IEEE/ACM Transactions on Networking (TON)
A Unified Monotonic Approach to Generalized Linear Fractional Programming
Journal of Global Optimization
Convex Optimization
Power Control in Wireless Cellular Networks
Foundations and Trends® in Networking
Power Control By Geometric Programming
IEEE Transactions on Wireless Communications
Distributed interference compensation for wireless networks
IEEE Journal on Selected Areas in Communications
A framework for uplink power control in cellular radio systems
IEEE Journal on Selected Areas in Communications
Achieving log-utility fairness in cdma systems via majorization theory
IEEE Communications Letters
Near optimum power control under fairness constraints in CoMP systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
S-MAPEL: monotonic optimization for non-convex joint power control and scheduling problems
IEEE Transactions on Wireless Communications
Monotonic optimization framework for the two-user MISO interference channel
IEEE Transactions on Communications
Weighted sum rate maximization on two user Gaussian interference channels with rate splitting
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Hybrid heuristic-waterfilling game theory approach in MC-CDMA resource allocation
Applied Soft Computing
Power allocation in the TV white space under constraint on secondary system self-interference
Journal of Electrical and Computer Engineering
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Achieving weighted throughput maximization (WTM) through power control has been a long standing open problem in interference-limited wireless networks. The complicated coupling between the mutual interferences of links gives rise to a non-convex optimization problem. Previous work has considered the WTM problem in the high signal to interference-and-noise ratio (SINR) regime, where the problem can be approximated and transformed into a convex optimization problem through proper change of variables. In the general SINR regime, however, the approximation and transformation approach does not work. This paper proposes an algorithm, MAPEL, which globally converges to a global optimal solution of the WTM problem in the general SINR regime. The MAPEL algorithm is designed based on three key observations of the WTM problem: (1) the objective function is monotonically increasing in SINR, (2) the objective function can be transformed into a product of exponentiated linear fraction functions, and (3) the feasible set of the equivalent transformed problem is always "normal", although not necessarily convex. The MAPEL algorithm finds the desired optimal power control solution by constructing a series of polyblocks that approximate the feasible SINR region in an increasing precision. Furthermore, by tuning the approximation factor in MAPEL, we could engineer a desirable tradeoff between optimality and convergence time. MAPEL provides an important benchmark for performance evaluation of other heuristic algorithms targeting the same problem. With the help of MAPEL, we evaluate the performance of several existing algorithms through extensive simulations.