Multifeed Lens Antennas for Next-G Communications and Sensing

Date
2024-04-22
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Abstract

As we edge towards higher frequencies for future communication needs, the significance of enhanced Effective Isotropic Radiated Power (EIRP) becomes paramount to counter the escalating path loss. Future 6G communications at millimeter wave frequencies typically require an EIRP of 75dBm. Consequently, minimizing DC power consumption at this high EIRP level becomes a critical issue. Moreover, constraints posted by narrow bandwidth and unpredictable user movement necessitate fast beam switching time and beam-steering decision speed. Relative to conventional lens antenna and phased array methodologies at millimeter wave frequencies, our proposed innovation offers superior DC power to EIRP efficiency, simultaneously maintaining or enhancing the achievable EIRP.

This thesis initially introduces foundational knowledge concerning single lens antenna. Subsequently, a novel generalized lens array topology is developed, employing ray-tracing calculations and HFSS simulations. This design ensures high gain, broad beam steering capabilities, swift beam switching, and elevated data rates, all while ensuring maximal DC to EIRP efficiency, reduced dimensions, and compatibility with Multiple Input Multiple Output (MIMO) systems. After that, the thesis delves into the experimental efforts to overcome the hurdles in fully demonstrating a D-band lens array. The characterization of Mt77 material is undertaken to assess the inherent routing loss. A 3D antenna radiation pattern testing system is established, confirming the gain enhancement of a single lens antenna. Furthermore, tailored PCB boards featuring Flip-Chip Buffer (BF) chips were developed and assessed to elucidate the principal flip-chip losses within our packaging approach.

Description
EMBARGO NOTE: This item is embargoed until 2025-08-01
Degree
Master of Science
Type
Thesis
Keywords
EIRP, beam steering, Gain
Citation

Wang, Hang. Multifeed Lens Antennas for Next-G Communications and Sensing. (2024). Masters thesis, Rice University. https://hdl.handle.net/1911/117749

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