Multi-Mode Spatial Signal Processor with Rainbow-like Fast Beam Training and Wideband Communications using True-Time-Delay Arrays
Chung-Ching Lin, Chase Puglisi, Veljko Boljanovic, Han Yan, Erfan, Ghaderi, Jayce Gaddis, Qiuyan Xu, Sreeni Poolakkal, Danijela Cabric, and, Subhanshu Gupta

TL;DR
This paper introduces a reconfigurable true-time-delay spatial signal processor for millimeter-wave 5G networks, enabling fast, wideband beam training and communication with minimized latency and high efficiency.
Contribution
It proposes a novel TTD-based SSP with frequency-division beam training and wideband operation, supported by an automated testbed for extensive characterization.
Findings
Supports 800 MHz bandwidth with 3.8 ns delay range
Achieves nearly 12 dB frequency-independent gain
Prototyped in 65nm CMOS with 29 mW power consumption
Abstract
Initial access in millimeter-wave (mmW) wireless is critical toward successful realization of the fifth-generation (5G) wireless networks and beyond. Limited bandwidth in existing standards and use of phase-shifters in analog/hybrid phased-antenna arrays (PAA) are not suited for these emerging standards demanding low-latency direction finding. This work proposes a reconfigurable true-time-delay (TTD) based spatial signal processor (SSP) with frequency-division beam training methodology and wideband beam-squint less data communications. Discrete-time delay compensated clocking technique is used to support 800~MHz bandwidth with a large unity-gain bandwidth ring-amplifier (RAMP)-based signal combiner. To extensively characterize the proposed SSP across different SSP modes and frequency-angle pairs, an automated testbed is developed using computer-vision techniques that significantly…
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Taxonomy
TopicsAntenna Design and Optimization · Microwave Engineering and Waveguides · Millimeter-Wave Propagation and Modeling
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
