5G mobile communication is based on three main pillars: enhanced mobile broadband, massive machine-type communication, and ultra-reliable low latency. For a mobile station (MS) to connect to a 5G network and access user data, it must first perform cell identification during the initial stage before establishing radio and network connections. This is done using the primary synchronization signal (PSS) and secondary synchronization signal (SSS) sent out by the 5G base station (gNB). Because of movement, the Doppler effect, and battery limits on the MS, detecting PSS and SSS needs to be both strong and efficient. The parameters estimated in this process include timing, carrier frequency offset, cell ID, and numerology. This paper looks at a cell identification technique that works well for an MS, introduces a low-complexity PSS detection technique designed to balance detection performance with computational efficiency. The proposed method reduces the number of complex multiplications required, making it suitable for low signal-to-noise ratio (SNR) environments while maintaining adequate detection accuracy. The methodology includes detailed system modeling to simulate the signal and noise conditions typical of 5G NR systems. The results indicate that this low-complexity PSS detection method is well-suited for practical use in 5G NR mobile stations, providing an efficient solution that aligns with the performance and resource constraints of modern mobile communication systems. The performance of this technique is tested through simulations, showing that PSS can be correctly detected at a signal-to-noise ratio (SNR) of -6 dB, meeting the performance needs. Additionally, complexity can be reduced by sacrificing some detection capability of the PSS