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Ordered Transmissions Schemes for Detection in Spatially Correlated Wireless Sensor Networks
- Source :
- IEEE Transactions on Communications. 69:1565-1577
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- The ordered transmissions scheme requires fewer sensor nodes to transmit their measurements than the conventional unordered transmissions scheme (UTS) in which all nodes transmit. Yet, it achieves the same error probability as UTS. For the practically relevant scenario in which the measurements of the sensor nodes are spatially correlated, we present a novel correlation-aware ordered transmissions scheme (CA-OTS) for the binary hypothesis testing problem with Gaussian statistics. It uses the timer scheme to make the nodes transmit their measurements in the decreasing order of the absolute values of the measurements without any node knowing the measurements of other nodes. CA-OTS applies to the general case where the hypotheses differ in the mean vector and covariance matrix, and markedly reduces the number of transmissions. It differs from the literature that assumes that the measurements of the nodes, when conditioned on the hypotheses, are statistically independent or the covariance matrix has a special structure. When the mean vector or covariance matrix is the same for the two hypotheses, we propose novel refinements that require even fewer transmissions. We also derive insightful upper bounds for them that apply to a general product-correlation model.
- Subjects :
- Computer science
Covariance matrix
Gaussian
05 social sciences
Structure (category theory)
050801 communication & media studies
020206 networking & telecommunications
02 engineering and technology
Upper and lower bounds
symbols.namesake
0508 media and communications
Signal-to-noise ratio
0202 electrical engineering, electronic engineering, information engineering
symbols
Node (circuits)
Timer
Electrical and Electronic Engineering
Wireless sensor network
Algorithm
Subjects
Details
- ISSN :
- 15580857 and 00906778
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Communications
- Accession number :
- edsair.doi...........035bf0caf687f7f85e5639307ab9091f