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Department: search.filters.department.Department of Electrical and Electronics EngineeringSubject: search.filters.subject.Energy harvesting

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    Communication by means of thermal noise: towards networks with extremely low power consumption
    (IEEE Inc., 2022) Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116
    In this paper, the paradigm of thermal noise communication (TherCom) is put forward for future wired/wireless networks with extremely low power consumption. Taking backscatter communication (BackCom) and reconfigurable intelligent surface (RIS)-based radio frequency chain-free transmitters one step further, a thermal noise-driven transmitter might enable zero-signal-power transmission by simply indexing resistors or other noise sources according to information bits. This preliminary paper aims to shed light on the theoretical foundations, transceiver designs, and error performance derivations as well as optimizations of two emerging TherCom solutions: Kirchhoff-law-Johnson-noise (KLJN) secure bit exchange and wireless thermal noise modulation (TherMod) schemes. Our theoretical and computer simulation findings reveal that noise variance detection, supported by sample variance estimation with carefully optimized decision thresholds, is a reliable way of extracting the embedded information from noise modulated signals, even with limited number of noise samples. IEEE
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    PublicationOpen Access
    Deep neural network based minimum length scheduling in wireless powered communication networks
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Khan, Nasir; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    Minimization of schedule length is key in ensuring the delay performance of wireless powered communication networks (WPCNs) demanding strict timing and reliability guarantees. Previous solution methodologies proposed for these wireless networks suffer from high run-time complexity, making it very difficult to solve the problem in real time. This paper considers a run-time efficient deep learning based approach for solving minimum length scheduling problem in a full-duplex WPCN. Leveraging upon the universal approximation capability of neural networks, a multi-output feed forward deep neural network based framework is proposed where inputs are the channel coefficients and outputs are the optimal power, transmission length and schedule of users. Simulation results indicate that the proposed deep learning based approach can very well approximate the true outputs with a percentage error below 1% for different network configurations while maintaining a very low run-time complexity.
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    PublicationOpen Access
    Effect of downlink energy transfer scheduling on SDMA and TDMA uplink transmission
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Pehlivan, İbrahim; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    The high cost and power consumption of digital beamforming, as a result of the high number of RF chains, has overshadowed its performance on multi-antenna wireless powered communication networks (WPCNs). This setback forced researchers to low-cost alternatives such as hybrid beamforming, which decreases the number of expensive RF chains by utilizing cheaper phase shifters. This cost-cutting, however, comes with reduced control over beamforming weights and compromise performance. To circumvent this deficiency, scheduling of energy harvesting (SEH), utilizing the degree of freedom in the time domain, has been proposed. In SEH, the downlink slot is subdivided into multiple variable-length subslots with different beamforming weights. In this paper, we examine the effect of SEH on the optimization of minimum length scheduling for space division multiple access (SDMA) uplink transmission compared to time division multiple access (TDMA) uplink transmission. Via simulations, we demonstrate that SDMA benefits more from the additional degree of freedom provided by the usage of SEH for any number of nodes. However, SDMA yields inferior delay performance compared to TDMA as the number of nodes increases, which restricts the application of SDMA with SEH, making it impractical.
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    PublicationOpen Access
    Optimal power control and scheduling for energy harvesting wireless networked control systems
    (Institute of Electrical and Electronics Engineers (IEEE), 2019) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Karadağ, Göksu; Faculty Member; Undergraduate Student; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    In this paper, we introduce RF energy harvesting paradigm into WNCS framework to study the optimal power control, energy harvesting and scheduling problem with the objective of providing maximum level of adaptivity under strict timing and reliability requirements employing the constant rate transmission model. We formulate the problem as a Mixed Integer Linear Programming Problem (MILP). We show the power allocation can be separated from the scheduling and harvesting at optimality. Then, we introduce a heuristic algorithm for the scheduling problem, periodic list scheduling (PLS), inspired from list scheduling of jobs with sequence dependent setup times on identical machines. We then demonstrate via extensive simulations the superiority of the proposed algorithm in terms of closeness to the optimal, adaptivity and runtime.
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    Total transmission time minimization through relay selection for full-duplex wireless powered cooperative communication networks
    (Springer Science and Business Media Deutschland GmbH, 2020) N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Kazmi, Syed Adil Abbas; Iqbal, Muhammad Shahid; 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 relay based full-duplex wireless powered cooperative communication network which consists of a hybrid access point (HAP), N users and K decode-and-forward relays with energy harvesting capability. We propose an optimization framework for relay selection with the objective of minimizing the total transmission time subject to energy causality and user traffic demand constraints. The formulated optimization problem is a mixed integer non-linear programming problem, which is difficult to solve for the global optimal solution in polynomial-time. As a solution strategy, we decompose the proposed optimization problem into two sub-problems: time allocation problem and relay selection problem. We derive the optimal solution of the time allocation problem by using convex optimization techniques. For the relay selection problem, based on the optimality analysis, we propose a polynomial-time heuristic algorithm, which minimizes the total transmission time by allocating the best relay to each user. Through simulations, we illustrate that the proposed algorithm outperforms the conventional predetermined relay allocation scheme and performs very close to the optimal solution for different network densities, HAP power values, and initial battery levels.