Analog Subspace Coding: A New Approach to Coding for Non-Coherent Wireless Networks

TL;DR

This paper introduces a new framework for subspace coding in non-coherent wireless networks, defining an analog operator channel and proposing Grassmann codes constructed via polynomial evaluations and characters, improving rate-distance trade-offs.

Contribution

It presents a novel analog subspace coding framework, including a new construction method for Grassmann codes using polynomial evaluations and character mappings.

Findings

CP codes outperform existing Grassmann codes in rate-distance trade-offs

The model demonstrates robustness against additive noise

New distance metric effectively captures code performance in interference scenarios

Abstract

We provide a novel framework to study subspace codes for non-coherent communications in wireless networks. To this end, an analog operator channel is defined with inputs and outputs being subspaces of $\mathbb{C}^n$. Then a certain distance is defined to capture the performance of subspace codes in terms of their capability to recover from interference and rank-deficiency of the network. We also study the robustness of the proposed model with respect to an additive noise. Furthermore, we propose a new approach to construct subspace codes in the analog domain, also regarded as Grassmann codes, by leveraging polynomial evaluations over finite fields together with characters associated to finite fields that map their elements to the unit circle in the complex plane. The constructed codes, referred to as character-polynomial (CP) codes, are shown to perform better comparing to other existing constructions of Grassmann codes in terms of the trade-off between the rate and the normalized minimum distance, for a wide range of values for $n$.