Researcher:
Önalan, Aysun Gurur

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Aysun Gurur

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Önalan

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Önalan, Aysun Gurur

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2019 - 201922020 - 20224

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    Minimum length scheduling for multi-cell wireless powered communication networks
    (IEEE, 2020) N/A; N/A; Department of Electrical and Electronics Engineering; Salık, Elif Dilek; Önalan, Aysun Gurur; Ergen, Sinem Çöleri; PhD Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 7211
    Wireless powered communication networks (WPCNs) will be a major enabler of massive machine type communications (MTCs), which is a major service domain for 5G and beyond systems. These MTC networks will be deployed by using low-power transceivers and a very limited set of transmission configurations. We investigate a novel minimum length scheduling problem for multi-cell full-duplex wireless powered communication networks to determine the optimal power control and scheduling for constant rate transmission model. The formulated optimization problem is combinatorial in nature and, thus, difficult to solve for the global optimum. As a solution strategy, first, we decompose the problem into the power control problem (PCP) and scheduling problem. For the PCP, we propose the optimal polynomial time algorithm based on the evaluation of Perron–Frobenius conditions. For the scheduling problem, we propose a heuristic algorithm that aims to maximize the number of concurrently transmitting users by maximizing the allowable interference on each user without violating the signal-to-noise-ratio (SNR) requirements. Through extensive simulations, we demonstrate a 50% reduction in the schedule length by using the proposed algorithm in comparison to unscheduled concurrent transmissions.
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    Minimum length scheduling for power constrained harvest-then-transmit communication networks
    (IEEE, 2019) N/A; N/A; Department of Electrical and Electronics Engineering; Salık, Elif Dilek; Önalan, Aysun Gurur; Ergen, Sinem Çöleri; PhD Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 7211
    We consider a wireless powered, harvest-then-transmit communication network, which consists of a single antenna, energy and information access point (aP) and multiple, single antenna, batteryless users with energy harvesting capabilities. at the beginning of a time frame, the aP broadcasts energy in the downlink to the users. then, users transmit their data to the aP in the uplink, using their harvested energy. We formulate the optimization problem with the objective of minimizing the total schedule length, subject to the constraints on the minimum amount of data to be sent to the aP, and unlike previous studies, the maximum transmit power for the information transmission. This problem is nonlinear and non-convex. the solution is based on bi-level optimization, consisting of optimizing the transmit power allocation of the nodes for a given energy harvesting time and searching over harvesting time allocation. We also propose a heuristic algorithm in which we incorporate the optimal solution of a single user network. Simulation results demonstrate that under appropriate network conditions, our proposed algorithms provide close-to-optimal results with a reasonable run time compared to a previously proposed time minimization algorithm that does not integrate the uplink power constraint.
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    Deep learning based minimum length scheduling for half duplex wireless powered communication networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Önalan, Aysun Gurur; Köprü, Berkay; Ergen, Sinem Çöleri; PhD Student; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 7211
    Minimum length scheduling is used to ensure the strict delay requirements of time-critical applications in wireless powered communications networks (WPCNs). The previous optimal and sub-optimal solutions of the problem suffer from the run-time complexity of the iterative algorithms, which makes real-time applications unpractical. This paper proposes a deep learning based framework for a low-complexity solution to the minimum length scheduling problem in half-duplex WPCNs. The objective of the problem is to minimize the duration of the schedule for energy harvesting (EH) and information transmission (IT), subject to the data demand, energy causality, and maximum transmit power constraints. Multi-input multi-output feed-forward deep neural network (DNN) architecture is considered, where the inputs are channel state information and two parameters derived from the optimality conditions of the problem; and outputs are the transmit powers, EH and IT lengths. To ensure the feasibility of the DNN outputs, we design a final layer which maps the estimated transmit powers to the feasible EH and IT lengths. The DNN is trained offline with both supervised and unsupervised techniques. Simulation results indicate that the proposed DNN-based approaches are up to 8.5 times faster than the benchmark iterative algorithms. These approaches also outperform benchmark sub-optimal algorithms in terms of accuracy with only 0.12% optimality gap and robustness against varying network conditions.
