Application of Edge Computing in Multi-Access Communication

# 1. Introduction to Edge Computing and Multi-access Communication

## 1.1 Fundamental Concepts and Principles of Edge Computing

Edge computing is a computational model that pushes computing power and data storage closer to the source of data generation or the consumer. Its basic principle involves deploying more computing devices at the network edge, allocating computational tasks to be processed on edge devices, thereby reducing data transmission delays, alleviating network load pressure, and increasing system response speed.

The concept of edge computing was first proposed by Cisco Systems in 2012, aiming to address issues of data transmission delays and bandwidth limitations inherent in the cloud computing model. Edge computing utilizes edge nodes that are closer to the data source to offer faster responses and higher bandwidth, allowing applications with high real-time requirements to operate better.

The fundamental principles of edge computing can be summarized as follows:
- Transfer some computational tasks from the central cloud to the edge devices for processing;
- Run lightweight applications on edge nodes to provide real-time computing and response services;
- Utilize storage resources on edge nodes to provide offline data processing and caching services;
- Coordinate and manage edge nodes with the cloud through network connections.

## 1.2 Basic Principles and Development History of Multi-access Communication

Multi-access communication is a communication technology that transmits multiple signals simultaneously on the same channel. Its basic principle involves using multiple independent coding methods to separate multiple signals, allowing them to be transmitted through the same channel during the same time period, thereby improving channel utilization and transmission efficiency.

The development history of multi-access communication can be traced back to the 1960s. The earliest multi-access communication technologies were based on Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA). Later, with the development of CDMA (Code Division Multiple Access) technology, multi-access communication entered a new phase.

CDMA technology relies on unique coding sequences representing different users, allowing signals from different users to overlap in the frequency domain and share the same channel in the time domain. It has strong resistance to interference and flexible resource allocation methods, becoming the main multi-access technology in 3G and 4G communication systems.

## 1.3 Correlation Between Edge Computing and Multi-access Communication

Edge computing and multi-access communication are closely related. First, edge computing can provide more efficient resource utilization and response capabilities to the multi-access communication system by processing, computing, and storing data on edge nodes.

Second, edge computing can reduce data transmission delays and improve the real-time performance of the multi-access communication system. By processing data and computing tasks on edge nodes, the need to transmit large amounts of data to the central cloud for processing is avoided, thereby reducing transmission delays and network load.

Furthermore, edge computing can provide a more flexible resource allocation and network management method for the multi-access communication system. By allocating resources and scheduling tasks on edge nodes, system resources can be utilized more effectively, increasing system capacity and coverage.

In summary, the combination of edge computing and multi-access communication can achieve advantages in resource optimization, delay reduction, and system performance enhancement, which is significant for the development of future communication networks.

# 2. Advantages of Edge Computing in Multi-access Communication

Edge computing and multi-access communication, as two key technological domains, have a close correlation. Edge computing, as a form of distributed computing, brings computing resources and data storage closer to the source of data generation, aiming to provide low-latency and fast-response computing services. Multi-access communication technology, on the other hand, is a method of communication capable of transmitting multiple users simultaneously and is widely used in wireless communication systems.

This chapter will focus on the advantages of edge computing in multi-access communication and its applications, specifically including the optimization of multi-access communication performance by edge computing, its value in reducing communication delays and improving data processing efficiency, as well as the significance of energy consumption optimization in multi-access communication.

### 2.1 The Role of Edge Computing in Optimizing Multi-access Communication Performance
Edge computing can leverage the characteristics of distributed computing, transferring computational tasks from central data centers to edge devices for processing. This approach can alleviate the load on central data centers while also reducing communication delays caused by network latency. For multi-access communication systems, edge computing technology can distribute computational tasks to edge servers closer to users, achieving lower transmission latency and faster response times.

### 2.2 The Value of Edge Computing in Reducing Communication Delays and Improving Data Processing Efficiency
In multi-access communication systems, communication delay is a significant performance indicator. Edge computing can greatly reduce the distance and time required for data transmission by distributing computational tasks to edge devices, thereby lowering communication delays. At the same time, edge computing can provide more efficient data processing capabilities, allowing multi-access communication systems to process large amounts of communication data more quickly and accurately.

### 2.3 The Significance of Edge Computing in Energy Consumption Optimization for Multi-access Communication
Edge computing can transfer computational tasks from central data centers to edge devices for processing, reducing the distance data must travel and the number of network transmissions, thus lowering energy consumption. In multi-access communication systems, the significance of energy consumption optimization through edge computing is particularly evident, especially for mobile devices. By utilizing edge computing technology, some computational tasks can be shifted from mobile devices to edge servers closer to users for processing, reducing the energy consumption of mobile devices.

In summary, edge computing has numerous advantages in mul