Multicarrier ISAC: Advances in Waveform Design, Signal Processing and Learning under Non-Idealities

TL;DR

The paper surveys multicarrier ISAC design for 5G/6G, emphasizing MC waveforms and joint waveform design with multi-antenna processing under hardware non-idealities. It develops MIMO-OFDM signal models for transmit, radar, and communications receivers, defines radar and communications KPIs, and discusses MCPC and 6G waveform options. It analyzes non-idealities such as PA nonlinearity, ICI, phase noise, SI, and antenna impairments, proposing mitigation and exploitation strategies, including dictionary learning and ICI/PN exploitation. It presents structured optimization and learning-based methods (supervised and reinforcement learning) to achieve ISAC trade-offs and outlines future directions including RIS, THz, security, and privacy in MC-ISAC systems.

Abstract

This paper addresses the topic of integrated sensing and communications (ISAC) in 5G and emerging 6G wireless networks. ISAC systems operate within shared, congested or even contested spectrum, aiming to deliver high performance in both wireless communications and radio frequency (RF) sensing. The expected benefits include more efficient utilization of spectrum, power, hardware (HW) and antenna resources. Focusing on multicarrier (MC) systems, which represent the most widely used communication waveforms, it explores the co-design and optimization of waveforms alongside multiantenna transceiver signal processing for communications and both monostatic and bistatic sensing applications of ISAC. Moreover, techniques of high practical relevance for overcoming and even harnessing challenges posed by non-idealities in actual transceiver implementations are considered. To operate in highly dynamic radio environments and target scenarios, both model-based structured optimization and learning-based methodologies for ISAC systems are covered, assessing their adaptability and learning capabilities under real-world conditions. The paper presents trade-offs in communication-centric and radar-sensing-centric approaches, aiming for an optimized balance in densely used spectrum.

Figures (8)

• Figure 1: Overview of the scope of the paper. Cooperative and co-designed RF sensing and wireless communications subsystems use MC waveforms for mutual benefit while dealing with various impairments.
• Figure 2: Generation of a $N \times L$ MCPC pulse comprised of $N$ subcarriers modulated by phase codes of length $L$. The intercarrier spacing is ${1}/{T_c}$ and the overall symbol duration is $T = LT_c$. Intercarrier spacing is increased to maintain orthogonality when spreading takes place.
• Figure 3: Impact of ICI on the range profile of OFDM radar with the parameters $f_c = 28 \, \rm{GHz}$, $\Delta f = 60 \, \rm{kHz}$, $N = 1024$ and $M = 16$, in the presence of $3$ targets having the same velocity $v$, the ranges $(30, 120, 160) \, \rm{m}$ and the SNRs (quantified by $\lvert\alpha_k\rvert^2/ \sigma_{\rm{r}} ^2$ in \ref{['eq_y_ici']}) $(30, -10, -10) \, \rm{dB}$, respectively. The range profiles are obtained via standard 2-D FFT processing Sturm11Fan_ISAC_6G_JSAC_2022 on \ref{['eq_y_ici']}. In scenarios characterized by high mobility, ICI results in elevated side-lobe levels and can obscure weaker targets, leading to missed detections.
• Figure 4: Impact of PN on the range profile of OFDM radar with the parameters $f_c = 28 \, \rm{GHz}$, $\Delta f = 120 \, \rm{kHz}$, $N = 512$ and $M = 8$, in the presence of $2$ targets with the ranges $(20, 110) \, \rm{m}$, the velocities $(0, 0) \, \rm{m/s}$ and the SNRs (quantified by $\lvert\alpha_k\rvert^2/ \sigma_{\rm{r}} ^2$ in \ref{['eq_y_pn']}) $(30, -5) \, \rm{dB}$, respectively. The oscillator is a free-running oscillator with the $3 \,\rm{dB}$ bandwidth $100 \, \rm{kHz}$. The range profiles are obtained via standard 2-D FFT processing Sturm11Fan_ISAC_6G_JSAC_2022 on \ref{['eq_y_pn']}. PN leads to increased side-lobe levels and can mask weaker targets.
• Figure 5: ICI exploitation to resolve Doppler ambiguity of high-speed targets and enhance target separability/resolvability via the use of additional Doppler information in $\mathbf{D} (\nu)$ in \ref{['eq_y_ici']}. The OFDM parameters are $f_c = 60 \, \rm{GHz}$, $N = 512$, $B = 100 \, \rm{MHz}$ and $M = 16$.