频域均衡全双工无线电的设计与测试平台部署
Design and Testbed Deployment of Frequency-Domain Equalization Full Duplex Radios
AI总结：
本文设计了基于频域均衡的射频自干扰消除全双工无线电，在两个测试平台上验证其性能，实现95dB总自干扰消除与1.87倍链路速率增益，并验证了上下行及异构网络下的增益规律，同时提供了可用测试设施与数据集。
摘要：
全双工（FD）无线通信可显著提升频谱效率，但需要有效的自干扰（SI）消除器。通过频域均衡（FDE）实现的射频（RF）自干扰消除（SIC）采用带通滤波器对自干扰进行信道化，适用于集成电路（IC）。本文探究了使用此类消除器的性能极限与更高层挑战。我们利用两个测试平台评估了一款定制化基于FDE的消除器的性能：一个搭载移动全双工无线电，另一个是在PAWR COSMOS测试平台中升级后的静态全双工无线电。后者是面向研究社区的长期可用设施，同时我们还发布了在COSMOS全双工无线电上采集的基带波形数据集，为更高网络层的全双工相关实验提供支持。我们在两个测试平台中评估了基于FDE的全双工无线电性能，实验显示在20MHz带宽下，整体自干扰消除量达到95dB（其中射频自干扰消除贡献52dB），链路级全双工平均速率增益为1.87倍。我们还在两类场景中开展实验：（i）存在用户间干扰的上下行网络；（ii）包含半双工与全双工用户的异构网络。两类网络中的实验全双工增益取决于用户的SNR值与全双工用户数量，分别为1.14倍-1.25倍和1.25倍-1.73倍，验证了此前的分析结果。
英文摘要：
Full-duplex (FD) wireless can significantly enhance spectrum efficiency but requires effective self-interference (SI) cancellers. RF SI cancellation (SIC) via frequency-domain equalization (FDE), where bandpass filters channelize the SI, is suited for integrated circuits (ICs). In this paper, we explore the limits and higher layer challenges associated with using such cancellers. We evaluate the performance of a custom FDE-based canceller using two testbeds; one with mobile FD radios and the other with upgraded, static FD radios in the PAWR COSMOS testbed. The latter is a lasting artifact for the research community, alongside a dataset containing baseband waveforms captured on the COSMOS FD radios, facilitating FD-related experimentation at the higher networking layers. We evaluate the performance of the FDE-based FD radios in both testbeds, with experiments showing 95 dB overall achieved SIC (52 dB from RF SIC) across 20 MHz bandwidth, and an average link-level FD rate gain of 1.87x. We also conduct experiments in (i) uplink-downlink networks with inter-user interference, and (ii) heterogeneous networks with half-duplex and FD users. The experimental FD gains in the two types of networks depend on the users' SNR values and the number of FD users, and are 1.14x-1.25x and 1.25x-1.73x, respectively, confirming previous analytical results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
