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Noncoherent Decision Fusion over Fading Hybrid MACs in Wireless Sensor Networks
Shoujun Liu1, Kehao Wang2, Kezhong Liu3
1School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China. lsj@whut.edu.cn.
Sensors (Basel, Switzerland)
|January 6, 2019
Summary
This study introduces a hybrid multi-access channel (MAC) for wireless sensor networks, improving noncoherent detection. Novel fusion rules offer optimal performance and efficient alternatives for resource-constrained networks.
Area of Science:
- Wireless Sensor Networks
- Signal Processing
- Communication Systems
Background:
- Noncoherent detection is crucial for wireless sensor networks (WSNs).
- Existing fusion rules often struggle with resource constraints and hybrid channel access.
- Integrating multi-access channel (MAC) characteristics into fusion rules is an open challenge.
Purpose of the Study:
- To develop optimal and low-complexity decision fusion rules for noncoherent detection in WSNs using a hybrid MAC.
- To analyze the performance of proposed fusion rules under Rayleigh fading.
- To compare the effectiveness of the hybrid MAC with conventional MACs.
Main Methods:
- Developed a likelihood ratio (LR)-based optimal fusion rule.
- Proposed three low-complexity sub-optimal rules: weighed energy detector (WED), deflection-coefficient-maximization (DCM), and two-step (TS).
- Analyzed performance under Rayleigh fading and varying channel signal-to-noise ratio (SNR) via theoretical analysis and simulations.
Main Results:
- The LR-based rule is optimal but computationally intensive.
- WED, DCM, and TS rules offer efficient alternatives with performance linked to SNR.
- The hybrid MAC with proposed fusion rules enhances detection performance at medium channel SNR compared to conventional MACs.
Conclusions:
- The proposed fusion rules effectively address decision fusion in WSNs with hybrid MACs.
- The hybrid MAC offers a performance advantage in medium SNR conditions.
- Low-complexity rules provide practical solutions for resource-limited WSNs.
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