Cross-Domain Dual-Functional OFDM Waveform Design for Accurate Sensing/Positioning

TL;DR

This paper introduces two innovative cross-domain OFDM waveform optimization strategies that enhance simultaneous sensing, positioning, and high-speed communication by resource allocation and waveform design adjustments.

Contribution

It proposes novel cross-domain waveform optimization methods for OFDM that balance communication and sensing/positioning performance based on different criteria.

Findings

Optimized resource allocation improves data rate and sensing accuracy.

Power and phase adjustments reduce sidelobe levels and PAPR.

Numerical results confirm the effectiveness of the proposed designs.

Abstract

Orthogonal frequency division multiplexing (OFDM) has been widely recognized as the representative waveform for 5G wireless networks, which can directly support sensing/positioning with existing infrastructure. To guarantee superior sensing/positioning accuracy while supporting high-speed communications simultaneously, the dual functions tend to be assigned with different resource elements (REs) due to their diverse design requirements. This motivates optimization of resource allocation/waveform design across time, frequency, power and delay-Doppler domains. Therefore, this article proposes two cross-domain waveform optimization strategies for effective convergence of OFDM-based communications and sensing/positioning, following communication- and sensing-centric criteria, respectively. For the communication-centric design, to maximize the achievable data rate, a fraction of REs are optimally allocated for communications according to prior knowledge of the communication channel. The remaining REs are then employed for sensing/positioning, where the sidelobe level and peak-to-average power ratio are suppressed by optimizing its power-frequency and phase-frequency characteristics for sensing performance improvement. For the sensing-centric design, a `locally' perfect auto-correlation property is ensured for accurate sensing and positioning by adjusting the unit cells of the ambiguity function within its region of interest (RoI). Afterwards, the irrelevant cells beyond RoI, which can readily determine the sensing power allocation, are optimized with the communication power allocation to enhance the achievable data rate. Numerical results demonstrate the superiority of the proposed waveform designs.