Implements semantic equalization for DeepJSCC, addressing mismatched latent spaces between transmitter and receiver models. Evaluates linear, neural, and zero-shot equalizers for aligning heterogeneous semantics. Enables robust, efficient communication in AI-native wireless systems.
This repo implements a MIMO-based method for semantic communications, learning precoder/decoder pairs to compress latent spaces and align semantics across devices. Includes both a linear ADMM-based model and a neural model under power and complexity constraints.
Canonical public-facing resources for Solarity AI LLC, including pitch decks, one-pagers, job descriptions, brand assets, and company documentation.
This repository implements the Parseval Frame Equalizer (PFE), a zero-shot semantic channel equalization framework for AI-native wireless systems. The approach aligns heterogeneous latent spaces without retraining, leveraging relative representations and Parseval frame theory to achieve semantic alignment, compression, and reconstruction.
To associate your repository with the ai-native-communication topic, visit your repo's landing page and select "manage topics."