Breaking the CP Limit: Robust Long-Range OFDM Sensing via Interference Cleaning

TL;DR

To combat the ISI and ICI-based interference-noise floor increase, joint-interference cancellation with coherent compensation is proposed, an efficient evolution of the successive-interference cancellation algorithm, utilizing high-precision chirp Z-transform estimation and frequency-domain coherent compensation to recover weak distant targets.

Abstract

In orthogonal frequency-division multiplexing-based radar and integrated sensing and communication systems, the sensing range is traditionally limited by the round-trip time corresponding to the cyclic prefix duration. Targets whose echoes arrive after this duration induce intersymbol interference (ISI) and associated intercarrier interference (ICI), which significantly degrade detection performance, elevate the interference-noise floor in the radar image, and reduce the useful signal power due to window mismatch. Existing methods face a trade-off between recovering useful signal and suppressing interference, particularly in multi-target scenarios. This paper proposes two frameworks to resolve this dilemma, offering a flexible trade-off between computational cost and target detection performance. First, a signal model is derived, demonstrating that ISI and ICI-oriented interference often dominates thermal noise in high-dynamic-range scenarios. To combat the ISI and ICI-based interference-noise floor increase, joint-interference cancellation with coherent compensation is proposed. This approach is an efficient evolution of the successive-interference cancellation algorithm, utilizing high-precision chirp Z-transform estimation and frequency-domain coherent compensation to recover weak distant targets. For scenarios requiring maximum precision, the full reconstruction-based sliding window scheme is presented, which shifts the receive window to capture optimal signal energy while performing full-signal reconstruction for all detected targets. Numerical results show that both methods outperform state-of-the-art benchmarks.

Figures (8)

• Figure 1: Considered ISAC system model.
• Figure 2: Received OFDM signal for two different targets, upper is for the target in the ISI free region and lower is for the non-ISI free region.
• Figure 3: Received power profile versus range for a target with 20 dBsm RCS. The effective received power is shown as (). The maximum ISI range $R_{\text{max,ISI}}$ is indicated by (). Noise floors are depicted as follows: Thermal noise is shown as (), and 12-bit quantization noise as (). The interference power is indicated by (). The effective received signal, including processing gain, is represented by (), and the peak power in the radar image by ().
• Figure 4: Analysis of noise, interference levels, and maximum detectable range versus interference source RCS. (a) Comparison of noise and interference power levels. Interference power is represented by (), thermal noise by (), and quantization noise by (). (b) Maximum detectable range for target RCS values of $0~\mathrm{dBsm}$ (), $10~\mathrm{dBsm}$ (), and $20~\mathrm{dBsm}$ (). The maximum unambiguous range limit is indicated by (), and the ISI-free range limit by ().
• Figure 5: SINR comparison for the weak target against RCS. The empirical detection threshold is indicated by (). The theoretical ideal SNR is shown in ($\square$). The existing methods are shown with lines: SW ($\times$), 15 iteration SIC ($\square$), TDCC ($\triangle$), FDCC ($\triangledown$), and MTCC ($\Diamond$). The proposed methods are shown with: SIC-CC ($\bigstar$) and FR-SW ($\bigstar$).