Browsing by Author "Kahraman, Ibrahim"

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    Interference Mitigation in Joint Communication and Sensing: A Precoding-Based Framework With SSK Modulation
    (IEEE, 2025) Hassan, Sumeyra; Kazemipourleilabadi, Negin; Kahraman, Ibrahim; Sadi, Yalcin; Koca, Mutlu; Panayirci, Erdal; Poor, H. Vincent
    This paper proposes a joint communication and sensing (JCS) system that integrates multiple-input multipleoutput (MIMO) communication and radar functionalities within a shared spectrum. A novel precoder design incorporating Maximal Ratio Combining (MRC) is proposed to eliminate radar-induced and multi-user interference (MUI), ensuring robust communication while maintaining radar sensing accuracy. The communication subsystem leverages spatial shift keying (SSK) to enhance spectral efficiency, while the radar employs a co-located MIMO configuration for precise target detection. Simulation results show that the proposed system achieves a bit error rate (BER) below 10(-2) at 20 dB signal-to-noise ratio (SNR) and a radar detection probability exceeding 90% at 5 dB SNR, validating its effectiveness in interference management. This approach enables seamless integration of communication and sensing, making it a promising solution for autonomous driving, smart cities, and next-generation wireless networks.
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    Citation - WoS: 13
    Citation - Scopus: 14
    Measurement-Based Large Scale Statistical Modeling of Air-To Wireless Uav Channels Via Novel Time-Frequency Analysis
    (IEEE-Inst Electrical Electronics Engineers Inc, 2022) Ede, Burak; Kaplan, Batuhan; Kahraman, Ibrahim; Kesir, Samed; Yarkan, Serhan; Ekti, Ali Riza; Baykas, Tuncer
    Any operation scenario for unmanned aerial vehicles also known as drones in real world requires resilient wireless link to guarantee capacity and performance for users, which can only be achieved by obtaining detailed knowledge about the propagation channel. Thus, this study investigates the large-scale channel propagation statistics for the line of sight air-to-air (A2A) drone communications to estimate the path loss exponent (PLE). We conducted a measurement campaign at 5.8 GHz, using low cost and light weight software defined radio based channel sounder which is developed in this study and then further integrated on commercially available drones. To determine the PLE, frequency-based, time-based and time-frequency based methods are utilized. Accuracy of the proposed method is verified under ideal conditions in a well-isolated anechoic chamber before the actual measurement campaign to verify the performance in a free space path loss environment. The path loss exponent for A2A wireless drone channel is estimated with these verified methods.