Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game

We consider dynamic spectrum access among cognitive radios from an adaptive, game theoretic learning perspective. Spectrum-agile cognitive radios compete for channels temporarily vacated by licensed primary users in order to satisfy their own demands while minimizing interference. For both slowly varying primary user activity and slowly varying statistics of "fast" primary user activity, we apply an adaptive regret based learning procedure which tracks the set of correlated equilibria of the game, treated as a distributed stochastic approximation. This procedure is shown to perform very well compared with other similar adaptive algorithms. We also estimate channel contention for a simple CSMA channel sharing scheme.

[1]  S. Hart,et al.  A Reinforcement Procedure Leading to Correlated Equilibrium , 2001 .

[2]  K. Ramchandran,et al.  Detecting primary receivers for cognitive radio applications , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[3]  Cristina Comaniciu,et al.  Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[4]  John B. Moore,et al.  Hidden Markov Models: Estimation and Control , 1994 .

[5]  R. Aumann.  Correlated Equilibrium as an Expression of Bayesian Rationality Author ( s ) , 1987 .

[6]  D. Goodman,et al.  A New Framework for Power Control in Wireless Data Networks: Games, Utility, and Pricing , 2002 .

[7]  S. Hart,et al.  Uncoupled Dynamics Do Not Lead to Nash Equilibrium , 2003 .

[8]  Joseph Mitola.  Cognitive Radio for Flexible Mobile Multimedia Communications , 2001, Mob. Networks Appl..

[9]  Cem U. Saraydar,et al.  Pricing and power control in a multicell wireless data network , 2001, IEEE J. Sel. Areas Commun..

[10]  U. Berthold,et al.  Guidelines for designing OFDM overlay systems , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[11]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[12]  Gang George Yin,et al.  Regime Switching Stochastic Approximation Algorithms with Application to Adaptive Discrete Stochastic Optimization , 2004, SIAM J. Optim..

[13]  S. Hart,et al.  A simple adaptive procedure leading to correlated equilibrium , 2000 .

[14]  David J. Goodman,et al.  Network Assisted Power Control for Wireless Data , 2001, Mob. Networks Appl..

[15]  David J. Goodman,et al.  Power control for wireless data , 1999, 1999 IEEE International Workshop on Mobile Multimedia Communications (MoMuC'99) (Cat. No.99EX384).

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

[17]  Qing Zhao,et al.  Power control in spectrum overlay networks: How to cross a multi-lane highway , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[18]  Josef Hofbauer,et al.  Stochastic Approximations and Differential Inclusions II: Applications , 2005 .

[19]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[20]  H. Kushner,et al.  Stochastic Approximation and Recursive Algorithms and Applications , 2003 .

[21]  Vikram Krishnamurthy,et al.  Transmission control in cognitive radio systems with latency constraints as a switching control dynamic game , 2008, 2008 47th IEEE Conference on Decision and Control.

[22]  Ananthram Swami,et al.  Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework , 2007, IEEE Journal on Selected Areas in Communications.

[23]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[24]  Cem U. Saraydar,et al.  Efficient power control via pricing in wireless data networks , 2002, IEEE Trans. Commun..

[25]  Wei Wang,et al.  List-coloring based channel allocation for open-spectrum wireless networks , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[26]  Ananthram Swami,et al.  Joint Design and Separation Principle for Opportunistic Spectrum Access in the Presence of Sensing Errors , 2007, IEEE Transactions on Information Theory.

[27]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[28]  P. Laguna,et al.  Signal Processing , 2002, Yearbook of Medical Informatics.

[29]  Panagiotis Papadimitratos,et al.  A bandwidth sharing approach to improve licensed spectrum utilization , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[30]  Kiran Challapali,et al.  Spectrum Agile Radio: Detecting Spectrum Opportunities , 2004 .

[31]  Gang George Yin,et al.  Decentralized Adaptive Filtering Algorithms for Sensor Activation in an Unattended Ground Sensor Network , 2008, IEEE Transactions on Signal Processing.