@article{Chen_Fang_Zhao_2018, title={Probabilistical Robust Power Control for Cognitive Radio Networks under Interference Uncertainty Conditions}, volume={14}, url={https://online-journals.org/index.php/i-joe/article/view/8967}, DOI={10.3991/ijoe.v14i07.8967}, abstractNote={<p class="0abstract"><a name="OLE_LINK11"></a><a name="OLE_LINK12"></a><span lang="EN-US">The focus of this paper is to find a robust power control strategy with uncertain noise plus interference (NI) in </span><span lang="EN-US">cognitive radio networks (</span><span lang="EN-US">CRNs</span><span lang="EN-US">)in an </span><span lang="EN-US">under orthogonal frequency-division multiplexing (OFDM) framework. The optimization problem is formulated to maximize </span><span lang="EN-US">the </span><span lang="EN-US">data rate of secondary users (SUs) under the constraints o</span><span lang="EN-US">f</span><span lang="EN-US"> transmission power of each SU, probabilistic the transmit rate of each SU at each subcarrier and robust interference constraint of primary user. In consideration of the feedback errors from the quantization </span><span lang="EN-US">due to</span><span lang="EN-US"> uniform distribution, the probabilistic constraint is transformed into closed forms. By using Lagrange relaxation of the coupling constraints method and subgradient iterative algorithm in a distributed way, we solve this dual problem. Numerical simulation results show that our proposed algorithm is superior to the robust power control scheme based on interference gain worst case approach and non-robust algorithm without quantization error in perfect channels in the improvement of data rate of each SU, convergence speed and computational complexity.</span></p>}, number={07}, journal={International Journal of Online and Biomedical Engineering (iJOE)}, author={Chen, Lingling and Fang, Zhiyi and Zhao, Xiaohui}, year={2018}, month={Jul.}, pages={pp. 90–107} }