IMNet: Intercarrier Interference Mitigation Network for Integrated Sensing and Communication in Spectrally Efficient FDM Systems

Abstract

Spectrally efficient frequency-division multiplexing (SEFDM) is an attractive waveform to improve communication spectral efficiency by compressing the subcarrier spacing, yet its use for integrated sensing and communication (ISAC) poses a fundamental sensing challenge. Specifically, the intentional loss of subcarrier orthogonality generates SEFDM-induced intercarrier interference (S-ICI), which combines with Doppler-induced ICI (D-ICI) from moving targets to blur range--velocity maps and severely degrade sensing accuracy. Building on multi-user multi-input-multi-output (MIMO) SEFDM systems, this paper develops a model-driven ISAC framework that supports spectrally efficient multi-user communication while mitigating both S-ICI and D-ICI in sensing. To this end, an intercarrier interference mitigation network (IMNet) is proposed, which exploits the distinct physical structures of the two interferences. A bank of Doppler correction filters first compensates the velocity-dependent D-ICI over multiple Doppler hypotheses, and an axial-attention network subsequently suppresses the residual D-ICI and the long-range S-ICI to recover reliable sensing signals. To further improve range and velocity estimation accuracy, IMNet with local refinement (IMNet-LR) is proposed, which performs maximum-likelihood refinement with nuisance projection around the IMNet detections to achieve sub-cell precision without an exhaustive global search. Simulation results show that IMNet-LR achieves near-maximum-likelihood range and velocity estimation accuracy with more than three orders of magnitude lower execution time compared to conventional detection methods.