# A Geometry-aided Message Passing Method for AoA-Based Short Range MIMO Channel Estimation

## TL;DR

This paper introduces a geometry-aided message passing algorithm for short-range MIMO channel estimation in mmWave wearable devices, exploiting local AoA structures to improve accuracy and reduce pilot transmissions.

## Contribution

It develops a novel geometry-based message passing method that leverages local AoA dependencies for efficient short-range MIMO channel estimation, overcoming limitations of far-field assumptions.

## Key findings

- Achieves accurate channel reconstruction with fewer pilot signals.
- Reduces pilot transmission compared to exhaustive beam search.
- Effectively exploits local AoA structures in short-range channels.

## Abstract

Short range channels commonly arise in millimeter wave (mmWave) wearable settings, where the length of the antenna arrays can be comparable to the distance between the radios. Conventional mmWave MIMO channel estimation techniques based on the far field assumption may perform poorly in short range settings due to the large angular spread and, hence, high available rank. We propose a geometry-aided message passing algorithm that exploits structure in short range line-of-sight (LoS) channels for spatial sub-Nyquist channel estimation. Our approach parametrizes the channel using angle-of-arrivals (AoAs) that are locally defined for subarrays of an antenna array. Furthermore, it leverages the dependencies between the local AoAs using factors based on the array geometry. We show that the LoS MIMO channel can be reconstructed using the derived local AoA estimates and the known transceiver geometry. The proposed approach achieves a reasonable rate with greatly reduced pilot transmissions when compared to exhaustive beam search-based local AoA estimation.