17 citations · 20 across the 10 of their papers we have counts for
16 papers · 1 filter
Indoor Propagation Measurements with Sekisui Transparent Reflectors at 28/39/120/144 GHz
Chethan K. Anjinappa, Ashwini P. Ganesh, Ozgur Ozdemir +5
One of the critical challenges of operating with the terahertz or millimeter-wave wireless networks is the necessity of at least a strong non-line-of-sight (NLoS) reflected path to…
Channel Rank Improvement in Urban Drone Corridors Using Passive Intelligent Reflectors
Ender Ozturk, Chethan Kumar Anjinappa, Fatih Erden +3
Multiple-input multiple-output (MIMO) techniques can help in scaling the achievable air-to-ground (A2G) channel capacity while communicating with drones. However, spatial multiplex…
Radar Cross Section Based Statistical Recognition of UAVs at Microwave Frequencies
Martins Ezuma, Chethan Kumar Anjinappa, Mark Funderburk +1
This paper presents a radar cross-section (RCS)-based statistical recognition system for identifying/ classifying unmanned aerial vehicles (UAVs) at microwave frequencies. First, t…
Base Station and Passive Reflectors Placement for Urban mmWave Networks
Chethan Kumar Anjinappa, Fatih Erden, Ismail Guvenc
The use of millimeter-wave (mmWave) bands in 5G networks introduce a new set of challenges to network planning. Vulnerability to blockages and high path loss at mmWave frequencies…
Outdoor mmWave Base Station Placement: A Multi-Armed Bandit Learning Approach
Fatih Erden, Chethan K. Anjinappa, Ender Ozturk +1
Base station (BS) placement in mobile networks is critical to the efficient use of resources in any communication system and one of the main factors that determines the quality of…
Localization with Deep Neural Networks using mmWave Ray Tracing Simulations
Udita Bhattacherjee, Chethan Kumar Anjinappa, LoyCurtis Smith +2
The world is moving towards faster data transformation with more efficient localization of a user being the preliminary requirement. This work investigates the use of a deep learni…