• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Resource Allocation with Proportional Rate In Cognitive Wireless Network: An Immune Clonal Optimization Scheme


Abstract

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.


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Cite this article

[IEEE Style]
ZhengYi Chai, DeXian Zhang and SiFeng Zhu, "Resource Allocation with Proportional Rate In Cognitive Wireless Network: An Immune Clonal Optimization Scheme," KSII Transactions on Internet and Information Systems, vol. 6, no. 5, pp. 1286-1302, 2012. DOI: 10.3837/tiis.2012.05.002

[ACM Style]
Chai, Z., Zhang, D., and Zhu, S. 2012. Resource Allocation with Proportional Rate In Cognitive Wireless Network: An Immune Clonal Optimization Scheme. KSII Transactions on Internet and Information Systems, 6, 5, (2012), 1286-1302. DOI: 10.3837/tiis.2012.05.002