低轨卫星信号重构及低复杂度检测测试数据集

本数据集为基于压缩感知的信号重构及低复杂度检测研究部分的实验数据。星地距离远，传播延迟大，传统基于授权的方式难以满足天基物联网低时延应用需求。免授权随机接入摒弃了传统授权接入方案中繁琐的信令交互，能有效降低信令开销、接入时延及传输功耗，已成为下一代星地通信关键技术之一。然而，一方面卫星覆盖范围大，天基物联网免调度接入系统需处理海量物联设备随机发送的数据，对上行信号检测提出了严峻挑战。另一方面由于基于免授权的天基物联网系统缺少随机访问阶段的上行同步过程，上行信号在各时隙进行异步传输，异步信号检测面临困难。为此，本课题开展了低轨卫星信号重构及低复杂度检测研究，形成了免授权接入时延仿真、星历准确时信号重构及低复杂度检测及面向异步的信号重构及低复杂度检测等3个小数据集：1.产生约10万个泊松分布的用户模拟地面用户，用户分别采用免授权和传统授权接入方式接入系统，计算用户分别采用上述2中接入方式的平均接入时延以及接入时延的比值。2.在随机产生用户信道状态信息、不同信噪比条件下对所提信号检测方案与所提LC-EA-EP算法、基准算法1-OLS算法、基准算法2-SSMP算法、基准算法3-CoSaMP算法进行仿真，给出了不同信噪比下各压缩感知算法的系统误码率性数据和计算复杂度数据。3.针对星历及位置信息不准确情况，在随机产生用户信道状态信息、不同信噪比条件下对所提信号检测方案与基准算法1-OAMP算法、基准算法2-MAMP算法、基准算法3-OLS算法进行仿真，给出了不同信噪比下各压缩感知算法的系统误码率性数据和计算复杂度数据。上述三个小数据集于2024年12月在北京市石景山区静洋大厦520生成。This dataset is the experimental data for the research on compressed sensing-based signal reconstruction and low-complexity detection. Due to the large satellite-to-earth distance and long propagation delay, traditional licensed-based access schemes struggle to meet the low-latency application requirements of space-based IoT. Grant-free random access abandons the cumbersome signaling interaction in traditional licensed access schemes, effectively reducing signaling overhead, access latency and transmission power consumption, and has become one of the key technologies for next-generation satellite-terrestrial communications. However, on one hand, the wide coverage of satellites requires space-based IoT grant-free access systems to process massive random data transmitted by IoT devices, posing severe challenges to uplink signal detection. On the other hand, grant-free space-based IoT systems lack the uplink synchronization process in the random access phase, leading to asynchronous transmission of uplink signals in each time slot, which brings difficulties to asynchronous signal detection. To address these issues, this study conducts research on low-orbit satellite signal reconstruction and low-complexity detection, and forms three sub-datasets: 1. Generate approximately 100,000 Poisson-distributed simulated ground users. The users access the system using grant-free and traditional licensed access methods respectively, and calculate the average access latency and the ratio of access latencies for the two access modes. 2. Under randomly generated user channel state information and different signal-to-noise ratio (SNR) conditions, simulate the proposed signal detection scheme along with the proposed LC-EA-EP algorithm, benchmark algorithm 1 (OLS algorithm), benchmark algorithm 2 (SSMP algorithm) and benchmark algorithm 3 (CoSaMP algorithm), and provide the system bit error rate (BER) performance data and computational complexity data of each compressed sensing algorithm under different SNRs. 3. For scenarios with inaccurate ephemeris and position information, under randomly generated user channel state information and different SNR conditions, simulate the proposed signal detection scheme along with benchmark algorithm 1 (OAMP algorithm), benchmark algorithm 2 (MAMP algorithm) and benchmark algorithm 3 (OLS algorithm), and provide the system bit error rate (BER) performance data and computational complexity data of each compressed sensing algorithm under different SNRs. The above three sub-datasets were generated in Room 520, Jingyang Building, Shijingshan District, Beijing, in December 2024.

搜集汇总

背景与挑战

背景概述

该数据集为低轨卫星通信中信号重构及低复杂度检测研究的实验数据，旨在支持免授权随机接入技术以降低时延和功耗。它包含三个小数据集，分别模拟接入时延对比、不同信噪比下的算法性能仿真以及星历信息不准确时的检测效果，涉及压缩感知算法和误码率分析。数据集由中国电子科技集团公司电子科学研究院生成，适用于电子与通信技术领域的研究。