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Optimal Receiver Placement for K-barrier Coverage in Passive Bistatic Radar Sensor Networks

Published:26 August 2020Publication History
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Abstract

The improvement of coverage quality in the construction of multiple-barrier coverage is a critical problem in a wireless sensor network. In this article, we investigate the K-barrier coverage construction problem in passive bistatic radar sensor networks. In contrast to traditional bistatic radar networks, the transmitters in a passive bistatic radar network are predeployed and noncooperative. To construct K barriers, we need to deploy receivers that couple with predeployed transmitters to build continuous barriers. In this work, we focus on the minimum number of receivers problem of constructing K-barrier coverage, where the minimum number of receivers is based on the predeployed transmitters. To handle this problem, we first investigate the optimal placement of receivers between adjacent transmitters for a sub-barrier formation and then determine the optimal placement of receivers for the one-barrier construction. For multiple-barrier coverage construction, we introduce a weighted transmitter graph (WTG) to describe the relation among different transmitters, where the weight in the graph is the minimum number of receivers needed for these two transmitters for a sub-barrier formation. Based on WTG, the minimum receivers problem changes to a problem of how to find K-disjoint paths with the minimum total weight in the graph. For large-scale networks, we also propose two efficient heuristic algorithms to solve the corresponding problem. Finally, we conduct extensive experiments to validate the correctness and the efficiency of the proposed algorithms.

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    • Published in

      cover image ACM Transactions on Internet Technology
      ACM Transactions on Internet Technology  Volume 20, Issue 3
      SI: Evolution of IoT Networking Architectures papers
      August 2020
      259 pages
      ISSN:1533-5399
      EISSN:1557-6051
      DOI:10.1145/3408328
      • Editor:
      • Ling Liu
      Issue’s Table of Contents

      Copyright © 2020 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 26 August 2020
      • Online AM: 7 May 2020
      • Accepted: 1 December 2019
      • Revised: 1 November 2019
      • Received: 1 June 2019
      Published in toit Volume 20, Issue 3

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