Abstract
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 > 0.
Original language | English (US) |
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Pages (from-to) | 2675-2689 |
Number of pages | 15 |
Journal | IEEE Transactions on Signal Processing |
Volume | 57 |
Issue number | 7 |
DOIs | |
State | Published - Jul 15 2009 |
Keywords
- Cognitive radio
- Complexity
- Duality
- Spectrum management
- Sum-rate maximization
- ε-approximation