Wu, J.; Qiu, Z.; Dai, M.; Bao, J.; Xu, X.; Cao, W. Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things. Sensors2024, 24, 688.
Wu, J.; Qiu, Z.; Dai, M.; Bao, J.; Xu, X.; Cao, W. Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things. Sensors 2024, 24, 688.
Wu, J.; Qiu, Z.; Dai, M.; Bao, J.; Xu, X.; Cao, W. Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things. Sensors2024, 24, 688.
Wu, J.; Qiu, Z.; Dai, M.; Bao, J.; Xu, X.; Cao, W. Distributed Sequential Detection for Cooperative Spectrum Sensing in Cognitive Internet of Things. Sensors 2024, 24, 688.
Abstract
Considering the spectrum shortage problem of IoT devices, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources, so that IoT devices can access it and meanwhile avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of the PU’s signal detection in IoT devices, the issue about the stopping time and decision cost arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the stopping time and cost function for IoT devices, and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal stopping time problem as a finite horizon problem, and solve the threshold of the optimal decision rule by dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various cost of each observation taken and thresholds.
Keywords
internet of thing; cooperative spectrum sensing; sequential detection rule; stopping time; cost function
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
