Next-Generation Wireless Networks
- [Stanford University]
- Overview
Next-generation wireless networks are the development and implementation of wireless communication technologies and their infrastructure. They use different frequencies and bandwidths across the electromagnetic spectrum to connect people and things.
Next-generation wireless networks (NGWN) include:
- Spectrum management
- Co-existence of multiple radio access technologies
- Artificial intelligence (AI) for Internet of Things (IoT)
- Vehicular networks and smart cities
- Audio/video communication
- Big data analytics
The idea behind the next-generation network (NGN) is that one network transports all information and services by encapsulating these into IP packets, similar to those used on the Internet.
Some examples of next-generation wireless networks (NGWNs) include:
- 5G: The next generation of wireless cellular technology, 5G has higher download speeds, higher bandwidth, and can connect more devices. 5G networks have a peak speed of 10 gigabits per second (Gbit/s) when there is only one user in the network. 5G gained widespread availability in 2020.
- 6G: The sixth-generation mobile network standard, 6G is under development and expected to come out around 2030. 6G networks will be able to use higher frequencies than 5G networks and provide substantially higher capacity and much lower latency.
- Millimeter-Wave (mmWave): A core wireless technology that enables new applications in areas such as smart transportation and telemedicine. In 2019, the Federal Communications Commission approved the commercial use of mmWave frequencies exceeding 100 gigahertz (GHz).
- NGWN Technologies
The integration of communications with different scales, diverse radio access technologies, and various network resources renders next-generation wireless networks (NGWN) highly heterogeneous and dynamic.
Emerging use cases and applications, such as machine to machine communications, autonomous driving, and factory automation, have stringent requirements in terms of reliability, latency, throughput, and so on. Such requirements pose new challenges to architecture design, network management, and resource orchestration in NGWN.
Next-generation wireless networks (NGWN) such as 5G and beyond are expected to be extremely complex and dynamic. The emergence of ultra-dense deployments of heterogeneous networks, high data rates, and new applications requiring new radio technology paradigms may create a number of critical challenges for network management, operations, planning, and troubleshooting.
At the same time, the generation and consumption of wireless data has gradually shifted from human-centered communication to machine-centered communication, making future wireless network operations more complex. Therefore, to alleviate the complexity of future wireless network operations, new approaches using distributed computing with better context awareness will become increasingly important.
Therefore, it is necessary to observe how artificial intelligence (AI) technologies such as deep learning (DL) and artificial neural networks (ANN) are being dynamically studied to solve numerous challenges in the Internet of Things (IoT). Machine learning (ML) is one of the most promising AI tools designed to support smart radio terminals.
NGWNs must be able to support low-latency communications, provide ultra-reliability, and cognitively manage Internet of Things (IoT) devices in real-time, dynamic environments.
This communication requirement and mobile edge and core intelligence can only be achieved by integrating fundamental concepts of AI and ML across wireless infrastructure and end-user devices for a variety of applications such as real-time traffic data, Autonomous driving sensor data cars or Netflix entertainment recommendations.
All of these applications generate large amounts of data that must be assembled and processed on the fly.
- NGWN: Highly Heterogeneous and Dynamic Networks
Next-generation wireless networks (NGWN) are expected to be complex and dynamic. NGWN networks are expected to be heterogeneous, meaning they will integrate different radio access technologies (RATs). These RATs can include 3GPP's LTE and WLAN.
The network architecture will be highly heterogeneous due to the integration of terrestrial networks, satellite networks, and aerial networks. The network environment will become highly dynamic because of the mobility of MUTs.
Heterogeneous networks are networks where the devices are made by different manufacturers, or the computers run different operating systems. Two common examples of heterogeneous networks are the Internet, and the cell phone networks.
Heterogeneous networks enable flexible and low-cost deployments and provide a uniform broadband experience to users anywhere in the network.
- The Research Topics of NGWN
Potential topics include but are not limited to the following:
- Next-Generation Wireless Networks (NGWN) using evolutionary computing and fuzzy systems
- Wireless communications and networking with Unmanned Aerial Vehicles
- Wireless virtual reality
- Mobile edge caching and computing
- Spectrum management and co-existence of multiple radio access technologies
- Artificial intelligence for Internet of Things
- Vehicular networks and smart cities
- Audio/video communication in NGWN
- Big data analytics for NGWN
- Intelligent communication for NGWN
- Distributed computation, in-network processing, and data mining in NGWN
- Case studies or applications of dynamic networks using NGWN
- NDN/SDN edge computing
- Quantum computing
- Communication protocols for NGWN
- Fog/cloud computing in NGWN
[More to come ...]
