Compact Heterogeneous Integration for Next Generation High Frequency Scalable Array with Miniaturized and Efficient Power Delivery Network
Najme Ebrahimi

TL;DR
This paper presents a compact, efficient heterogeneous integration approach for high-frequency arrays, reducing parasitics and loss to enable miniaturized systems with high bandwidth and power efficiency.
Contribution
It introduces novel packaging and power delivery techniques for integrated high-frequency arrays, achieving wideband operation and high efficiency in a compact form.
Findings
Achieved 9 Gb/s data rate with 64 QAM modulation.
Demonstrated 20% fractional bandwidth operation from 71-86 GHz.
Enhanced power efficiency with 25% EIRP/PDC ratio.
Abstract
Next generation communication and sensing require enabling technologies for miniaturized and efficient heterogeneous systems while integrating technologies ranging from silicon to compound semiconductors and from photonic chips to micro-sensors. To this end, high frequency and mm-wave (MMW) lossy parasitics and delay between modules need to be significantly reduced to minimize area, loss and thermal heating of inter-chip wiring and power delivery networks. In this work, we propose novel approaches to achieve an efficient wideband MMW array integrations. The proposed techniques are built upon the following: 1) fixed antenna package buildup for every element with differential excitation on two half sides of array to reduce the fabrication cost and the IC-to-antenna routing loss; 2) miniaturized aperture coupled local oscillator (LO) and intermediate frequency (IF) power delivery feed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMicrowave Engineering and Waveguides · Radio Frequency Integrated Circuit Design · Energy Harvesting in Wireless Networks
MethodsExtreme Value Machine
