Joint spectrum allocation and energy harvesting optimization in green powered heterogeneous cognitive radio networks

Ali Shahini, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)36-49
Number of pages14
JournalComputer Communications
StatePublished - Sep 2018

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


  • Cooperative spectrum sensing
  • Energy harvesting
  • Heterogeneous cognitive radio network
  • Resource allocation
  • Time slot optimization


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