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Found 9 papers, 0 papers with code
An Aliasing-Free Hybrid Digital-Analog Polyphonic Synthesizer
At the heart of the synthesizer is the big Fourier oscillator (BFO), a novel digital very-large scale integration (VLSI) design that utilizes additive synthesis to generate a wide variety of aliasing-free waveforms.
5G Features and Standards for Vehicle Data Exploitation
Cars capture and generate huge volumes of data in real-time about the driving dynamics, the environment, and the driver and passengers' activities.
A Resolution-Adaptive 8 mm$^\text{2}$ 9.98 Gb/s 39.7 pJ/b 32-Antenna All-Digital Spatial Equalizer for mmWave Massive MU-MIMO in 65nm CMOS
All-digital millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) receivers enable extreme data rates but require high power consumption.
Resolution-Adaptive All-Digital Spatial Equalization for mmWave Massive MU-MIMO
All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral efficiency, flexibility, and baseband-processing simplicity over hybrid analog-digital solutions.
Analog vs. Digital Spatial Transforms: A Throughput, Power, and Area Comparison
Spatial linear transforms that process multiple parallel analog signals to simplify downstream signal processing find widespread use in multi-antenna communication systems, machine learning inference, data compression, audio and ultrasound applications, among many others.
High-Bandwidth Spatial Equalization for mmWave Massive MU-MIMO with Processing-In-Memory
All-digital basestation (BS) architectures enable superior spectral efficiency compared to hybrid solutions in massive multi-user MIMO systems.
WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic
Low-resolution neural networks represent both weights and activations with few bits, drastically reducing the multiplication complexity.
Siamese Neural Networks for Wireless Positioning and Channel Charting
In this paper, we propose a unified architecture based on Siamese networks that can be used for supervised UE positioning and unsupervised channel charting.
Improving Channel Charting with Representation-Constrained Autoencoders
Channel charting (CC) has been proposed recently to enable logical positioning of user equipments (UEs) in the neighborhood of a multi-antenna base-station solely from channel-state information (CSI).
