Research Article
Resource Allocation in OFDM-Based Cognitive Radios Under Proportional Rate Constraint
@INPROCEEDINGS{10.1007/978-3-319-78139-6_42, author={Hongzhi Wang and Yongfei Yan and Mingyue Zhou}, title={Resource Allocation in OFDM-Based Cognitive Radios Under Proportional Rate Constraint}, proceedings={Communications and Networking. 12th International Conference, ChinaCom 2017, Xi’an, China, October 10-12, 2017, Proceedings, Part II}, proceedings_a={CHINACOM}, year={2018}, month={4}, keywords={Cognitive radio Orthogonal frequency division multiplexing (OFDM) Resource allocation Proportional fairness Spectrum sharing}, doi={10.1007/978-3-319-78139-6_42} }- Hongzhi Wang
Yongfei Yan
Mingyue Zhou
Year: 2018
Resource Allocation in OFDM-Based Cognitive Radios Under Proportional Rate Constraint
CHINACOM
Springer
DOI: 10.1007/978-3-319-78139-6_42
Abstract
The objective of this paper is to optimize the power allocation to maximize the total rate of secondary users (SUs) under the SU total transmit power constraint and primary user (PU) interference temperature constraint, a proportional rate constraint is also used to assure that each SU can achieve fairness. The power allocation problem is not a convex optimization problem, which can be converted to a convex optimization problem without introducing auxiliary variables. To reduce the burden of information exchange and computational complexity, PU interference temperature constraint can be decoupled to an average interference constraint. The Lagrangian duality method is used to solve the optimal transmission power. Numerical results show that the proposed algorithm not only improves the rate fairness of each SU, but also guarantees the quality of service (QoS) of PU.
