3 papers
cs.NI2026
SAIL: Unsupervised Spatial-Angular Interpretable Feature Learning for RF Map Synthesis
Sopan Sarkar, Marwan Krunz
In wireless networks, radio-frequency (RF) maps are critical for tasks such as capacity planning, coverage estimation, and localization. Traditional approaches for obtaining RF map…
cs.LG2023
RADIANCE: Radio-Frequency Adversarial Deep-learning Inference for Automated Network Coverage Estimation
Sopan Sarkar, Mohammad Hossein Manshaei, Marwan Krunz
Radio-frequency coverage maps (RF maps) are extensively utilized in wireless networks for capacity planning, placement of access points and base stations, localization, and coverag…
cs.CR2019
A Robust Algorithm for Sniffing BLE Long-Lived Connections in Real-time
Sopan Sarkar, Jianqing Liu, Emil Jovanov
Bluetooth Low Energy (BLE) has become an intrinsic wireless technology for the Internet of Things (IoT). With the proliferation of BLE-embedded IoT devices, it is important to stud…