Resource allocation in orthogonal frequency division multiple access-based cognitive radio systems with minimum rate constraints

• Published in: International journal of communication systems Vol. 27; no. 8; pp. 1147 - 1159
• Main Authors: Li, Li, Xu, Changqing, Fan, Pingzhi, He, Jian
• Format: Journal Article
• Language: English
• Published: Chichester Blackwell Publishing Ltd 01.08.2014; Wiley Subscription Services, Inc
• Subjects: Algorithms; Cognitive radio; cognitive radio (CR); Frequency division; Interference; minimum rate constraints; Optimization; orthogonal frequency division multiple access (OFDMA); Plutonium; Resource allocation; Thresholds
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.2400

SUMMARYIn this paper, resource allocation problem in orthogonal frequency division multiple access‐based cognitive radio (CR) systems to maintain minimum transmission rate constraints of CR users (CRUs) with the specified interference thresholds is investigated. Firstly, a single primary user (PU) CR system is considered, and a suboptimal resource allocation algorithm to maximize the sum transmission rate of all CRUs is proposed. Secondly, the single‐PU scenario is extended to multiple‐PU case, and an asymptotically optimal resource allocation algorithm is proposed using dual methods subject to constraints on both interference thresholds of PUs and total transmit power of all CRUs. Analysis and numerical results show that, in contrast to classical resource allocation algorithms, the proposed algorithm can achieve higher transmission rate and guarantee each CRU's minimum transmission rate in both scenarios. Copyright © 2012 John Wiley & Sons, Ltd. In this paper, resource allocation in cognitive radio systems based on orthogonal frequency division multiple access with minimum rate constraints of cognitive radio users (CRUs) is investigated to maximize the sum transmission rate of all CRUs while limit the interference introduced to primary users (PUs) under specified thresholds. In single PU scenario, a suboptimal resource allocation algorithm with low complexity is proposed and extended to general case with multiple PUs, resulting an optimal resource allocation algorithm using dual methods.