Fair subcarrier and power allocation for multiuser orthogonal frequency-division multiple access cognitive radio networks using a colonel blotto game

The problem of subcarrier allocation (SA) and power allocation (PA) for both the downlink and uplink of cognitive radio networks (CRNs) is studied. Two joint SA and PA schemes based on Blotto games are presented for orthogonal frequency-division multiple access (OFDMA)-based CRNs. In this work, the authors consider a more practical scenario by taking into account the correlation between adjacent subcarriers. In the proposed games, secondary users (SUs) simultaneously compete for subcarriers using a limited budget. In order to win as many good subcarriers as possible, the SUs are required to wisely allocate their budget subject to the transmit power, budget and interference temperature constraints. Two PA and budget allocation strategies are derived to enable fair sharing of spectrum among the SUs. It is shown that by manipulating the total budget available for each SU, competitive fairness can be enforced. In addition, the conditions to ensure the existence and uniqueness of Nash equilibrium (NE) in the proposed methods are established and algorithms which ensure convergence to NE are proposed. Simulation results show that the proposed methods can converge rapidly and allocate resources fairly and efficiently in correlated fading OFDMA channels.

[1]  Youngnam Han,et al.  A Competitive Fair Subchannel Allocation for OFDMA System Using an Auction Algorithm , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[2]  Michael L. Honig,et al.  Auction-Based Spectrum Sharing , 2006, Mob. Networks Appl..

[3]  T. Charles Clancy,et al.  Formalizing the interference temperature model , 2007 .

[4]  Hamid Aghvami,et al.  Cognitive Radio game for secondary spectrum access problem , 2009, IEEE Transactions on Wireless Communications.

[5]  Wenbo Wang,et al.  An uplink resource allocation scheme for OFDMA-based cognitive radio networks , 2009, Int. J. Commun. Syst..

[6]  Moh Lim Sim,et al.  Game theoretic approach for channel assignment and power control with no-internal-regret learning in wireless ad hoc networks , 2008, IET Commun..

[7]  Ha H. Nguyen,et al.  Resource Allocation for OFDM-Based Cognitive Radio Multicast Networks , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[8]  Kwang Bok Lee,et al.  Transmit power adaptation for multiuser OFDM systems , 2003, IEEE J. Sel. Areas Commun..

[9]  H.-H. Chen,et al.  Optimal distributed joint frequency, rate and power allocation in cognitive OFDMA systems , 2008, IET Commun..

[10]  Dong-Ho Cho,et al.  Fairness-Aware Adaptive Resource Allocation Scheme in Multihop OFDMA Systems , 2007, IEEE Communications Letters.

[11]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[12]  Zhigang Cao,et al.  Diversity-Multiplexing Tradeoff in OFDMA Systems with Coherence Bandwidth Splitting , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[13]  Zhu Han,et al.  Fair multiuser channel allocation for OFDMA networks using Nash bargaining solutions and coalitions , 2005, IEEE Transactions on Communications.

[14]  Hoon Kim,et al.  A proportional fair scheduling for multicarrier transmission systems , 2004 .

[15]  Andrea J. Goldsmith,et al.  Degrees of freedom in adaptive modulation: a unified view , 2001, IEEE Trans. Commun..

[16]  Alexander Matros,et al.  A Blotto Game with Incomplete Information , 2009 .

[17]  Seong-Lyun Kim,et al.  Joint subcarrier and power allocation in uplink OFDMA systems , 2005, IEEE Communications Letters.

[18]  Hamid Aghvami,et al.  Interference-limited resource allocation for cognitive radio in orthogonal frequency-division multiplexing networks , 2008, IET Commun..

[19]  Eytan Modiano,et al.  Wireless channel allocation using an auction algorithm , 2006, IEEE Journal on Selected Areas in Communications.

[20]  W. C. Jakes,et al.  Microwave Mobile Communications , 1974 .