# A Fast Acquisition Algorithm for Hybrid Signals of 5G and BeiDou B1
## 1 Introduction  
BeiDou is a satellite navigation system developed by China, which has the functions of navigation and positioning, short message communication, and can provide high-precision positioning, timing, and speed measurement services, and has played an important role in rail transportation, industrial digitalization, and precision agriculture. The fifth-generation communication technology can provide higher speed, lower latency, and more reliable mobile communication services, significantly expanding mobile internet application scenarios. BeiDou navigation and 5G services are increasingly important in human society. However, the signal frequency of BeiDou navigation and positioning services is located in the L-band, which is very close to some frequency bands of FR1 of 5G. Due to the high power of 5G signals emitted by ground base stations and the low power of BeiDou signals on the ground, this leads to significant interference in the reception link of BeiDou signals. Therefore, the problem of compatible reception of BeiDou navigation and 5G signals has attracted more and more attention from the academic community. The following research focuses on the key issues affecting the performance of GNSS and 5G signals regarding positioning, timing, and accuracy on hybrid architectures and platforms. The following research focuses on GNSS and 5G signals in terms of hybrid positioning, compatibility, and interference detection. [PERSON] et al. present preliminary experimental results of hybrid positioning tests with 5G and GNSS and evaluate the achievable positioning performance of GNSS and 5G. The paper examines the possiblegains in complete performance by fusing real GNSS and simulated 5G observations. It shows the importance of GNSS and 5G fusion in harsh environments [1]. [PERSON] et al. propose that the technology of 5G communication-assisted GNSS can broadcast ephemeris and corrections from newly implemented IoT base stations to user terminals and also send secure positioning information from terminals to monitor network applications, improving the performance of IoT in terms of accuracy, continuity, and time to first fix (TTFF) [2]. [PERSON] et al. proposed a robust adaptive fading filter (RAF) algorithm based on predicted residuals and a joint Kalman filter (FKF) algorithm operating in fused feedback mode in the context of a 5G network environment based on device-to-device (D2D) and self-organizing network (SON) technologies to achieve robust, reliable, and continuous high-precision positioning services with anti-interference capability and good generality after integrating BDS and SON positioning data [3]. [PERSON] et al. investigated location-based TA estimation for 5G-integrated LEO satellite communication systems. The proposed method can approach the restricted Cramer-Rao lower bound (CRLB) for TA estimation, thus ensuring uplink frame alignment for different users [4]. [PERSON] et al. analyzed the mutual interference problem between the radio-determined satellite service (RDSS) of BeiDou and 5G signals due to the similar operating frequencies and derived the exact range of neighboring frequency effects to improve the electromagnetic protection of RDSS receivers [4]. [PERSON] et al. detected GPS spoofing attacks by GPS signals and 5G radio positioning signals and used 5G positioning instead of GPS positioning to avoid GPS spoofing attacks. The experimental results showed that the detection rate exceeded 98% [5]. [PERSON] et al. proposed an integrated GNSS/5G 3D localization scheme based on D2D communication, which improved the localization accuracy by about 58% over the GNSS localization results using time of arrival (TOA) and received signal strength (RSS) measurements in a 5G network using density space clustering with noise (DBSCAN) and particle filtering (PF) algorithms [6]. [PERSON] et al.