A utility-based joint power and rate adaptive algorithm in wireless ad hoc networks

In this paper, a utility-based joint power and rate adaptive algorithm (UPRA) is proposed to alleviate the influence of channel variation by using softened signal-to-interference-and-noise ratio (SINR) requirements. The transmission power and rate of each user will be adjusted to maximize its own net-utility according to the states of channel, which results in a balance between the effective transmission rate and power consumption. Although the UPRA works based on a non-cooperative game, cooperation among users can be achieved so that the throughput of the whole network will be improved. The convergence of the algorithm has also been studied in both feasible and infeasible cases.

[1]  Zoran Gajic,et al.  A nash game algorithm for SIR-based power control in 3G wireless CDMA networks , 2005, IEEE/ACM Transactions on Networking.

[2]  Roy D. Yates,et al.  Stochastic power control for cellular radio systems , 1998, IEEE Trans. Commun..

[3]  A. J. Jones.  Game theory; mathematical models of conflict. , 1980 .

[4]  Gerard J. Foschini,et al.  A simple distributed autonomous power control algorithm and its convergence , 1993 .

[5]  Gregory J. Pottie,et al.  A distributed scheme for integrated predictive dynamic channel and power allocation in cellular radio networks , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[6]  A. Subramanian,et al.  Joint rate and power control algorithms for wireless networks , 2005, IEEE Transactions on Signal Processing.

[7]  Kin K. Leung.  Power control by interference prediction for broadband wireless packet networks , 2002, IEEE Trans. Wirel. Commun..

[8]  Sukumar Nandi,et al.  Full auto rate MAC protocol for wireless ad hoc networks , 2005 .

[9]  Ness B. Shroff,et al.  A utility-based power-control scheme in wireless cellular systems , 2003, TNET.

[10]  S. Sorooshyari,et al.  Optimal SIR and interference-based distributed power control for wireless networks , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[11]  Fernando Paganini,et al.  Game theoretic approach to power control in cellular CDMA , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[12]  Zhisheng Niu,et al.  Joint power and rate control for wireless ad hoc networks: a game-theoretical approach with step-up pricing , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

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

[14]  Subhrakanti Dey,et al.  Optimal power control in wireless data networks with outage-based utility guarantees , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[15]  Roy D. Yates,et al.  A Framework for Uplink Power Control in Cellular Radio Systems , 1995, IEEE J. Sel. Areas Commun..

[16]  Kin K. Leung.  A Kalman-filter method for power control in broadband wireless networks , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).