TY - GEN
T1 - Distributed joint power and admission control for ad-hoc and cognitive underlay networks
AU - Mitliagkas, I.
AU - Sidiropoulos, N. D.
AU - Swami, A.
PY - 2010
Y1 - 2010
N2 - Power control is important in interference-limited cellular, ad-hoc, and cognitive wireless networks, when the objective is to ensure a certain quality of service to each connection. Power control has been extensively studied in this context, including distributed algorithms that are particularly appealing in ad-hoc and cognitive settings. A long-standing issue is that the power control problem may be infeasible, thus requiring appropriate admission control. The power and admission control parts of the problem are tightly coupled, but the joint problem is NP-hard. In recent work, we developed a convex relaxation-based deflation approach to the joint problem, which was shown to outperform the prior art, and yield close to optimal solutions at moderate computational cost. In this paper, we derive a distributed version of our joint power and admission control algorithm. The algorithm alternates between distributed approximation and distributed deflation - reaching consensus on a user to drop, when needed. Both phases require only local communication and computation, yielding a relatively lightweight distributed algorithm which also attains close to optimal performance.
AB - Power control is important in interference-limited cellular, ad-hoc, and cognitive wireless networks, when the objective is to ensure a certain quality of service to each connection. Power control has been extensively studied in this context, including distributed algorithms that are particularly appealing in ad-hoc and cognitive settings. A long-standing issue is that the power control problem may be infeasible, thus requiring appropriate admission control. The power and admission control parts of the problem are tightly coupled, but the joint problem is NP-hard. In recent work, we developed a convex relaxation-based deflation approach to the joint problem, which was shown to outperform the prior art, and yield close to optimal solutions at moderate computational cost. In this paper, we derive a distributed version of our joint power and admission control algorithm. The algorithm alternates between distributed approximation and distributed deflation - reaching consensus on a user to drop, when needed. Both phases require only local communication and computation, yielding a relatively lightweight distributed algorithm which also attains close to optimal performance.
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U2 - 10.1109/ICASSP.2010.5496132
DO - 10.1109/ICASSP.2010.5496132
M3 - Conference contribution
AN - SCOPUS:78049370767
SN - 9781424442966
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 3014
EP - 3017
BT - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Y2 - 14 March 2010 through 19 March 2010
ER -