# On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective

arXiv: https://arxiv.org/abs/2211.00434 · HTML: https://mlsanity.com/paper/2211.00434/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Nov 2022.

## Built on by (most cited first, 2 of 2)

- [Synesthesia of Machines (SoM)-Enhanced ISAC Precoding for Vehicular Networks with Double Dynamics](https://mlsanity.com/paper/2408.13546/) (2024)
- [Synesthesia of Machines (SoM)-Enhanced Sub-THz ISAC Transmission for Air-Ground Network](https://mlsanity.com/paper/2506.12831/) (2025)

## Abstract (arXiv)

In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation. To begin with, we consider a multi-input multi-output (MIMO) ISAC system and reveal that the optimal ISAC signal is in the subspace spanned by the transmitted steering vectors of the sensing channel and the right singular matrix of the communication channel. By leveraging this result, we study a basic ISAC scenario with a single target and a single-antenna communication user, and derive the optimal waveform covariance matrix for minimizing the estimation error under a given communication rate constraint. To quantify the integration gain of ISAC systems, we define the subspace "correlation coefficient" to characterize the coupling effect between S&C channels. Finally, numerical results are provided to validate the effectiveness of the proposed approaches.