Estimation of Primary Channel Mean Period Based on State Transition Probability in Cognitive Radio

IEEE Access

Xiang Gao¹  Weiqin Li¹  Guoliang Shentu² 

[1] School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, China;Shandong Guoyao Quantum Lidar Technology Company Ltd., Jinan, China;

关键词: Cognitive radio;    dynamic spectrum access;    spectrum sensing;    mean period;   

DOI  :  10.1109/ACCESS.2022.3175852

来源: DOAJ

【 摘 要 】

Primary channel mean period plays an important role in improving the performance of Dynamic Spectrum Access (DSA), because many algorithms to improve the performance of Cognitive Radio (CR) need to use the channel mean period as a prior knowledge. Secondary Users (SUs) can obtain statistics of the primary channel by spectrum sensing. However, SUs’ estimation of the mean period is inaccurate due to errors in the spectrum sensing in the real world, which will lead to performance degradation of CR systems. In this paper, we use a two-state Markov chain to model channel states, and use state transition probability to analyze the influence of sensing errors on the mean period. At the same time, we derive the estimation formula of the mean period of the original channel. Simulation results confirm that the proposed estimation method is superior to the existing estimation methods, and can accurately estimate the original period even with high sensing error probability.

【 授权许可】

Unknown