Receiver Diversity for Distributed Detection in Wireless Sensor Networks

2012 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad A. Al-Jarrah ◽  
Mohammad M. Al-Ibrahim
Keyword(s):  
Detection System ◽  
Block Codes ◽  
Distributed Detection ◽  
Wireless Sensor ◽  
Fusion Center ◽  
Receiver Diversity ◽  
Space Time Block Codes ◽  
Optimal Fusion ◽  
Central Device

In this paper, parallel distributed detection in wireless sensor network (WSN) is considered where the sensors process the observations to make local decisions and send these decisions to a central device called fusion center. Receiver diversity technique is proposed here for the distributed detection system in order to enhance the system reliability by improving the detection performance. The fusion center is assumed to be multiple antennas device in order to imply the idea of receiver diversity. Different combining schemes at the fusion center side are used to reduce the fading effects in the case of receiver diversity. Transmitter diversity is also considered in this paper. Cooperative sensors are assumed in order to obtain Alamouti space time block codes. Optimal and sub-optimal fusion rules are derived for each case study. Simulation results show the performance improvement obtained as compared to the conventional distributed detection system in which no diversity is used.

Cooperative Space Time Coding for Semi Distributed Detection in Wireless Sensor Networks

2012 ◽  
Vol 2 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Mohammad A. Al-Jarrah ◽  
Nedal K. Al-Ababneh ◽  
Mohammad M. Al-Ibrahim ◽  
Rami A. Al-Jarrah
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Parallel Architecture ◽  
Block Codes ◽  
Space Time ◽  
Distributed Detection ◽  
Wireless Sensor ◽  
Space Time Coding ◽  
Space Time Block Codes ◽  
Central Device

Parallel distributed detection in wireless sensor networks (WSNs) is considered in this paper. In parallel architecture, sensors process the observations to make local decisions and send them to a central device called fusion center. Parallel architecture is assumed in this paper with cooperative sensors in order to obtain Alamouti space time block codes (STBCs). A similar idea was discussed by Vosoughi and Ahmadi (2009). Although the likelihood ratio provided in that paper is correct, the simulation results don’t make sense. In this paper, we are going to prove that the results provided in (Vosoughi & Ahmadi, 2009) are not correct. Upper bound for the detection performance is also derived. Furthermore, suboptimal fusion rules are derived to support our results. Moreover, correct results are shown in this paper.

scholarly journals A Soft–Hard Combination Decision Fusion Scheme for a Clustered Distributed Detection System with Multiple Sensors

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4370 ◽  
Author(s):  
Junhai Luo ◽  
Xiaoting He
Keyword(s):  
Detection System ◽  
Decision Fusion ◽  
Detection Performance ◽  
Distributed Detection ◽  
Fusion Center ◽  
Soft Decision ◽  
Multiple Sensors ◽  
Fusion Scheme ◽  
Hard Decision ◽  
Centralized System

In the distributed detection system with multiple sensors, there are two ways for local sensors to deliver their local decisions to the fusion center (FC): a one-bit hard decision and a multiple-bit soft decision. Compared with the soft decision, the hard decision has worse detection performance due to the loss of sensing information but has the main advantage of smaller communication costs. To get a tradeoff between communication costs and detection performance, we propose a soft–hard combination decision fusion scheme for the clustered distributed detection system with multiple sensors and non-ideal communication channels. A clustered distributed detection system is configured by a fuzzy logic system and a fuzzy c-means clustering algorithm. In clusters, each local sensor transmits its local multiple-bit soft decision to its corresponding cluster head (CH) under the non-ideal channel, in which a simple and efficient soft decision fusion method is used. Between clusters, the fusion center combines all cluster heads’ one-bit hard decisions into a final global decision by using an optimal fusion rule. We show that the clustered distributed system with the proposed scheme has a good performance that is close to that of the centralized system, but it consumes much less energy than the centralized system at the same time. In addition, the system with the proposed scheme significantly outperforms the conventional distributed detection system that only uses a hard decision fusion. Using simulation results, we also show that the detection performance increases when more bits are delivered in the soft decision in the distributed detection system.

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