Agenda

PhD Thesis Defence

• Thursday, 10 October 2024
• 12:00-15:00
• Aula

Millimeter-Wave Transceiver Frontends for Broadband, Energy-Efficient, and Linear Phased-Array Systems

Millimeter-wave (mm-wave) communication systems have been considered as key enablers for developing the fifth-generation (5G) of a mobile network, offering high data throughput, low network latency, and improved link robustness. Taking advantage of mm-wave phased arrays empowers 5G communication systems to establish directional links with large bandwidths between the base station and user equipment. Despite its huge potential, mm-wave 5G has several natural disadvantages. The shorter wavelength of mm-wave signals results in lower penetrability, higher free-space path loss, and susceptibility to atmospheric attenuation, limiting coverage. Additionally, 5G systems, requiring high data throughput and complex modulation, face challenges such as increased receiver noise and sensitivity, reduced link budgets, and limitations in transmitter power and efficiency due to nanoscale CMOS constraints and high PAPR, which also impacts system reliability and thermal management.

Unlike the digital front-end and computing processors, whose performance and power efficiency are significantly improved by technology scaling, the performance improvement of the analog front-end (RF/mm-wave and baseband circuitry) mainly relies on circuits and architectural innovations. Luckily, operating at mm-wave frequencies unlocks new op-portunities to address its natural challenges and innovate beyond initial expectations. This dissertation introduces a series of innovative designs and techniques to enhance the performance and efficiency of power amplifiers (PAs) and transceivers for 5G mm-wave systems.

PhD Thesis Defence

• Monday, 18 November 2024
• 17:30-19:30
• Aula Senaatszaal

Angle Estimation and Target Detection with Automotive Radar. Machine Learning and Compressive Sensing Approaches