Adaptive Gradient-Based Methods for Adaptive Power Allocation in OFDM-Based Cognitive Radio Networks

• Published in: IEEE transactions on vehicular technology Vol. 63; no. 2; pp. 836 - 848
• Main Authors: Pao, Wei-Chen, Chen, Yung-Fang
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Allocations; Applied sciences; Cognitive radio; Cognitive radio (CR); Complexity; Computation; Computational complexity; Exact sciences and technology; gradient descent; Heuristic; Information, signal and communications theory; Interference constraints; Iterative methods; Mathematical analysis; Mathematical models; Multiplexing; Networks; OFDM; Orthogonal Frequency Division Multiplexing; orthogonal frequency-division multiplexing (OFDM); power allocation; Radiocommunication specific techniques; Radiocommunications; Resource management; Signal and communications theory; Telecommunications; Telecommunications and information theory; Vectors; Time variable channel; Resource allocation; Cognitive radio (CR); Iterative method; Subcarrier; Power allocation; Computational complexity; Adaptive method; Optimal solution; Descent method; Orthogonal frequency division multiplexing; System simulation; Resource management; Approximate solution; Gradient method; gradient descent; Comparative study; Radio communication; orthogonal frequency-division multiplexing (OFDM); Software radio
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2013.2272804

A gradient-based method is designed for power allocation in orthogonal-frequency-division-multiplexing (OFDM) -based cognitive radio networks. The resource allocation problem subject to a mutual interference constraint is considered. We utilize the gradient descent approach to allocate power to subcarriers in cognitive radio (CR) networks. The proposed gradient-based power allocation method with a well-designed step size can approximate the optimal solution within a few iterations. Due to the derived equation for power allocation in an adaptive manner, the proposed method is feasible for adaptive power allocation in time-varying channels. The analysis for the selection of the step size is presented in this paper. For comparison purposes, a greedy power-loading method requiring numerous iterations is also designed for this power allocation problem. The proposed gradient-based method and the greedy power-loading method both have a computational complexity of O(N), but the proposed gradient-based method requires far fewer iterations. As demonstrated in the simulation results, the proposed gradient-based method with the adaptive step size has a fast rate to achieve a near-optimal solution within an extremely small number of iterations and has quite a low computational complexity of O(N).