Beamforming duality and algorithms for weighted sum rate maximization in cognitive radio networks

I. Wei Lai, Liang Zheng, Chia Han Lee, Chee Wei Tan

研究成果: 書貢獻/報告類型篇章


In this chapter, we investigate the joint design of transmit beamforming and power control to maximize the weighted sum rate in the multiple-input single-output (MISO) cognitive radio network constrained by arbitrary power budgets and interference temperatures. The nonnegativity of the physical quantities, e.g., channel parameters, powers, and rates, is exploited to enable key tools in nonnegative matrix theory, such as the (linear and nonlinear) Perron-Frobenius theory, quasi-invertibility, and Friedland-Karlin inequalities, to tackle this nonconvex problem. Under certain (quasi-invertibility) sufficient condition, a tight convex relaxation technique can relax multiple constraints to bound the global optimal value in a systematic way. Then, a single-input multiple-output (SIMO)-MISO duality is established through a virtual dual SIMO network and Lagrange duality. This SIMO-MISO duality proved to have the zero duality gap that connects the optimality conditions of the primal MISO network and the virtual dual SIMO network. By exploiting the SIMO-MISO duality, we present an algorithm to optimally solve the sum rate maximization problem.

主出版物標題Cognitive Radio Networks
主出版物子標題Performance, Applications and Technology
發行者Nova Science Publisher Inc.
出版狀態已發佈 - 2018 1月 1

ASJC Scopus subject areas

  • 一般工程


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