Active Reconfigurable Intelligent Surface Enhanced Spectrum Sensing for Cognitive Radio Networks
Jungang Ge, Ying-Chang Liang, Sumei Sun, Yonghong Zeng, Zhidong Bai

TL;DR
This paper introduces an active RIS-assisted spectrum sensing system for cognitive radio networks, enhancing detection performance by signal amplification and interference mitigation, with an optimization algorithm for the reflecting coefficients.
Contribution
It proposes a novel active RIS-based spectrum sensing framework with an iterative WMMSE optimization algorithm for RCM, improving detection probability under power and interference constraints.
Findings
Active RIS outperforms passive RIS in weak interference scenarios.
Passive RIS performs better under strong interference with the same power budget.
The WMMSE-based RCM optimization effectively enhances spectrum sensing performance.
Abstract
In opportunistic cognitive radio networks, when the primary signal is very weak compared to the background noise, the secondary user requires long sensing time to achieve a reliable spectrum sensing performance, leading to little remaining time for the secondary transmission. To tackle this issue, we propose an active reconfigurable intelligent surface (RIS) assisted spectrum sensing system, where the received signal strength from the interested primary user can be enhanced and underlying interference within the background noise can be mitigated as well. In comparison with the passive RIS, the active RIS can not only adapt the phase shift of each reflecting element but also amplify the incident signals. Notably, we study the reflecting coefficient matrix (RCM) optimization problem to improve the detection probability given a maximum tolerable false alarm probability and limited sensing…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Satellite Communication Systems · Indoor and Outdoor Localization Technologies
