Fundamental Limits of MIMO-OTFS and MIMO-OFDM in High-Dynamics ISAC: An Antenna Array Architecture Perspective

2026-07-22

AI Summary

This study addresses the severe Doppler shift and time-varying channel challenges in high-mobility integrated sensing and communication (ISAC) systems by developing a unified theoretical framework based on antenna array architecture. It comparatively analyzes sparse arrays (SA) and uniform linear arrays (ULA), evaluating the ergodic channel capacity and Cramér–Rao bound (CRB) for angle estimation under MIMO-OTFS and MIMO-OFDM waveforms. Leveraging random matrix theory, capacity analysis, CRB derivation, and second-order moment modeling of antenna positions, the work demonstrates that SA achieves significantly higher communication capacity due to its more uniform spatial eigenvalue distribution, and its angle estimation CRB improves quadratically with the number of antennas. The results reveal that this performance gain stems from array geometry rather than waveform choice, and under ideal conditions, MIMO-OTFS and MIMO-OFDM exhibit nearly identical performance limits.

Abstract

This paper investigates the fundamental limits of MIMO-OTFS and MIMO-OFDM integrated sensing and communications (ISAC) systems in high-mobility environments, specifically comparing sparse arrays (SA) against conventional uniform linear arrays (ULA). High-dynamics scenarios, such as V2X and satellite networks, suffer from severe Doppler shifts and rapidly time-varying channels, necessitating robust modulation schemes and efficient array geometries. A unified theoretical analysis of ergodic channel capacity and the Cramér$\unicode{x2013}$Rao bound (CRB) for angle estimation is provided. Utilizing the framework of stochastic majorization, the study reveals that SAs consistently outperform ULAs by creating a more $\unicode{x201C}$uniform$\unicode{x201D}$ spatial eigenvalue distribution, which decorrelates the multipath environment and increases communication capacity. For sensing, the paper proves that the angle CRB is inversely proportional to the array's second-order moment of antenna positions asymptotically, demonstrating that SAs achieve superior accuracy$\unicode{x2014}$improving by up to the square of the number of antennas$\unicode{x2014}$due to their increased physical aperture. Notably, the analysis shows that under relatively ideal conditions, MIMO-OTFS and MIMO-OFDM share similar fundamental limits for both capacity and angle estimation, suggesting that spatial geometry, rather than waveform, is the primary driver of fundamental performance gains in the spatial dimension.

Problem

• MIMO-OTFS
• MIMO-OFDM
• ISAC
• high-dynamics
• antenna array

Innovation

• Sparse Arrays
• MIMO-OTFS
• Integrated Sensing and Communications
• Cramér-Rao Bound
• Stochastic Majorization