# A Review of PCI Express Protocol-Based Systems in Response to 5G Application Demand
## 1 Introduction  
In 2019, AI and AI-related innovation, fifth-generation mobile networks (5G), cloud computing, and the IoT became important to the market. In 2022, [PERSON](tm) introduced the productivity revolution with AI [1]. PCIe 5.0 is over 10% based on the PCIe 4.0 market [2]. Market demand strategies can be developed with the T-plan analysis method [3]. This analysis process tracks market demand, products, technologies, and strategies for products.  
Market demand can be calculated based on data pertaining to 5G applications from the 3 rd Generation Partnership Project (3 GPP). Using 5G applications created with network slice layers, a PC system can focus on AI, IoT, high-performance computing, and cloud storage for security products. 5G applications are in demand for edge service in physical and virtual resources. In this study, we used the serial bus as the basic design model and reviewed the system topology. To evaluate application demand, we assessed suitable technologies and developed market-appropriate solutions. We used the PCI Express system for the processor, memory, storage, and USB devices for network slice services. We reviewedperformance and power efficiency. Following the released PCI Express roadmap, product designs should be ready in around three years for each generation. Considering USB, PCI Express, CXL, and security risks, it will also take around three years to produce these product changes.  
In this survey, we referenced system-related specifications and release schedules, and reviewed the products introduced to the market. Our methodology involved reviewing enhancements and features in USB, PCI Express, NVMe, and CXL. Based on these serial bus solutions and 5G application slices, we attempted to understand the need for AI, IoT, cloud computing, and storage.  
Security algorithms were suggested for quantum computers to highlight some of the changes needed to provide more secure systems, and have been part of market demand since 2016 [4]. Systems and devices using 5G applications require more secure products than those previously in use. Intel(tm) and Microsoft(tm) must commence security review processes and provide secure updates and solutions. The specifications of USB, PCIe, and NVMe also include more secure solutions during protocol transition with PCI Express. Products with secure hardware and software have been introduced to the market, while market demand for 5G secure cloud and 5G network usage has increased.  
For the PC industry, Intel(tm), AMD(tm), and NVIDIA(tm) are the three major solution providers. The roadmaps for AI and deep learning produced by these three companies provide valuable product strategies. We reviewed these solutions for hardware and software in different product lines, including CPU- and GPU-based systems designed for application slicing in physical and virtual devices. As a result, devices with low power and low data throughput are designed for IoT, while devices with high power and high data throughput are designed for AI and deep learning. USB PDs provide appropriate power design for products as demanded. Cloud services are based on data throughput, storage, and performance. Deep learning uses CPU and GPU solutions for performance, as demanded.  
Secure devices such as TPM can be combined with systems that protect data while moving it from the field to backup services. Risks in different network slicing layers in virtual and physical resources require more silicon and hardware security solutions.