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Robust Power Allocation for OFDM-Based Cognitive Radio Networks under Signal-to-Interference-plus-Noise-Ratio Constraints

Yongjun Xu 1,2, Qianbin Chen 1, Lun Tang 1, and Xiaoge Huang 1
1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
2. The State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China
Abstract—Traditional power allocation schemes in Orthogonal Frequency Division Multiplexing (OFDM) based Cognitive Radio Networks (CRNs) are achieved under perfect channel state information (i.e., exact parameter information). Due to channel estimation errors and feedback delays, however, channel uncertainties are inevitable in practical CRNs. In this paper, considering bounded channel uncertainties, a robust power allocation algorithm is proposed to minimize the total transmit power of Secondary Users (SUs) subject to the interference temperature constraint of primary user and the received Signal-to-Interference-plus-Noise Ratio (SINR) constraint of SU where the non-convex optimization problem is converted into a convex optimization problem that is solved by dual decomposition theory. Numerical results demonstrate the effectiveness of the proposed algorithm by comparing with the non-robust algorithm in the aspect of suppressing the effect of parameter uncertainties.

Index Terms—Cognitive radio, robust power allocation, parametric uncertainties, robustness

Cite: Yongjun Xu, Qianbin Chen, Lun Tang, and Xiaoge Huang, "Robust Power Allocation for OFDM-Based Cognitive Radio Networks under Signal-to-Interference-plus-Noise-Ratio Constraints," Journal of Communications, vol. 12, no. 1, pp. 8-16, 2017. Doi: 10.12720/jcm.12.1.8-16
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