TY - GEN
T1 - Utility-based power control for peer-to-peer cognitive radio networks with heterogeneous QoS constraints
AU - Gatsis, Nikolaos
AU - Marques, Antonio G.
AU - Giannakis, Georgios B
PY - 2008
Y1 - 2008
N2 - Transmit-power control is a critical task in cognitive radio (CR) networks. In the present contribution, adherence to hierarchies between primary and secondary users in a peer-to-peer CR network is enabled through distributed power control. Hierarchies are effected by imposing minimum and maximum bounds on a quality-of-service (QoS) metric, such as communication rate. These bounds translate to signal-to-interference-plus-noise ratio (SINR) constraints. Furthermore, a utility function captures each user's satisfaction with the received SINR. The novel power control strategy maximizes the total utility while respecting individual SINR constraints - a task recast as a convex optimization problem under a suitable relaxation. Sufficient conditions, realistic for practical CR networks, are provided to obtain the optimal power allocation from the solution of the relaxed problem. Finally, a low-overhead distributed algorithm for optimal power control is developed, and tested against competing alternatives via simulations.
AB - Transmit-power control is a critical task in cognitive radio (CR) networks. In the present contribution, adherence to hierarchies between primary and secondary users in a peer-to-peer CR network is enabled through distributed power control. Hierarchies are effected by imposing minimum and maximum bounds on a quality-of-service (QoS) metric, such as communication rate. These bounds translate to signal-to-interference-plus-noise ratio (SINR) constraints. Furthermore, a utility function captures each user's satisfaction with the received SINR. The novel power control strategy maximizes the total utility while respecting individual SINR constraints - a task recast as a convex optimization problem under a suitable relaxation. Sufficient conditions, realistic for practical CR networks, are provided to obtain the optimal power allocation from the solution of the relaxed problem. Finally, a low-overhead distributed algorithm for optimal power control is developed, and tested against competing alternatives via simulations.
KW - Cognitive radios
KW - Distributed algorithms
KW - Optimization methods
KW - Power control
KW - QoS constraints
UR - http://www.scopus.com/inward/record.url?scp=51449120011&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51449120011&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2008.4518232
DO - 10.1109/ICASSP.2008.4518232
M3 - Conference contribution
AN - SCOPUS:51449120011
SN - 1424414849
SN - 9781424414840
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2805
EP - 2808
BT - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
T2 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Y2 - 31 March 2008 through 4 April 2008
ER -