CORTEXA
← Browse
arxiveess.SP2026-07-22

SNR-Dependent Mismatched Filtering for Bistatic OFDM Ranging

Ying Zhang, Fan Liu, Yifeng Xiong, Jie Yang, Xinyi Wang, Shi Jin

This paper investigates the ranging performance of a bistatic integrated sensing and communications (ISAC) system employing orthogonal frequency-division multiplexing (OFDM), in which an ISAC transmitter emits a communication waveform carrying random data symbols, and a separate receiver performs ranging by correlating the received signal with a locally demodulated symbol sequence. Owing to inevitable demodulation errors, the ranging processor operates under mismatched filtering rather than ideal matched filtering, resulting in a delay-domain correlation response whose sidelobe structure explicitly depends on the signal-to-noise ratio (SNR). Focusing on frequency-flat fading channels, we derive closed-form expressions for the expected sidelobe level (ESL) and the average mainlobe level of the resulting mismatched ranging response for BPSK, QPSK, and general square QAM constellations. The analysis quantitatively characterizes how SNR-driven symbol decision errors reshape the delay-domain sidelobe behavior, thereby providing analytical insight into the SNR-dependent scaling behavior of ranging performance in bistatic OFDM-based ISAC systems. Simulation results validate the theoretical derivations and confirm the accuracy of the proposed analysis.

View free PDFSource page

Related papers

arxiveess.SP2026-07-16

Elliptic Range-Doppler Mapping for OFDM-ISAC under IQ Imbalance

Thrassos K. Oikonomou, Dimitrios Bozanis, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, George K. Karagiannidis

Receiver in-phase/quadrature imbalance (IQI) couples each OFDM subcarrier with its mirror counterpart, creating ghost targets and degrading range-Doppler recovery in orthogonal frequency division multiplexing (OFDM) integrated sensing and communication (ISAC). Instead of first co…

View free PDFSource page
arxiveess.SP2026-06-29

Effective Depth in Joint Source-Channel Coding: An Implicit Equilibrium Analysis

Kaiwen Yu, Gang Wu, Xiaodong Xu, Yi Ma, Rahim Tafazolli

A fundamental design question in deep joint source-channel coding (Deep JSCC) remains insufficiently explored: given a channel signal-to-noise ratio (SNR), what effective computation depth is required for semantic reconstruction? Existing Deep JSCC systems typically employ fixed-…

View free PDFSource page
arxiveess.SP2026-07-23

Constellation Selection and Power Allocation for Multi-Cell OFDM-ISAC: Managing Inter-Cell Interference and Sensing Sidelobes

Kaitao Meng, Kawon Han, Christos Masouros, Lajos Hanzo

Future integrated sensing and communication (ISAC) networks are expected to operate in dense multi-cell environments, where multiple base stations (BSs) share their time-frequency resources for communication and sensing. In such scenarios, the delay--Doppler (DD) sensing performa…

View free PDFSource page
arxiveess.SP2026-07-31

Multi-User MIMO Enhancement using Metasurface Wavefront Bending (MWB)

Xiaolu Yang, Oscar Cespedes Vicente, Christophe Caloz

This paper introduces metasurface wavefront bending (MWB) to enhance spatial multiplexing in radiative nearfield multi-user multiple-input multiple-output (MU-MIMO) systems. By increasing spherical-wave curvature, MWB strengthens range-dependent phase variations across the receiv…

View free PDFSource page
arxiveess.SP2026-07-16

Jacobi Elliptic Chirps for Sub-Nyquist Multi-Target Ranging

Dimitrios Bozanis, Thrassos K. Oikonomou, Sotiris A. Tegos, Panagiotis D. Diamantoulakis, George K. Karagiannidis

Sub-Nyquist sampling is an attractive way to reduce the hardware cost of wideband pulse-compression radar, but it introduces coherent alias-induced replicas in the matched-filter range profile, producing spurious peaks known as ghost targets. Existing frequency-modulated waveform…

View free PDFSource page
arxiveess.SP2026-07-22

Lightweight Gated Recurrent Unit Variants for Real-Time Channel Prediction

Kyriakos Christodoulides, Kyriakos M. Deliparaschos, Risto Wichman, Themistoklis Charalambous

Machine-learning-based channel predictors must operate under stringent latency, memory, and computational constraints while remaining robust to noisy and time-varying observations. This paper develops a causal channel-prediction framework based on three single-layer gated recurre…

View free PDFSource page