Dualband OFDM Delay Estimation for Multi-Target Localization

TL;DR

The paper addresses delay estimation for dual-band OFDM in ILC under fragmented spectrum by introducing a PSF-centric model that links subcarrier layout to delay resolution via the PSF $p(\tau)$. It adapts the RELAX algorithm to perform PSF deconvolution, enabling robust multi-target delay estimation from non-contiguous measurements. Key contributions include analytical characterization of the dual-band PSF, a RELAX-based dual-band delay estimator, and practical guidelines for choosing the inter-band gap to balance resolution against sidelobe-induced ambiguity and noise sensitivity. The results demonstrate improved robustness and accuracy in dual-band scenarios, supporting ILC performance under fragmented spectrum and informing waveform design.

Abstract

Integrated localization and communication systems aim to reuse communication waveforms for simultaneous data transmission and localization, but delay resolution is fundamentally limited by the available bandwidth. In practice, large contiguous bandwidths are difficult to obtain due to hardware constraints and spectrum fragmentation. Aggregating non-contiguous narrow bands can increase the effective frequency span, but a non-contiguous frequency layout introduces challenges such as elevated sidelobes and ambiguity in delay estimation. This paper introduces a point-spread-function (PSF)-centric framework for dual-band OFDM delay estimation. We model the observed delay profile as the convolution of the true target response with a PSF determined by the dual-band subcarrier selection pattern, explicitly linking band configuration to resolution and ambiguity. To suppress PSF-induced artifacts, we adapt the RELAX algorithm for dual-band multi-target delay estimation. Simulations demonstrate improved robustness and accuracy in dual-band scenarios, supporting ILC under fragmented spectrum.

Figures (5)

• Figure 1: Subcarrier selection functions (SCFs) (top row) and the corresponding point-spread functions (PSFs) (bottom row) for different center-frequency gaps $f_{\mathrm{gap}}$. Each subband has bandwidth $B_{\mathrm{sub}}=40$ MHz.
• Figure 2: Single-target delay RMSE versus SNR for different center-frequency gaps $f_{\mathrm{gap}}$, together with the corresponding Cramér--Rao bounds (CRBs).
• Figure 3: Delay profile comparison: IDFT-based dual-band profile and RELAX reconstruction.
• Figure 4: Delay RMSE comparison of OMP and RELAX.
• Figure 5: Impact of center-frequency gap $f_{\mathrm{gap}}$ on RELAX performance.