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We aim at maximizing the sum rate of secondary users (SUs) in OFDM-basedHeterogeneous Cognitive Radio (CR) Networks using RF energy harvesting.Assuming SUs operate in a time switching fashion, each time slot is partitionedinto three non-overlapping parts devoted for energy harvesting, spectrumsensing and data transmission. The general problem of joint resource allocationand structure optimization is formulated as a Mixed Integer NonlinearProgramming task which is NP-hard and intractable. Thus, we propose to tackleit by decomposing it into two subproblems. We first propose a sub-channelallocation scheme to approximately satisfy SUs' rate requirements and removethe integer constraints. For the second step, we prove that the generaloptimization problem is reduced to a convex optimization task. Considering thetrade-off among fractions of each time slot, we focus on optimizing the timeslot structures of SUs that maximize the total throughput while guaranteeingthe rate requirements of both real-time and non-real-time SUs. Since thereduced optimization problem does not have a simple closed-form solution, wethus propose a near optimal closed-form solution by utilizing Lambert-Wfunction. We also exploit iterative gradient method based on Lagrangian dualdecomposition to achieve near optimal solutions. Simulation results arepresented to validate the optimality of the proposed schemes.

Joint Spectrum Allocation and Structure Optimization in Green Powered Heterogeneous Cognitive Radio Networks