Robotic Wireless Networks

There is growing agreement that wireless capacity (at the PHY and MAC layers) is reaching saturation. Many believe that the next ?jump? in network capacity will emerge from new ways of organizing networks. While there exists substantial work on new network architectures, one assumption that most proposals seem to make is that infrastructure ? WiFi APs, enterprise WLANs, cell towers ? is static. This project considers the possibility of relaxing this assumption and explores the implications of physically moving wireless network infrastructure to improve/optimize desired performance metrics. For example, we envision WiFi access points on wheels that move within a small region to exploit the multipath nature of wireless signals; in the future, we envision drones flying into high demand areas, hovering at strategic locations, and serving as cellular proxies to ground clients. This project is a foray into the landscape of such "robotic wireless networks".

smart home


     Experimentation Platform (Mobile WiFi Access Point):


Figure above shows an iMob AP assembled using a Roomba iRobot 2.1, a webcam, and a laptop equipped with  Intel 5300 802.11n cards. The laptop is mounted on the iRobot and connected to it over the serial interface; it is also connected to a Microsoft live cam (attached in front of the iRobot) to guide its motion. The laptop acts as the controller for the whole system, sending motion commands to the robot (via the OSI interface), while also controlling the network interface for transmission/reception. 8 laptop clients were uniformly scattered at various locations and programmed to communicate back to the iMob AP. The robot?s mobility is confined within a 2x2 feet square region, demarcated by colored duct tapes pasted on the floor. If the robot drifts out of the square box, the camera detects the color of the duct tapes and triggers a change in heading direction. The AP performs ?raster scans? within the square box at a speed of 10 cm/sec ? during the scan, the AP continuously sends around 200 packets/second, equivalent to 60 packets per 3cms. Transmissions are performed on regular OFDM with 3x3 MIMO at both 2.4GHz and 5GHz bands. Clients record the per-packet channel state information (CSI) for offline analysis.

     Experimentation Platform (Cellular Extension through Drones):


The above figures shows a drone carrying a WiFi router providing coverage to potential clients spread across an outdoor area. Reducing the search space for placement of the drone is achieved through use of ray-tracing techniques over a 3D model of the large structures and terrain.
The ray-tracing estimates are used as a guide and the drone performs real measurements in the vicinity of this guided location. This achieves close to Oracle gains for most clients.

         Main Results (Mobile WiFi Access Point):

real gain

         Main Results (Cellular Extension through Drones):
DroneNet gain


Future Directions:

  • Mobile access points can be extended to run on rails inside false ceilings in buildings. Linear tracks with more accurate and fast repositioning abilities will have new set of challenges, but in offices and shop-floors, such mechanism might be easy to realize.
  • Use of drones as cell tower extensions would need many more innovations beyond just the search problem of where to place the drone. However, even in this space, we have not yet used the rich Channel State Information (CSI) available in MIMO systems. Client mobility will add to the challenges of DroneNet.

          UIUC/USC Collaboration:
  • Periodic brainstorming sessions and discussions with PI Nelakuditi and his team from USC. The discussions are mainly focussed on characterizing the practical aspects of Robotic Networks, namely the ramifications of imprecise motion of the robot, the limits of velocity, the difficulty in instantaneous braking, etc. These discussions have led to ironing out various pragmatic parts of the paper -- the findings and experiences from these exercises are being prepared for a submission to the IEEE Transactions of Mobile Computing. PI Roy Choudhury and Nelakuditi also submitted a CRI proposal to NSF.
  • Rufeng Meng, one of PI Nelakuditi's PhD students, visited UIUC from Summer 2015 to Fall 2015. He was collaborating on various aspects of mobility algorithms.
  • Ongoing collaboration with the USC team is focussing on drones and how they could serve as proxies to cellular towers, i.e., a drone flies into a region of high network congestion, positions itself strategically, and offers WiFi connectivity with cellular backhaul to the actual cell tower. Algorithmic questions pertain to the "search algorithm" so that the drone could find the best "hovering location".

          Educational and Outreach Activities:
  • Included in course material for "ECE/CS 498: Mobile Computing and Applications"
  • Invited seminar at the "Robotics Applications Workshop" at UC Berkeley
  • Planning on showcasing iMob at UIUC's Engineering Open House, 2017.
  • Short talk at NSF Workshop on Wireless Testbeds and Platforms

                               nsf funding         huawei