Dataset for FFT of IQ samples: LTE, NR, and Overlap

Dynamic Spectrum Sharing (DSS) is an enabler for a seamless transition from 4G Long TermEvolution (LTE) to 5G New Radio (NR) by utilizing existing LTE bands without static spectrum re-farming. In this paper, we propose a cross-band DSS scheme that utilizes the Multimedia BroadcastMulticast Service over a Single Frequency Network (MBSFN) feature of an LTE network and theMulticast Broadcast Service (MBS) feature of an NR network. The proposed DSS scheme utilizes LTEand NR resource controllers to assign muted MBSFN subframes on the LTE band and muted MBSsubframes on the NR band based on traffic needs. In contrast to the state-of-the-art, the proposed DSSscheme does not require a coordination signaling channel between the LTE and NR networks. Instead, amachine learning-based Technology Recognition and Traffic Characterization (TRTC) system is used toidentify and characterize traffic patterns. The LTE and NR resource controllers use the TRTC to sensethe muted subframes and offload traffic accordingly. On average, the proposed DSS, as compared tostatic band configuration, improves the LTE throughput, NR throughput, LTE band spectrum utilizationefficiency, and NR band spectrum utilization efficiency by 13.5%, 8.3%, 11.8%, and 20.7%, respectively.

动态频谱共享（DSS）作为一种推动从4G长期演进（LTE）技术平稳过渡至5G新无线（NR）技术的关键技术，其通过利用现有的LTE频段而无需静态频谱重耕来实现。在本研究中，我们提出了一种跨频段DSS方案，该方案利用了LTE网络的多媒体广播单频网（MBSFN）功能和NR网络的组播广播服务（MBS）功能。所提出的DSS方案运用LTE和NR资源控制器，根据流量需求在LTE频段上分配静默的MBSFN子帧和在NR频段上分配静默的MBS子帧。与现有技术相比，该DSS方案无需在LTE和NR网络之间建立协调信令信道。相反，采用基于机器学习的科技识别与流量特征分析（TRTC）系统来识别和描述流量模式。LTE和NR资源控制器利用TRTC感知静默子帧并相应地卸载流量。相较于静态频段配置，所提出的DSS方案平均提升了LTE吞吐量、NR吞吐量、LTE频段频谱利用率以及NR频段频谱利用率，分别达到13.5%、8.3%、11.8%和20.7%。