Spectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks

被引:10
|
作者
Cohen, Kobi [1 ]
Leshem, Amir [2 ]
机构
[1] Ben Gurion Univ Negev, Dept Elect & Comp Engn, IL-84105 Beer Sheva, Israel
[2] Bar Ilan Univ, Fac Engn, IL-52900 Ramat Gan, Israel
关键词
Detection; multiple access channel (MAC); wireless sensor networks; large deviations; DISTRIBUTED DETECTION; DECENTRALIZED DETECTION; SIGNAL-DETECTION; FUSION; TRANSMISSION; PERFORMANCE; LIFETIME;
D O I
10.1109/TSP.2018.2873512
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 narrowhand 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.
引用
收藏
页码:5988 / 6001
页数:14
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