A Coalitional Game-Based Algorithm for OFDMA Resource Allocation in Multicast Cognitive Radio Networks

• Published in: Wireless personal communications Vol. 80; no. 1; pp. 415 - 427
• Main Authors: Tan, Chee Keong, Chuah, Teong Chee, Tan, Su Wei
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.01.2015
• Subjects: Algorithms; Associations; Channels; Communications Engineering; Computer Communication Networks; Dynamics; Engineering; Formations; Gain; Multicast; Networks; Signal,Image and Speech Processing; Multicast; OFDMA; Cognitive radio; Resource allocation; Coalitional game theory
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-014-2018-2

This letter investigates resource allocation for orthogonal frequency division multiple access (OFDMA)-based multicast cognitive radio networks (MCRNs) under the consideration of primary users’ activities. Due to the heterogeneity of channel gains among secondary users (SUs), the existing multicast schemes are highly conservative and spectrally inefficient. To address this issue, we formulate a novel multicasting problem for MCRNs. This new formulation optimally and adaptively exploits multiuser diversity of OFDMA through dynamic group formation, which clusters SUs within a multicast group into multiple smaller subgroups (coalitions) based on their channel gains. Subcarriers and power are then allocated to these subgroups to maximize aggregate data rate (ADR) of the system. A coalitional game theory is adopted to model the group formation where SUs are allowed to form coalitions to compete for resources. A novel cognitive multicast coalitional game (CMCG) is proposed for SUs to self-organize to reach multi-coalitional equilibrium where optimality can be obtained. Simulation results show that the proposed CMCG algorithm significantly improves the system ADR as compared to the conventional unicast and multicast schemes.