TY - JOUR
T1 - Joint spectrum allocation and energy harvesting optimization in green powered heterogeneous cognitive radio networks
AU - Shahini, Ali
AU - Ansari, Nirwan
N1 - Funding Information:
This work was supported in part by NSF under grant no. CNS-1320468. Preliminaries of this work was presented at the Sarnoff Symposium, Newark, NJ, September 2016 [1].
Funding Information:
This work was supported in part by NSF under grant no. CNS-1320468 . Preliminaries of this work was presented at the Sarnoff Symposium, Newark, NJ, September 2016 [1] .
Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/9
Y1 - 2018/9
N2 - 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.
AB - 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.
KW - Cooperative spectrum sensing
KW - Energy harvesting
KW - Heterogeneous cognitive radio network
KW - Resource allocation
KW - Time slot optimization
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U2 - 10.1016/j.comcom.2018.05.011
DO - 10.1016/j.comcom.2018.05.011
M3 - Article
AN - SCOPUS:85048458070
SN - 0140-3664
VL - 127
SP - 36
EP - 49
JO - Computer Communications
JF - Computer Communications
ER -