Abstract
Channel allocation is an important part of cognitive radio(CR), and has received intensive studies in recent years. Previous works of channel allocation haven’t taken the social relationship between primary users(PUs) and secondary users(SUs) into consideration. As a result, these allocation schemes ignore the willingness of CR users and may not adapt a personalized environment. Moreover, the traditional channel allocation schemes do not have the capability to protect the network performance from being hurt by some ill-behaved nodes. To tackle this challenge, we first introduce the social relationship into channel allocation and make some definitions about the social attributes. Then, we propose a Sociability-Assisted Channel Allocation Scheme(SACAS) which takes both the social relationship and the channel condition into consideration. Then, we use semi-definite programming(SDP) to obtain the optimal solution of SACAS. The simulation results show the superiority of SACAS over traditional algorithms.
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Li, Z., Jing, T., Huo, Y., Pan, L., Zhou, W. (2014). Channel Allocation in Sociability-Assisted Cognitive Radio Networks Using Semi-definite Programming. In: Cai, Z., Wang, C., Cheng, S., Wang, H., Gao, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2014. Lecture Notes in Computer Science, vol 8491. Springer, Cham. https://doi.org/10.1007/978-3-319-07782-6_47
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DOI: https://doi.org/10.1007/978-3-319-07782-6_47
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