arXiv subjects

Caglar Tunc

Publications and source records attributed to Caglar Tunc.

4 recordsLinked to original sources

arXiv2026

A Three-Dimensional Path Loss Model for THz Band Aerial Communications

Accurate characterization of Terahertz (THz) band path loss is critical for reliable high-frequency communication, especially in aerial networks where transceivers may operate at different altitudes. Existing THz-band path loss models for aerial networks focus on horizontal or vertical transceiver deployments, and fall short at modeling the random 3D geometry of transceiver locations. To address this limitation, we propose a new analytical THz path loss model that incorporates arbitrary 3D geometry of transceiver locations and frequency-selective absorption, obtained through a two-dimensional regression. We validate our proposed model with the propagation data collected via the Atmospheric Model (am) tool for multiple aerial link types, including drone-to-drone (Dr2Dr), medium-altitude aerial communication (MAAC), high-altitude unmanned aerial vehicles~(UAV)-to-UAV (U2U) links over varying transceiver separation and sub-THz to low-THz spectrum, i.e., 0.1--1~THz. The proposed framework provides a unified and accurate model for analyzing and designing future high-frequency aerial communication systems.

eess.SP↗

arXiv2024

Optimal Digital Twinning of Random Systems with Twinning Rate Constraints

With the massive advancements in processing power, Digital Twins (DTs) have become powerful tools to monitor and analyze physical entities. However, due to the potentially very high number of Physical Systems (PSs) to be tracked and emulated, for instance, in a factory environment or an Internet of Things (IoT) network, continuous twinning might become infeasible. In this paper, a DT system is investigated with a set of random PSs, where the twinning rate is limited due to resource constraints. Three cost functions are considered to quantify and penalize the twinning delay. For these cost functions, the optimal twinning problem under twinning rate constraints is formulated. In a numerical example, the proposed cost functions are evaluated for two, one push-based and one pull-based, benchmark twinning policies. The proposed methodology is the first to investigate the optimal twinning problem with random PSs and twinning rate constraints, and serves as a guideline for real-world implementations on how frequently PSs should be twinned.

cs.NI↗

arXiv2024

DTRAN: A Special Use Case of RAN Optimization using Digital Twin

The emergence of beyond 5G (B5G) and 6G networks underscores the critical role of advanced computer-aided tools, such as network digital twins (DTs), in fostering autonomous networks and ubiquitous intelligence. Existing solutions in the DT domain primarily aim to model and automate specific tasks within the network lifecycle, which lack flexibility and adaptability for fully autonomous design and management. Unlike the existing DT approaches, we propose RAN optimization using the Digital Twin (DTRAN) framework that follows a holistic approach from core to edge networks. The proposed DTRAN framework enables real-time data management and communication with the physical network, which provides a more accurate and detailed digital replica than the existing approaches. We outline the main building blocks of the DTRAN and describe the details of our specific use case, which is RAN configuration optimization, to demonstrate the applicability of the proposed framework for a real-world scenario.

cs.NI↗

arXiv2019

Optimal Transmission Policies for Energy Harvesting Age of Information Systems with Battery Recovery

We consider an energy harvesting information update system where a sensor is allowed to choose a transmission mode for each transmission, where each mode consists of a transmission power-error pair. We also incorporate the battery phenomenon called battery recovery effect where a battery replenishes the deliverable energy if kept idle after discharge. For an energy-limited age of information (AoI) system, this phenomenon gives rise to the interesting trade-off of recovering energy after transmissions, at the cost of increased AoI. Considering two metrics, namely peak-age hitting probability and average age as the worst-case and average performance indicators, respectively, we propose a framework that formulates the optimal transmission scheme selection problem as a Markov Decision Process (MDP). We show that the gains obtained by considering both battery dynamics and adjustable transmission power together are much higher than the sum gain achieved if they are considered separately. We also propose a simple methodology to optimize the system performance taking into account worst-case and average performances jointly.

cs.IT↗