With the proliferation of bandwidth hungry mobile devices, dense deployments of users, and the proliferation of Internet of Things (IoT) technologies, broadband spectrum needs have been continuously increasing in recent years. The use of the millimeter wave (mmWave) frequency bands is seen as a major way to address this spectrum crunch problem since large amounts of licensed and unlicensed bandwidths are available at these frequencies, leading to new standards being developed for 5G cellular and Wi-Fi using mmWave. In parallel, there have been unprecedented recent advances in commercial unmanned aerial vehicle (UAV) technologies, which has resulted in their adoption in a wide range of applications, such as disaster relief, agricultural monitoring, wireless connectivity in rural areas, and hotspot connectivity for major sporting events. The proposed research in this project aims to study the foundations of mmWave communications in UAVs in a systematic manner using notions from wireless networks, communication theory, optimization theory, and software defined radios (SDRs), starting from channel sounding and characterization. The data collected from this project will be made public and disseminated via the 5G Millimeter Wave Channel Modeling Alliance. The project will train both graduate students and undergraduate students across multiple institutions in an emerging area of national interest.
A key challenge in any mmWave communication is that beamforming needs to be used in order to overcome the path loss. The use of mmWave on UAVs poses additional challenges and benefits. The challenges are primarily due to limited battery life and weight carrying capability of UAVs and the benefits accrue from the use of: 1) large bandwidth; 2) ability to implement 3D beamforming enabling improved spatial reuse; and 3) harnessing the UAV mobility to perform dynamic UAV clustering and interference management. The goal of this project is to address these fundamental challenges via a unique research collaboration focused on developing the next-generation of analytical and experimental tools for designing, modeling, optimizing, and testing mmWave UAV networks. Specific areas of study will include: (i) novel precoder designs for mmWave UAVs taking into account realistic propagation characteristics derived from channel sounding experiments; (ii) equalizer design for mmWave UAVs that trade-off beamwidth against equalizer structure; (iii) multiple access design for mmWave UAVs: code division and time division multiple access techniques will be revisited for mmWave UAV communications, for serving users that are accessed by the same transmitter beam; and (iv) optimal UAV placement for multi-hop wireless backhaul by investigating the use of UAVs as flying relays.
