Intelligent Spectrum Resource Allocation Based on Joint Optimization in Heterogeneous Cognitive Radio

• Published in: IEEE transactions on emerging topics in computational intelligence Vol. 4; no. 1; pp. 5 - 12
• Main Authors: Liu, Xin, Jia, Min
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cognitive radio; Computer simulation; False alarms; Heterogeneous cognitive radio; intelligent spectrum resource allocation; Interference; Jamming; joint optimization; Optimization; Probability; Resource allocation; Resource management; Sensors; Throughput
• ISSN: 2471-285X; 2471-285X
• DOI: 10.1109/TETCI.2018.2865630

In conventional cognitive radio (CR), only when a primary user (PU) is detected to be absent, the idle spectrum can be accessed by a secondary user (SU), in addition, the allocation processes for spectrum resources of CR such as sensing time and transmission power are often independent. In this paper, to improve the SU's throughput in a heterogeneous CR, an intelligent spectrum resource allocation based on joint optimization is proposed. The proposed scheme allows the SU to access the PU' s spectrum not only in overlay mode but also in underlay mode. The SU accesses the spectrum with full power when PU is absent and with controlled power when PU is present. The transmission rates in the cases of perfect transmission, false alarm transmission, spectrum sharing transmission and interference transmission are analyzed, respectively, which are then used to achieve the average aggregate throughput of the SU. We have formulated spectrum resource allocation as a joint optimization problem of subchannel transmission power and spectrum sensing time, which can make the SU achieve the maximal throughput subject to the limits of minimal detection probability, maximal total power and maximal interference power for the SU. We propose an alternating diretion optimization (ADO) based joint optimization algorithm to solve the joint optimization problem. The simulation results have indicated that the proposed heterogeneous CR is superior to the traditional CR.