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    PublicationOpen Access
    Minimum length scheduling for power constrained harvest-then-transmit communication networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2019) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Salık, Elif Dilek; Önalan, Aysun Gurur; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A; N/A
    We consider a wireless powered, harvest-then-transmit communication network, which consists of a single antenna, energy and information access point (AP) and multiple, single antenna, batteryless users with energy harvesting capabilities. At the beginning of a time frame, the AP broadcasts energy in the downlink to the users. Then, users transmit their data to the AP in the uplink, using their harvested energy. We formulate the optimization problem with the objective of minimizing the total schedule length, subject to the constraints on the minimum amount of data to be sent to the AP, and unlike previous studies, the maximum transmit power for the information transmission. This problem is nonlinear and non-convex. The solution is based on bi-level optimization, consisting of optimizing the transmit power allocation of the nodes for a given energy harvesting time and searching over harvesting time allocation. We also propose a heuristic algorithm in which we incorporate the optimal solution of a single user network. Simulation results demonstrate that under appropriate network conditions, our proposed algorithms provide close-to-optimal results with a reasonable run time compared to a previously proposed time minimization algorithm that does not integrate the uplink power constraint.
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    PublicationOpen Access
    Relay selection, scheduling, and power control in wireless-powered cooperative communication networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2020) Department of Electrical and Electronics Engineering; Önalan, Aysun Gurur; Salık, Elif Dilek; Ergen, Sinem Çöleri; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 7211
    Relay nodes are used to improve the throughput, delay and reliability performance of energy harvesting networks by assisting both energy and information transfer between sources and access point. Previous studies on radio frequency energy harvesting networks are limited to single-source-single/multiple-relay networks. In this paper, a novel joint relay selection, scheduling and power control problem for multiple-source-multiple-relay network is formulated with the objective of minimizing the total duration of wireless power and information transfer. The formulated problem is non-convex mixed-integer non-linear programming problem, and proven to be NP-hard. We first formulate a sub-problem on scheduling and power control for a given relay selection. We propose an efficient optimal algorithm based on a bi-level optimization over power transfer time allocation. Then, for optimal relay selection, we present optimal exponential-time Branch-and-Bound (BB) based algorithm where the nodes are pruned with problem specific lower and upper bounds. We also provide two BB-based heuristic approaches limiting the number of branches generated from a BB-node, and a relay criterion based lower complexity heuristic algorithm. The proposed algorithms are demonstrated to outperform conventional harvest-then-cooperate approaches with up to 87% lower schedule length for various network settings with at least 7.88 times higher algorithm runtime.
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    PublicationOpen Access
    Minimum length scheduling for multi-cell wireless powered communication networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2020) Department of Electrical and Electronics Engineering; Salık, Elif Dilek; Önalan, Aysun Gurur; Ergen, Sinem Çöleri; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 7211
    We consider a wireless powered, harvest-then-transmit communication network, which consists of multiple, single antenna, energy and information access points (APs) and multiple, single antenna users with energy harvesting capabilities and rechargeable batteries, and allows simultaneous information transmission. We formulate the joint power control and scheduling problem with the objective of minimizing the total schedule length, subject to the constraints on the minimum amount of data to be sent by the users to the APs, and the maximum transmit power for the information transmission. This problem is a nonlinear and non-convex, mixed integer programming problem for which there is no known polynomial time algorithm. The proposed heuristic algorithm is based on, first, finding the solution for a fixed energy harvesting time and then searching for the optimal energy harvesting time that minimizes the total schedule length. For the former, a scheduling problem is formulated as an integer programming problem, which we solve with Branch and Price based methods upon solving the power control problem separately. Simulation results demonstrate that the proposed algorithm outperforms previously proposed time minimization algorithms that do not consider simultaneous transmission scenarios up to 3:5% for larger AP power, 25:4% for tighter maximum transmit power limit, and 6:5% for greater number of users per AP.