What is it about?
Cognitive radio sensor networks can make better use of scarce wireless spectrum, but their performance depends on correctly identifying when licensed channels are free. In practice, spectrum sensing is imperfect: noise can cause false alarms or missed detections, while battery-powered sensor nodes must also conserve energy. This work develops a multi-hop uneven clustering and routing protocol for cognitive radio sensor networks assisted by an active intelligent reflecting surface. The method considers imperfect spectrum sensing explicitly and offers three ways to determine an appropriate energy-detection threshold, including an approach that maximizes sensing accuracy. It then combines sensing accuracy, available channels, residual energy, and communication distance when choosing cluster heads, forming clusters, and selecting relay nodes. In this way, nodes that can sense the spectrum more reliably and have better channel availability are given greater responsibility for forwarding data, while uneven clustering helps balance energy use across the network. The protocol is evaluated through simulations involving a three-ring network topology, active reflecting-surface assistance, and multiple primary users.
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Why is it important?
Many existing routing protocols for cognitive radio sensor networks either rely heavily on direct node-to-sink communication or assume that spectrum sensing is perfectly accurate. These assumptions can become problematic in realistic wireless environments, where false alarms waste spectrum opportunities and missed detections can cause interference and packet loss. The distinctive feature of this work is that spectrum-sensing reliability is not treated as a separate physical-layer issue; instead, it directly influences clustering and multi-hop routing decisions. The proposed framework therefore links sensing quality, channel availability, and energy balancing within one routing process. In the reported simulations, the method improved packet delivery ratio by up to 74% and extended network lifetime by up to 194% compared with the benchmark protocols considered, showing the potential value of jointly addressing sensing uncertainty and energy-efficient routing in long-lived wireless monitoring systems.
Perspectives
What I find particularly valuable about this work is the way it connects uncertainty in spectrum sensing with higher-level network decisions. Rather than assuming that sensing results are always correct, the routing process recognizes that communication decisions should reflect how trustworthy those sensing results actually are. From my perspective, this provides a useful direction for designing more practical cognitive sensor networks, because reliability, spectrum access, and energy consumption are inherently coupled rather than independent concerns. The work also illustrates how active reflecting surfaces can support network-level energy and reliability objectives rather than being used only as a physical-layer signal-enhancement technology. A natural next step is to move toward more realistic near-field models, where individual reflecting elements may experience different amplitudes and phase shifts, and ultimately to evaluate such sensing-aware routing strategies under experimental or hardware-assisted conditions.
Chair, IEEE PES EICC Task Force on AI-Enabled Resilience of CPES|Clarivate HCR|AE: IEEE TSG/TSTE/TII Yang Li
Northeast Electric Power University
Read the Original
This page is a summary of: An Imperfect Spectrum Sensing-based Inter-ring Energy Balance-oriented Multi-hop Uneven Clustering Routing Protocol for Active IRS-assisted CRSNs, IEEE Sensors Journal, January 2026, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/jsen.2026.3733071.
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