Elements of information theory
Elements of information theory
Analysis of iterative waterfilling algorithm for multiuser power control in digital subscriber lines
EURASIP Journal on Applied Signal Processing
Joint multiuser detection and optimal spectrum balancing for digital subscriber lines
EURASIP Journal on Applied Signal Processing
Spectrum management for interference-limited multiuser communication systems
IEEE Transactions on Information Theory
Dynamic spectrum management for next-generation DSL systems
IEEE Communications Magazine
Distributed multiuser power control for digital subscriber lines
IEEE Journal on Selected Areas in Communications
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Bandwidth and routing optimization in wireless cellular networks with relays
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Improved dual decomposition based optimization for DSL dynamic spectrum management
IEEE Transactions on Signal Processing
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Consider a communication system whereby multiple users share a common frequency band and must choose their transmit power spectra jointly in response to physical channel conditions including the effects of interference. The goal of the users is to maximize a system-wide utility function (e.g., weighted sum-rate of all users), subject to individual power constraints. A popular approach to solve the discretized version of this nonconvex problem is by Lagrangian dual relaxation. Unfortunately the discretized spectrum management problem is NP-hard and its Lagrangian dual is in general not equivalent to the primal formulation due to a positive duality gap. In this paper, we use a convexity result of Lyapunov to estimate the size of duality gap for the discretized spectrum management problem and show that the duality gap vanishes asymptotically at the rate O(1/√N), where N is the size of the uniform discretization of the shared spectrum. If the channels are frequency flat, the duality gap estimate improves to O(1/N). Moreover, when restricted to the FDMA spectrum sharing strategies, we show that the Lagrangian dual relaxation, combined with a linear programming scheme, can generate an ε-optimal solution for the continuous formulation of the spectrum management problem in polynomial time for any ε O.