Real time parameter estimation for adaptive OFDM/OTFS selection

TL;DR

This paper introduces a real-time parameter estimation method using ISAC to dynamically select between OFDM and OTFS waveforms, improving high mobility communication performance.

Contribution

It presents a novel adaptive strategy leveraging ISAC for real-time channel parameter estimation to optimize waveform selection in wireless systems.

Findings

Outperforms existing waveform selection methods in high mobility scenarios

Enhances system adaptability with low complexity

Demonstrates improved data transmission reliability

Abstract

Future wireless communication systems must simultaneously address multiple challenges to ensure accurate data detection, deliver high Quality of Service (QoS), adding enable a high data transmission with low system design. Additionally, they need to reduce energy consumption and latency without increasing system complexity. Orthogonal Frequency Division Multiplexing (OFDM) is a commonly used waveform in 4G and 5G systems, it has limitations in handling significant delay and Doppler spread in high mobility scenarios. To overcome these weaknesses, a novel waveform named Orthogonal Time Frequency Space (OTFS) has been proposed, which aims to improve upon OFDM by closely matching signals to channel behavior. In this study, we propose a novel strategy that enables operators to dynamically select the best waveform based on estimated mobile user parameters. We use an Integrated Radar Sensing and Communication System (ISAC) to estimate delay and Doppler, as well as speed and range. This approach allows the base station to adapt to the mobile target, thereby enhancing the performance of wireless communication systems in high mobility and low complexity scenarios. Simulation results demonstrate the effectiveness of our proposed approach and show that it outperforms existing methods.