Joint spectrum allocation and energy harvesting optimization in green powered heterogeneous cognitive radio networks
| Autor: | Nirwan Ansari, Ali Shahini |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Optimization problem Computer Networks and Communications Orthogonal frequency-division multiplexing Computer science 020206 networking & telecommunications 020302 automobile design & engineering 02 engineering and technology Frequency allocation symbols.namesake Cognitive radio 0203 mechanical engineering Convex optimization 0202 electrical engineering electronic engineering information engineering symbols Resource allocation Throughput (business) Gradient method Lagrangian |
| Zdroj: | Computer Communications. 127:36-49 |
| ISSN: | 0140-3664 |
| DOI: | 10.1016/j.comcom.2018.05.011 |
| Popis: | We aim at maximizing the sum rate of secondary users (SUs) in OFDM-based Heterogeneous Cognitive Radio (CR) Networks using RF energy harvesting. Assuming SUs operate in a time switching fashion, each time slot is partitioned into three non-overlapping parts devoted for energy harvesting, spectrum sensing and data transmission. The general problem of joint resource allocation and structure optimization is formulated as a Mixed Integer Nonlinear Programming task which is NP-hard and intractable. Thus, we propose to tackle it by decomposing it into two subproblems. We first propose a sub-channel allocation scheme to approximately satisfy SUs’ rate requirements and remove the integer constraints. For the second step, we prove that the general optimization problem is reduced to a convex optimization task. Considering the trade-off among fractions of each time slot, we focus on optimizing the time slot structures of SUs that maximize the total throughput while guaranteeing the rate requirements of both real-time and non-real-time SUs. Since the reduced optimization problem does not have a simple closed-form solution, we thus propose a near optimal closed-form solution by utilizing Lambert-W function. We also exploit iterative gradient method based on Lagrangian dual decomposition to achieve near optimal solutions. Simulation results are presented to validate the optimality of the proposed schemes. |
| Databáze: | OpenAIRE |
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