Abstract: Millimeter-wave (mmWave) technology plays a central role in next-generation (5G & 6G) wireless networking, IoT, wireless sensing, and radar imaging. Millimeter-wave frequencies (> 24 GHz) offer a huge amount of bandwidth that enables wireless networks to deliver multi-Gbps links and provides wireless sensing systems with the ability to estimate time of flight with sub-nanosecond accuracy. Millimeter-wave radios, however, must use very directional antennas to focus their power and compensate for the signal attenuation at such high frequencies. The directionality of mmWave radios introduces new challenges in wireless networks in terms of mobility and blockage but at the same time delivers new opportunities in terms of dense spatial reuse and 3D radar imaging. In this talk, I will present our work on pushing the performance limits of millimeter-wave systems by addressing these new challenges and exploiting the new opportunities. First, I will present results on fast beamforming and alignment algorithms as well as medium access protocols for enabling dense spatial reuse in mmWave networks. Then, I will highlight our work on enabling through fog high-resolution mmWave imaging for self-driving cars using generative adversarial networks. Finally, I will discuss our recent work on millimeter-wave wireless network-on-chip. 

Speaker Bio: Haitham Hassanieh is an assistant professor in the ECE and CS departments at UIUC. He received his Ph.D. in Electrical Engineering and Computer Science from MIT. His areas of expertise are wireless networks, mobile systems, and algorithms. He has won multiple awards including MobiSys Best Paper Award, SIGCOMM Best Paper Award, the Sprowls award for best thesis in computer science at MIT, the TR10 award for Technology Review Top 10 Breakthrough Technologies, the NSF Career Award, the Alfred Sloan Foundation Fellowship, and the ACM Doctoral Dissertation Award.