Wireless Systems &
Autonomous Research Labs

Multi-Dimensional Drone Communications Infrastructure (MuDDI)
Co-PI: Dinesh Rajan (SMU)

The next wave of applications for Unmanned Aerial Vehicles (UAVs) or drones range from delivery of consumer goods or Internet connectivity during natural disasters to defense scenarios such as autonomous combat or search and rescue, all of which require coordination of multiple entities across various altitudes from in-flight to ground-based stations. However, there are two important challenges to realizing such applications. First, positioning many antennas to communicate in three dimensions is non-trivial since the load capacity in terms of power and weight is highly restricted, and the drone body may block reception on the opposite side of the antenna. Second, large-scale antenna arrays are increasingly being used to increase channel quality in a given direction. However, there is limited antenna scale on a single UAV, and the challenge of distributing the antenna array across a drone swarm is extremely complex due to constant mobility, varying relative positions, and the inability to update the channel state of all transmitting nodes. In this project, the goal is to build MuDDI, a Multi-Dimensional Drone Communication Infrastructure, which will enable indoor and outdoor experimentation with UAVs to address research issues related to 3-D connectivity, distributed antennas across a drone swarm, and 3-D swarm formations that optimize the transmission to intended receivers.

Channel Recognition for Optimized Links And Networks (CROLA)
Co-PI: Dinesh Rajan (SMU)

Wirelessly-connected users encounter a vast array of environmental settings from factors including diverse terrain, buildings, vegetation, weather conditions, and velocities. Today, when traversing across these diverse conditions, each environmental change triggers a new wireless channel characterization so that links can have optimal performance for transmission rate and frequency band decisions, both of which depend on spatial and environmental characteristics. This characterization process can induce a high overhead on the network, greatly reducing the overall performance of the wireless links which were seeking to be optimized. In this project, diverse wireless scenarios will be classified into a finite set to recognize wireless channel types and optimize per-link and network-wide decisions. The project will significantly reduce the amount of characterization that needs to be performed per environment, especially when revisiting a location or when a new location shares many similarities as those previously visited.

Theory, Algorithms, and Experiments for Frequency-Agile Beamforming Mesh (FabMesh)
Co-PI: Mung Chiang (Princeton University)

The FCC seeks to connect 19 million unserved Americans to broadband by 2020. These rural areas have yet to be fully connected to the Internet due to wireline infrastructure costs which exceed potential revenue opportunities. Even in heavily-populated environments with sufficient wireline infrastructure, capacity issues remain in congested stadiums, disaster recovery zones, and public transportation. Each aforementioned access challenge seemingly is well-suited for wireless mesh networks, but have yet to be fully solved. However, recently, there has been a sizable growth in radios operating in diverse frequency bands (e.g., TV white spaces) with emerging multi-antenna schemes. In this project, multi-user beamforming and diverse frequency bands are leveraged to significantly build upon the flexibility originally sought by mesh networks. In doing so, frequency-agile beamforming mesh (FabMesh) networks seek to truly scale in complexity and cost according to the user population and traffic demand.

CAREER: Leveraging Simultaneous Access to Multiple Frequency Bands in Multihop Wireless

Due to the culmination of the recent reapportionment of FCC frequency bands and the acceleration of wireless device complexity, simultaneous access to multiple diverse wireless frequency bands is becoming more of a reality. Naturally, the question arises: How can simultaneous access to a wide range of frequency bands with distinct propagation and communication capabilities improve current wireless network performance? In this CAREER research, a foundation is laid for exploiting multiple frequency bands for multihop wireless networks from per-link to network-wide decisions. To do so, this project uses experimental design, measurement analysis, analytical modeling, and embedded programming on an array of devices and testbeds from mobile phones globally reachable via application downloads to in-lab and in-the-field wireless infrastructures.

Dallas-ARea Testbed for Context-Aware, Cognitive Research (DART-CARs)
Co-PI: Dinesh Rajan (SMU)

Wireless system performance is known to be highly dependent upon the characteristics of the environment. Despite the increasing ability of wireless devices to sense their surroundings, wireless systems have yet to fully leverage contextual data to improve performance. To this end, DART-CARs is an NSF-funded infrastructure (NSF CISE CRI) that allows the study of wireless performance in a broad class of mobile and static environments in and around the Dallas area from indoor labs to outdoor high-way speeds within a single testbed.