High-Precision 5G-NR Downlink Signal Detection Sensor Developed Using Software-Defined Radio

As the amount of required mobile data traffic continues to grow, spectrum resources for 5G will become insufficient. Therefore, 5G systems using dynamic spectrum sharing (DSS) are attracting attention to expand the available spectrum resources. In DSS, frequency bands already allocated to other systems (primary users) are used by secondary users under conditions that do not interfere with the primary users. To protect primary users, a spectrum management database is mainly used. However, assuming that the primary user is mobile, the primary user system can be stably protected by combining the database-dependent method with radio sensing technology that can detect the 5G signal of the secondary user with high accuracy. In this paper, a high-precision 5G downlink signal detection method is proposed. In addition, the proposed method is implemented into software-defined radio as a radio sensor. The performance of the developed radio sensor is experimentally evaluated and validated by comparing with computer simulation results. In the additive white Gaussian noise (AWGN) environment and a multipath fading environment defined by the third-generation partnership project (3GPP), detection rates of 99% and 90% were achieved at a target signal-to-noise power ratio (SNR) of -10 dB, respectively.