A new perspective on spectrum sensing for cognitive sensor networks

Abstract

We address an important aspect of spectrum sensing that has been often overlooked by researches. While the cognitive radio is supposed to be aware of its surrounding, existing works do not consider the characteristics of secondary users to find the optimal sensing period. In this paper, a hybrid sensing method is presented that finds the optimal sensing period according to the characteristics of both primary and secondary users. Based on a continuous time Markov chain model, the proposed method adaptively varies its parameters to avoid unnecessary sensing tasks. In addition, the proposed method guarantees the priority of licensed users and spectrum opportunities to be discovered by cognitive users. Finally, the hybrid method is compared with a non-hybrid technique. It is concluded that the proposed method outperforms the non-hybrid method in terms of transmission efficiency.

Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends

“…Their simulation results show that this algorithm can acquire a 30% gain in the ratio of frequency spectrum utilization than the conventional method. Zahmati et al [ 70 ] presented a hybrid sensing method that finds the optimal sensing period according to the characteristics of both PU and SUs. The proposed method varies its parameters adaptively to avoid unnecessary sensing tasks based on a continuous time Markov chain model.…”

A Nonlinearity Mitigation Method for a Broadband RF Front-End in a Sensor Based on Best Delay Searching

“…At present, most studies regarding CR-WSN in published papers focus on the development of sensing techniques [7,8,9,10,11,12,13]. The literature [7] provides a spectrum-sensing technique based on the autocorrelation of received samples and decides whether signals exist by means of a derived Euclidean distance.…”