TY - JOUR
T1 - Spectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks
AU - Cohen, Kobi
AU - Leshem, Amir
N1 - Funding Information:
Manuscript received April 8, 2018; revised August 26, 2018 and September 22, 2018; accepted September 22, 2018. Date of publication October 2, 2018; date of current version October 12, 2018. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Chandra Ramabhadra Murthy. The work of K. Cohen was supported by the U.S.-Israel Binational Science Foundation under Grant 2017723. The work of A. Leshem was supported by the ISF Grant 903/2013. A short version of this paper was presented at IEEE International Symposium on Information Theory 2018 [1]. (Corresponding author: Kobi Cohen.) K. Cohen is with the Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel (e-mail:, yakovsec@bgu.ac.il).
Publisher Copyright:
© 1991-2012 IEEE.
PY - 2018/11/15
Y1 - 2018/11/15
N2 - We consider a binary hypothesis testing problem using wireless sensor networks (WSNs). The decision is made by a fusion center and is based on received data from the sensors. We focus on a spectrum and energy efficient transmission scheme used to reduce the spectrum usage and energy consumption during the detection task. We propose a spectrum and energy efficient multiple access (SEEMA) transmission protocol that performs a censoring-Type transmission based on the density of observations using multiple access channels (MAC). Specifically, in SEEMA, only sensors with highly informative observations transmit their data in each data collection. The sensors transmit a common shaping waveform and the fusion center receives a superposition of the analog transmitted signals. SEEMA has important advantages for detection tasks in WSNs. First, it is highly energy and bandwidth efficient due to transmission savings and narrowband transmission over MAC. Second, it can be implemented by simple dumb sensors (oblivious to observation statistics, and local data processing is not required), which simplifies the implementation as compared to existing MAC transmission schemes for detection in WSNs. We establish a finite sample analysis and an asymptotic analysis of the error probability with respect to the network size and provide system design conditions to obtain the exponential decay of the error. Specific performance analysis is developed for common non-i.i.d. observation scenarios, including local i.i.d. observations, and Markovian correlated observations. Numerical examples demonstrate SEEMA performance.
AB - We consider a binary hypothesis testing problem using wireless sensor networks (WSNs). The decision is made by a fusion center and is based on received data from the sensors. We focus on a spectrum and energy efficient transmission scheme used to reduce the spectrum usage and energy consumption during the detection task. We propose a spectrum and energy efficient multiple access (SEEMA) transmission protocol that performs a censoring-Type transmission based on the density of observations using multiple access channels (MAC). Specifically, in SEEMA, only sensors with highly informative observations transmit their data in each data collection. The sensors transmit a common shaping waveform and the fusion center receives a superposition of the analog transmitted signals. SEEMA has important advantages for detection tasks in WSNs. First, it is highly energy and bandwidth efficient due to transmission savings and narrowband transmission over MAC. Second, it can be implemented by simple dumb sensors (oblivious to observation statistics, and local data processing is not required), which simplifies the implementation as compared to existing MAC transmission schemes for detection in WSNs. We establish a finite sample analysis and an asymptotic analysis of the error probability with respect to the network size and provide system design conditions to obtain the exponential decay of the error. Specific performance analysis is developed for common non-i.i.d. observation scenarios, including local i.i.d. observations, and Markovian correlated observations. Numerical examples demonstrate SEEMA performance.
KW - Detection
KW - large deviations
KW - multiple access channel (MAC)
KW - wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=85054471120&partnerID=8YFLogxK
U2 - 10.1109/TSP.2018.2873512
DO - 10.1109/TSP.2018.2873512
M3 - Article
AN - SCOPUS:85054471120
VL - 66
SP - 5988
EP - 6001
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
SN - 1053-587X
IS - 22
M1 - 8478801
ER -