# Design and Performance Analysis of Hardware Realization of 3 GPP Physical Layer for 5G Cell Search
## 1 Introduction  
In a cellular network, user equipment (UE) performs initial access (IA) to establish communication with the base station (BS) every time it is powered ON [1, 2, 3, 4, 5, 6]. The IA comprises the downlink and uplink synchronizations. The downlink synchronization involves the cell search (CS), and acquisition of minimum system information (MSI) at the UE [7, 8, 9, 2]. The first step, CS, allows the UE to obtain cell identity and synchronize with the BS in terms of symbol, slot, subframe, and frame timings [7, 8, 9]. After the CS, MSI acquisition provides information such as access type (barred, restricted, or unrestricted), carrier frequency and bandwidth, cell selection information (minimum receiver level), scheduling information, downlink/uplink configurations, etc. [2, 10, 11, 12]. The uplink synchronization, via physical random access channel (PRACH), allows the base station to locate and instruct the UE to fine-tune the uplink timings such that uplink transmissions from multiple UEs are aligned in time irrespective of their distances from base-station [10, 13, 14]. In [15], CS is moved from UE to BS via code-book-based approach. However, this approach is not compatible with existing 3 GPP standards. The CS is the first and foremost step of the 5G IA and the focus of the work presented in this paper. It is accomplished via synchronization signals (SS) broadcasted by 5G node B (gNB). 5G 3 rd generation partnership project (3 GPP) specifications offer a detailed discussion on the SS generation at gNB, but limited understanding about their blind search and detection at UE is available [7, 8, 9, 10, 16, 17, 18]. Historically, it is left to be designed by equipment manufacturers. The CS in 5G substantially evolved from 4G Long Term Evolution (LTE) [19, 20, 21, 22, 23]. The significant difference is the location of SS in the frequency domain. In 4G LTE, the SSis transmitted over the subcarriers in the middle of the carrier [19]. In 5G, the location is not fixed and is unknown, which means the UE needs to blindly search the SS over the entire carrier bandwidth [10]. To simplify the blind search, 3 GPP introduced Global Synchronization Channel Number (GSCN) in 5G, which pre-defines possible positions where gNB can transmit SS. The SS bandwidth and overall transmission bandwidth in 5G are significantly wider; hence, SS detection requires multiple large-size correlators [4]. This makes the blind search computationally complex and time-consuming. Deep learning for CS may not be suitable for low latency applications [24]. Other blocks of the CS physical layer (PHY), including message generators, channel encoders, data modulators, scramblers, interleaves, and their counterparts in the receivers, are redesigned in 5G [25, 26]. Thus, efficient design of 5G CS and in-depth performance analysis are essential to understand computational complexity and identify the limitations for future standard releases. The work presented in this paper aims to innovate algorithms and architecture for accurate and reliable 5G CS. The proposed 5G CS PHY is based on the Release 16 of the 3 GPP standards [16, 17, 18]. The main contributions of the paper are summarized as follows:  
1. We develop and integrate various building blocks of the 5G CS PHY of the gNB transmitter and UE receiver for realization on hardware. Along with the conventional baseband PHY operations, we design the gNB scheduler to broadcast the SS signals as per the 3 GPP specifications. 2. We demonstrate the design and FPGA implementation of signal processing blocks such as primary SS (PSS) and secondary SS (SSS) detection, demodulation reference signal (DMRS) detection, and cell identity (CI) estimation at UE as per 3 GPP standard. Multiple instances of the detected PSS, SSS, and DMRS signals are used to detect the frame, sub-frame, and symbol boundaries in the received signal. 3.