Active Projects

Ultra-Connectivity for 6G Wireless Communications: UAV and Intelligent Reflective Surface Enabled Heterogeneous Network Design; funded by TÜBİTAK, (2020-2023)

In this project, we propose a reliable, energy-efficient, and effective vertical heterogeneous network scheme (VHetNet) satisfying 6G wireless network requirements. We aim to reveal a high-performance VHetNet with unmanned aerial vehicles (UAVs) and intelligent reflecting surfaces (IRS) considering physical layer security. The project will be carrying out under the supervision of Prof. Lütfiye Durak Ata as a Principal Researcher (ITU), and the researchers from different universities and the industrial partner as Assoc. Prof. Sultan Aldırmaz Çolak (Kocaeli Univ.), Assist. Prof. Mustafa Namdar (Kütahya Dumlupınar Univ.), Assist. Prof. Arif Başgümüş (Kütahya Dumlupınar Univ.), Assist. Prof. Mehmet Akif Yazıcı (ITU), and Dr. Mehmet Başaran (Siemens Turkey), respectively.

Accepted Papers:

RF Energy Harvesting in Next Generation Wireless Communications Systems; funded by İTÜ-AYP, (2018-2021)

Wireless energy harvesting has been regarded as a promising approach to extend the life-time of a wireless communication systems. In energy harvesting (EH), energy is obtained by wind, solar, vibration and etc. Thus, the harvesting energy transformed to electricity and can be used by the nodes. However, the aforementioned traditional EH methods are not always available. RF EH has been emerged as a key promising technique which enables the wireless systems to harvests energy from the incoming signals in the environment. This energy is available as a dedicated or ambient and can be used in through the whole day.

Efficient IoT System Design Through Energy Harvesting; funded by İTÜ Vodafone Future Lab, (2018-2021)

Powering the IoT devices is an important issue in the 5G and beyond. Conventional batteries won’t work in the IoT applicaitons because of their various shapes and sizes and low power requirements. Therefore, power sources for IoT devices will need several key features of their own like: small/thin size and flexible shape and wireless connectivity which ables them to charge a device on the go, easy to use anywhere. A promising approach of power source alternatives for the IoT is harvesting energy from radio frequencies.

Optimization of a mobile network based on most used sites / routes; funded by İTÜ Vodafone Future Lab, (2018-2021)

Using the signaling information which contains the handover attempts and successes between the spurge and destination cells, it is possible to form a pattern of sites and cells in a matrix, that indicate the typical route that mobility, service and capacity needs to be sured for the smooth operation of the mobile network. This is valid for all the technologies and also for voice and data, even though voice will benefit the most from this type of optimization. Using machine learning and forecasting, it is possible to predict the traffic that can be carried by new sites that can be introduced in the network as well as the amount of traffic lost due to the loss of a site/ radio/ cell.

Completed Projects

Algorithm Development Project for Image Processing Supported Landing System

The algorithm has been developed and performance analyzes have been performed for the unmanned aerial vehicles (UAV) to perform image processing assisted landing.

[Research Project , funded by TUSAŞ/TAI]

Visual Notification of Indoor Sounds to the Users via TV

The goal of the project is to design a new generation TV unit with the partnership of Arçelik AŞ, which senses home-environment sounds and notifies the user visually especially for hearing-impaired persons.

[ SAN-TEZ Project, Funded by the Ministry of Science, Industry and Technology-(2014 – 2015)]

LTE eNodeB Performance Measurement, Software Development of Self-Configurable Networks

LTE eNodeB Performance Measurement, Software Development of Self-Configurable Networks: The role of handover parameters in improving the energy efficiency of cellular networks is analyzed, and the negative effects of handover failure (HOF) and ping-pong (PP) rate are investigated. The network performance of the new algorithm is explored in terms of real vehicular traffic data and state-of-the-art specifications of eNodeBs.
[Funded by Scientific and Technological Research Council of Turkey, TUBITAK under Grant TEYDEB Project No.3160085-(2017 – 2018)]

5G+: Communication Networks for 5G and beyond

[Umbrella Project, funded by Istanbul Technical University-(2015 – 2016)]

Detection of anti-personnel and anti-tank landmines

We have participated in the development and implementation of a multi-sensor landmine detection system. We have worked on feature extraction techniques and fuzzy decision problem based on the Neyman-Pearson criterion. We have assumed responsibilities on the sensor fusion processor.

