), pp.5577~5588 (2011)[DOI]
  9. D. Li, "Energy-based collaborative source localization using acoustic microsensor array", EURASIP Journal on Applied Signal Processing, 2003, pp.321~337 (2003)[DOI]
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  13. N. Wernersson, "Distributed quantization over noisy channels", IEEE Trans. on communications, 57, pp.1693~1700 (2009)[DOI]

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