Robust Solutions to Least-Squares Problems with Uncertain Data
SIAM Journal on Matrix Analysis and Applications
Mathematics of Operations Research
Robust Solutions to Uncertain Semidefinite Programs
SIAM Journal on Optimization
Operations Research
Convex Optimization
Rate-maximizing power allocation in OFDM based on partial channel knowledge
IEEE Transactions on Wireless Communications
Comparisons and enhancement strategies for linearizing mixed 0-1 quadratic programs
Discrete Optimization
Robust solutions of uncertain linear programs
Operations Research Letters
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This paper proposes two robust binary quadratically constrained quadratic programs (BQCQP) for wireless Orthogonal Frequency Division Multiple Access (OFDMA) networks. The first one is based on a scenario uncertainty approach from Kouvelis and Yu [1] and the second is based on an interval uncertainty approach from Bertsimas and Sim [2]. Both robust models allow to decide what modulations and what sub-carriers are going to be used by a particular user in the system depending on its bit rate requirements. Thus, we derive two robust semidefinite relaxations to compute lower bounds. Our numerical results show, in average near optimal integrality gaps of 4.12% and 1.15% under the scenario and interval approach when compared to the optimal solution of the problem derived by linearizing the two quadratic models with Fortet linearization method. Some comparison between the two robust approaches is also provided.