Cooperative energy spectrum sensing has been widely applied in cognitive radio （CR） networks. In this paper, two cooperative sensing algorithms based on the received signals＇ correlation matrix were proposed. The f...Cooperative energy spectrum sensing has been widely applied in cognitive radio （CR） networks. In this paper, two cooperative sensing algorithms based on the received signals＇ correlation matrix were proposed. The first proposed algorithm made use of both diagonal elements and non-diagonal elements in the cooperative scheme. In the second algorithm, when the sensing station can obtain the information of the channel gains between the primary user and the sensing nodes, the weighted linear model can be adopted to improve the sensing performance. This paper analyzed the effectiveness of these two proposed coopera- tive algorithms and demonstrated that they can considerably improve the sensing performance compared with the traditional linear cooperative sensing algorithms. Simulation results showed that the sensing performance can be significantly enhanced by using the proposed algorithms, especially when the number of cooperative nodes is large.展开更多
基金Supported by the National Natural Science Foundation of China(No. 60832008)the National Key Basic Research and Development (973) Program of China (No. 2007CB310608)
文摘Cooperative energy spectrum sensing has been widely applied in cognitive radio （CR） networks. In this paper, two cooperative sensing algorithms based on the received signals＇ correlation matrix were proposed. The first proposed algorithm made use of both diagonal elements and non-diagonal elements in the cooperative scheme. In the second algorithm, when the sensing station can obtain the information of the channel gains between the primary user and the sensing nodes, the weighted linear model can be adopted to improve the sensing performance. This paper analyzed the effectiveness of these two proposed coopera- tive algorithms and demonstrated that they can considerably improve the sensing performance compared with the traditional linear cooperative sensing algorithms. Simulation results showed that the sensing performance can be significantly enhanced by using the proposed algorithms, especially when the number of cooperative nodes is large.
