Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective

This article provides an overview of the state-of-art results on communication resource allocation over space, time, and frequency for emerging cognitive radio (CR) wireless networks. Focusing on the interference-power/interference-temperature (IT) constraint approach for CRs to protect primary radio transmissions, many new and challenging problems regarding the design of CR systems are formulated, and some of the corresponding solutions are shown to be obtainable by restructuring some classic results known for traditional (non-CR) wireless networks. It is demonstrated that convex optimization plays an essential role in solving these problems, in a both rigorous and efficient way. Promising research directions on interference management for CR and other related multiuser communication systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex optimization for signal processin

"Core-Selecting Auctions: An Experimental Study"

Many business and policy problems, such as allocation of spectrum rights and financial assets, involve allocation of heterogeneous objects among players with superadditive values. This paper uses laboratory experiments to study core-selecting auctions (clock-proxy auctions of Ausubel, Cramton, and Milgrom (2004)) recently proposed as a solution to this problem. Our experimental design involves three factors. The first factor is the auction design and we consider generalized Vickrey auctions, simultaneous ascending auctions, and clock-proxy auctions. The second factor is the value structure of agents. In addition to a benchmark case of additive values, we considered superadditive value structures which feature the exposure problem and the coordination problem. The third factor is subject characteristics. We ran experiments with professional traders and university students. We found that clock-proxy auctions outperformed generalized Vickrey auctions. Clock-proxy auctions outperformed simultaneous ascending auctions with the exposure problem value structure, and did statistically equally well with the additive and the coordination problem value structure. The result suggests a trade-off between efficiency improvements and complexity in package bidding. An ANOVA of outcomes demonstrated that auction designs were significant, and the interaction terms were often significant. We estimated the effect of auction design on efficiency and revenue and found that its magnitude depended on the valuation structure and subject characteristics. The result suggests that market design is not one-size-fits-all and a successful design builds on an understanding of fine details of the problem environments.

Robustness maximization of parallel multichannel systems

Bit error rate (BER) minimization and SNR-gap maximization, two robustness optimization problems, are solved, under average power and bit-rate constraints, according to the waterfilling policy. Under peak-power constraint the solutions differ and this paper gives bit-loading solutions of both robustness optimization problems over independent parallel channels. The study is based on analytical approach with generalized Lagrangian relaxation tool and on greedy-type algorithm approach. Tight BER expressions are used for square and rectangular quadrature amplitude modulations. Integer bit solution of analytical continuous bit-rates is performed with a new generalized secant method. The asymptotic convergence of both robustness optimizations is proved for both analytical and algorithmic approaches. We also prove that, in conventional margin maximization problem, the equivalence between SNR-gap maximization and power minimization does not hold with peak-power limitation. Based on a defined dissimilarity measure, bit-loading solutions are compared over power line communication channel for multicarrier systems. Simulation results confirm the asymptotic convergence of both allocation policies. In non asymptotic regime the allocation policies can be interchanged depending on the robustness measure and the operating point of the communication system. The low computational effort of the suboptimal solution based on analytical approach leads to a good trade-off between performance and complexity.Comment: 27 pages, 8 figures, submitted to IEEE Trans. Inform. Theor

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Potential games form a class of non-cooperative games where unilateral improvement dynamics are guaranteed to converge in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on Communications, vol. E98-B, no. 9, Sept. 201