26 GHz OFDM and 77 GHz FMCW Radar Dataset for Domain Shift Invariant Blockage Prediction

This dataset is the radar and groundtruth dataset linked to the paper "26 GHz OFDM and 77 GHz FMCW Radar Dataset for Domain Shift Invariant Blockage Prediction". The abstract of this paper is blow. The infor of the other part of the communication OFDM dataset in this paper can be found in the paper that is openly accessible. <br> This paper presents a novel millimeter wave communication (comms) and radar sensing co-existing dataset. The measurement campaign was performed for blockage prediction with diverse human activities. 26 GHz Orthogonal Frequency Division Multiplexing (OFDM) multi-beam communication testbed and 77 GHz Frequency-Modulated Continuous-Wave (FMCW) multiple input, multiple output (MIMO) radar multi-monostatic set-up were configured. The corresponding bistatic channel state information and multi-monostatic backscattered channels are pre-processed for preliminary domain shift analysis by means of visual pre-processed sample inspection. Domain shift inside a blockage prediction model occurs when measurement circumstances under which model training data was collected significantly differ from the model inference measurement circumstances. Domain shifts cause model performance deterioration in the inference phase. No previous millimeter wave blockage prediction research considers mitigating domain shift in prediction models. We argue that this is caused by no millimeter wave blockage prediction datasets being available with samples collected under a large number of different measurement circumstances. Analysis results indicate presence of different signature presence levels in pre-processed radar backscattered channel samples and different doppler bin energy magnitudes and locations in pre-processed OFDM testbed channel state information samples captured under varying measurement circumstances. Therefore, creating a large enough blockage prediction dataset with samples captured under varying measurement circumstances that induce hard enough domain shifts between model train and inference situations is important to allow model domain shift mitigation research.

本数据集与论文《面向域不变遮挡预测的26 GHz正交频分复用与77 GHz调频连续波雷达数据集》相关联。该论文摘要如下。本文中通信正交频分复用（Orthogonal Frequency Division Multiplexing, OFDM）数据集其余部分的相关信息，可在已公开可获取的论文中查阅。

本论文提出了一种全新的毫米波通信与雷达感知共存数据集。本次测量实验围绕多样化人体活动下的遮挡预测任务展开。实验配置了26 GHz正交频分复用（OFDM）多波束通信测试平台，以及77 GHz调频连续波（Frequency-Modulated Continuous-Wave, FMCW）多输入多输出（Multiple Input Multiple Output, MIMO）雷达多静态部署方案。我们已对对应的双基地信道状态信息与多静态反向散射信道进行预处理，通过可视化预处理样本检视的方式开展初步的域偏移（domain shift）分析。当模型训练数据的采集环境与模型推理时的测量环境存在显著差异时，遮挡预测模型便会出现域偏移问题。域偏移会导致模型在推理阶段的性能下降。此前的毫米波遮挡预测研究均未考虑在预测模型中缓解域偏移问题。我们认为，这一现状的成因在于尚未存在可在大量不同测量环境下采集样本的毫米波遮挡预测数据集。

分析结果表明，在不同测量环境下采集的预处理雷达反向散射信道样本中，特征信号的存在程度存在差异；同时，预处理后的OFDM测试平台信道状态信息样本中，多普勒仓（doppler bin）的能量幅值与位置亦存在不同。因此，构建一个规模足够大的遮挡预测数据集，使其包含在不同测量环境下采集的样本，并能在模型训练与推理场景间引发足够显著的域偏移，对于开展模型域偏移缓解研究具有重要意义。

搜集汇总

背景与挑战

背景概述

该数据集是一个毫米波通信和雷达传感共存的数据集，包含26 GHz OFDM多波束通信测试床和77 GHz FMCW MIMO雷达多单静态设置的测量数据，用于阻塞预测研究。数据集旨在支持模型域偏移缓解研究，包含不同测量环境下的预处理雷达反向散射通道和OFDM测试床信道状态信息样本。