Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Energy-Constrained Optimal Quantization for Wireless Sensor Networks | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 462930 12 pages doi 2008 462930 Research Article Energy-Constrained Optimal Quantization for Wireless Sensor Networks Xiliang Luo1 and Georgios B. Giannakis2 1 Qualcomm Inc. San Diego CA 92121 USA 2 Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN 55455 USA Correspondence should be addressed to Georgios B. Giannakis georgios@ Received 28 May 2007 Revised 15 October 2007 Accepted 2 November 2007 Recommended by Huaiyu Dai As low power low cost and longevity of transceivers are major requirements in wireless sensor networks optimizing their design under energy constraints is of paramount importance. To this end we develop quantizers under strict energy constraints to effect optimal reconstruction at the fusion center. Propagation modulation as well as transmitter and receiver structures are jointly accounted for using a binary symmetric channel model. We first optimize quantization for reconstructing a single sensor s measurement and deriving the optimal number of quantization levels as well as the optimal energy allocation across bits. The constraints take into account not only the transmission energy but also the energy consumed by the transceiver s circuitry. Furthermore we consider multiple sensors collaborating to estimate a deterministic parameter in noise. Similarly optimum energy allocation and optimum number of quantization bits are derived and tested with simulated examples. Finally we study the effect of channel coding on the reconstruction performance under strict energy constraints and jointly optimize the number of quantization levels as well as the number of channel uses. Copyright 2008 X. Luo and G. B. Giannakis. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original
