Current students


DONG KAICycle: XXXIV

Section: Telecommunications
Advisor: SPAGNOLINI UMBERTO
Tutor: MONTI-GUARNIERI ANDREA VIRGILIO

Major Research topic:
Signal Processing in Massive V2X Communication Systems

Abstract:
Millimeter-wave (mm-wave) communication is a promising candidate technique in accident-free, cooperative automated driving that is enabled by the ultra-reliable low-latency communications (URLLC). However, the strict requirements in terms of ultra-high traffic volume (1 Gbps), ultra-low latency (3 ms) and packet loss (10-5) make it challenging to reach the goal of cooperative sensing and controlling in the scenario of connected automated driving (CAD) of next-generation V2X communications system [1].
The stringent performance requirements of V2X communications has high demands for massive data processing. In order to realize the continuous massive raw sensor data exchange in CAD scenario, large amounts of antenna arrays with directional beamforming will be deployed on vehicle under the V2X communication paradigm. That will inevitably argument the cost and power efficiency. Efficient/adaptive beamforming is one key and challenging technique for V2X communications system in CAD scenario. The conventional beam alignment methods are based on beam sweeping cannot effectively adopt to critical/high level of cooperative automated driving. Hence, accurate tracking and fast beam alignment methods for the moving vehicles in CAD scenario are highly demanding and difficult to achieve with lower errors.
My focus of research activity will be advanced signal processing algorithms incorporated with statistical learning methods to support URLLC and accurate positioning in massive V2X communication system. The focus aims to: (i) design reliable cooperative sensing and vehicle positioning methods in URLLC links, (ii) design and validate the algorithms to realize adaptive beam alignment and accurate tracking for moving vehicles in CAD scenario of V2X communications, (iii) comparison and performance assessment with other existing methods utilizing designed/upgraded algorithms under some specified conditions (channel model, X-band, etc.).
[1] European Telecommunications Standards Institute (ETSI), Service requirements for enhanced V2X scenarios TS 122 186, 2018-10.