Distributed uplink power control for optimal sir assignment in cellular data networks

Authors:
Prashanth Hande;Sundeep Rangan;Mung Chiang;Xinzhou Wu
Affiliations:
Department of Electrical Engineering, Princeton University, Princeton, NJ and Qualcomm Flarion Technologies, Bedminster, NJ;Qualcomm Flarion Technologies, Bridgewater, NJ;Department of Electrical Engineering, Princeton University, Princeton, NJ;Qualcomm Flarion Technologies, Bridgewater, NJ
Venue:
IEEE/ACM Transactions on Networking (TON)
Year:
2008

Citing 8
Cited 8

Topics in matrix analysis

Topics in matrix analysis
Fair end-to-end window-based congestion control

IEEE/ACM Transactions on Networking (TON)
A utility-based power-control scheme in wireless cellular systems

IEEE/ACM Transactions on Networking (TON)
Radio link admission algorithms for wireless networks with power control and active link quality protection

INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 1)-Volume - Volume 1
Convex Optimization

Convex Optimization
Fundamentals of wireless communication

Fundamentals of wireless communication
Pricing and power control in a multicell wireless data network

IEEE Journal on Selected Areas in Communications
A framework for uplink power control in cellular radio systems

IEEE Journal on Selected Areas in Communications

Joint power control, beamforming and BS assignment for optimal SIR assignment

Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Utility-based power control with QoS support

Wireless Networks
A characterization of max---min SIR-balanced power allocation with applications

Wireless Networks
Joint utility-based power control and receive beamforming in decentralized wireless networks

EURASIP Journal on Wireless Communications and Networking - Special issue on interference management in wireless communication systems: theory and applications
Distributed delay-power control algorithms for bandwidth sharing in wireless networks

IEEE/ACM Transactions on Networking (TON)
On distributed power control and transceiver optimization in wireless networks

Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
On Opportunistic Power Control for Alamouti and SM MIMO Systems

Wireless Personal Communications: An International Journal
A utility maximization framework for fair and efficient multicasting in multicarrier wireless cellular networks

IEEE/ACM Transactions on Networking (TON)

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper solves the joint power control and SIR assignment problem through distributed algorithms in the uplink of multi-cellular wireless networks. The 1993 Foschini-Miljanic distributed power control can attain a given fixed and feasible SIR target. In data networks, however, SIR needs to be jointly optimized with transmit powers in wireless data networks. In the vast research literature since the mid-1990s, solutions to this joint optimization problem are either distributed but suboptimal, or optimal but centralized. For convex formulations of this problem, we report a distributed and optimal algorithm. The main issue that has been the research bottleneck is the complicated, coupled constraint set, and we resolve it through a re-parametrization via the left Perron Frobenius eigenvectors, followed by development of a locally computable ascent direction. A key step is a new characterization of the feasible SIR region in terms of the loads on the base stations, and an indication of the potential interference from mobile stations, which we term spillage. Based on this load-spillage characterization, we first develop a distributed algorithm that can achieve any Pareto-optimal SIR assignment, then a distributed algorithm that picks out a particular Pareto-optimal SIR assignment and the associated powers through utility maximization. Extensions to power-constrained and interference-constrained cases are carried out. The algorithms are theoretically sound and practically implementable: we present convergence and optimality proofs as well as simulations using 3GPP network and path loss models.