Wireless Communications
Introduction to Space-Time Wireless Communications
Introduction to Space-Time Wireless Communications
IEEE Transactions on Mobile Computing
IEEE Transactions on Information Theory
Cooperative spectrum sensing in cognitive radios with incomplete likelihood functions
IEEE Transactions on Signal Processing
NIST Handbook of Mathematical Functions
NIST Handbook of Mathematical Functions
Optimal linear fusion for distributed detection via semidefinite programming
IEEE Transactions on Signal Processing
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
Utilization of Location Information in Cognitive Wireless Networks
IEEE Wireless Communications
Cognitive Radio: A Communications Engineering View
IEEE Wireless Communications
IEEE Transactions on Wireless Communications
Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks
IEEE Transactions on Wireless Communications - Part 2
Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks
IEEE Transactions on Wireless Communications
Exploiting location awareness toward improved wireless system design in cognitive radio
IEEE Communications Magazine
A survey on spectrum management in cognitive radio networks
IEEE Communications Magazine
Capacity- and Bayesian-Based Cognitive Sensing with Location Side Information
IEEE Journal on Selected Areas in Communications
Concepts and results for 3D digital terrain-based wave propagation models: an overview
IEEE Journal on Selected Areas in Communications
Hi-index | 0.00 |
Without an efficient way to achieve the reliability of the decision, the implementation of weighted data fusion is limited in the hard decision combination for cooperative spectrum sensing. To address this problem, a new cooperative spectrum sensing scheme based on the location information of the primary user (PU) and cognitive radio (CR) is proposed. In the new scheme, depending on the location information, the channel condition between the PU and each CR is obtained at the fusion center (FC), with which the local sensing reliability is first achieved. Then we calculate the transmission reliability between the CR and FC. Based on both the local sensing reliability and the transmission reliability, the combining weighting factor is determined for optimal data fusion. On the basis of this proposed scheme, we study the global sensing false alarm and detection probabilities, derive the expressions to obtain the optimal local sensing threshold, and perform an error analysis that demonstrates the impact of imperfect channel knowledge. Using both analytical and simulation methods, we find that the proposed scheme achieves better performance compared with the conventional logical fusion rules in the hard decision combination for cooperative spectrum sensing.