Decentralized sequential change detection using physical layer fusion

• Published in: IEEE transactions on wireless communications Vol. 7; no. 12; pp. 4999 - 5008
• Main Authors: Zacharias, L., Sundaresan, R.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additive noise; Ali-Silvey distance; Applied sciences; Array signal processing; Change detection; Channels; correlation; Decentralized; Delay; detection; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Formulations; Information, signal and communications theory; Markov decision process; Media Access Protocol; multiple access channel; Physical layer; Sensor fusion; sensor network; Sensors; sequential; Services and terminals of telecommunications; Signal and communications theory; Signal, noise; Simulation; Statistics; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Telemetry. Remote supervision. Telewarning. Remote control; Topology; Wireless communication; Wireless sensor networks; Working environment noise; Markov process; Ali-Silvey distance; Multiple access; Markov decision; Change detection; Gaussian channel; Wireless telecommunication; Geometric distribution; Star network; Sequential detection; Remote sensing; Optimal strategy; Simulation; correlation; sensor network; multiple access channel; Markov decision process; Delay time; Call centres; Sensor array; Multiple channel; Signal detection
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/T-WC.2008.070808

The problem of decentralized sequential detection with conditionally independent observations is studied. The sensors form a star topology with a central node called fusion center as the hub. The sensors make noisy observations of a parameter that changes from an initial state to a final state at a random time where the random change time has a geometric distribution. The sensors amplify and forward the observations over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. The optimal transmission strategy at each stage is shown to be the one that maximizes a certain Ali-Silvey distance between the distributions for the hypotheses before and after the change. Simulations demonstrate that the proposed analog technique has lower detection delays when compared with existing schemes. Simulations further demonstrate that the energy-constrained formulation enables better use of the total available energy than the power-constrained formulation in the change detection problem.