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.

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.

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.