[ Funded by Ministry of Defense]

Detection and Parameter Extraction of Low Probability of Intercept Radar Waveforms by Time-Frequency Signal Processing

Conventional pulsed radar systems are easily detected by advanced electronic support systems and radar warning receivers due to their high-powered transmissions. As the use of low probability of intercept (LPI) radar waveforms provides significant advantages in radar systems, we investigate LPI radar waveform detection and parameter extraction in this project. The proposed novel analysis techniques are implemented on the FPGA.

[Research Project of no. 113E117, funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK)-(2013 – 2015)]

High-resolution time-frequency distributions on the application of spread-spectrum communications and dissimilarity measures and retrieval on time-frequency distributions

High-resolution time-frequency representations are developed and applied to various communication applications. Moreover, fractional Fourier domain adaptive filter has been designed and original results in the discrete form of the transform are obtained. Signal retrieval and classification problem is also investigated by time-frequency signal processing.

[ Research Project of no. 105E078, Funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK)-(2006 – 2013)]

Mobile Edge Computing With Computation Offloading And Transmission Scheduling For Delay Sensitive Applications; funded by İTÜ BAP, (2020-2021)

In this project, our objective will be an intensive study and modeling of the next generation communication of MEC systems. We plan to design a framework for determining energy optimal computation offloading configuration considering the application and system-specific parameters. We will focus on algorithms and methods that used for making the offloading decision and try to enhance their performance by novel approaches for making an optimal offloading decision. We will concentrate on the amount of energy overheads(for data transmission or local computation) and energy saving (for computing the task in the edge server)and try to use a suitable optimization algorithm for minimizing the energy consumption with respect to the time, price,and security.We will generate computation tasks randomly at mobile users along the time. For each task, the mobile user can choose to either process it locally or offload it via uplink transmission to the edge for cloud computing (all the task or part of that). By considering tradeoffs between local and edge computing, wireless characteristics and noncooperative game interactions between mobile users, we will formulate a mechanism design problem to jointly determine a computation offloading scheme, a transmission scheduling discipline, and a pricing rule.

Noise Radar Waveform Design; funded by ARMERKOM, (2019-2020)

Noise radars are innovative radar structure predicted to be used in next generation radar technologies, with low probability of being detected on which various research and concept proof studies have been carried out. Within the scope of this project, it is aimed to develop and analyze algorithms that produce digital waveforms that can be utilized in software-defined radars. Synthesis of these waveforms will be verified by  various optimization algorithms. As a result, the performance of the waveforms will be analyzed and compared according to the metrics to be determined.

Network Optimization Based on Intensive Cellular Transitions in Mobile Communication Networks; funded by İTÜ BAP, (2019-2020)

Further information is needed to enable a fully autonomous and flexible network to enable future next-generation networks to overcome existing limitations and address the problems of existing cellular systems. This project focuses on the learning behavior of solutions of self-healing networks (SHN). The main issue addressed in this project is to dynamically adjust network parameters for detecting heavily used transitions in a cellular network in order to prevent interruption of service and uninterrupted communication. For the purpose of SHN, a review of common machine learning techniques encountered in cellular networks will be presented, as well as machine learning solutions. Within the scope of this project, it is planned to receive data from a telecommunication operator and if this is not possible, it is aimed to continue the new researches in the field of self-optimizing networks that can be implemented in the near future by using algorithms developed on synthetic data. 

Cooperative Vehicular Communications and Physical Layer Security Analysis in Cognitive Radio Networks; funded by İTÜ BAP, (2019-2020)

In this project, cooperative communication systems, which are not included in the literature under the assumption of cascade fading channel, will be examined, the maximum ratio combining (MRC), equal gain combining, EGC and / or selection combining , SC) will be used. In addition to the cooperative communication systems, cognitive radio networks (CRN) will be used to ensure the effective use of the existing spectrum due to the lack of frequency band in the communication systems also, physical layer security techniques will be used in order to ensure safe transmission and prevent any illegal user from accessing the data. The outage probability, secrecy outage probability calculations will be obtained in closed form.

Interference Management in Cognitive Radio Networks; funded by Presidency of Defense Industries, Turkey-(2017-2019)

This project includes reducing interference in military communications utilizing efficient spectrum allocation for all terminals. In addition, the projects aim to support different location and network topologies without spectrum planning in military communications. Flexibility to use in countries’ borders or conflict zones is aimed at designing next-generation communication systems that can be configured dynamically.