How the field of 6G Communication is developing part1(Artificial Intelligence + Telecommunication)
- Towards Blockchain-based Trust and Reputation Management for Trustworthy 6G Networks(arXiv)
Author : Guntur Dharma Putra, Volkan Dedeoglu, Salil S Kanhere, Raja Jurdak
Abstract : 6G is envisioned to enable futuristic technologies, which exhibit more complexities than the previous generations, as it aims to bring connectivity to a large number of devices, many of which may not be trustworthy. Proper authentication can protect the network from unauthorized adversaries. However, it cannot guarantee in situ reliability and trustworthiness of authorized network nodes, as they can be compromised post-authentication and impede the reliability and resilience of the network. Trust and Reputation Management (TRM) is an effective approach to continuously evaluate the trustworthiness of each participant by collecting and processing evidence of their interactions with other nodes and the infrastructure. In this article, we argue that blockchain-based TRM is critical to build trustworthy 6G networks, where blockchain acts as a decentralized platform for collaboratively managing and processing interaction evidence with the end goal of quantifying trust. We present a case study of resource management in 6G networks, where blockchain-based TRM quantifies and maintains reputation scores by evaluating fulfillment of resource owner’s obligations and facilitating resource consumers to provide feedback. We also discuss inherent challenges and future directions for the development of blockchain-based TRM for next-generation 6G networks
2. On-Demand Resource Management for 6G Wireless Networks Using Knowledge-Assisted Dynamic Neural Networks(arXiv)
Author : Longfei Ma, Nan Cheng, Xiucheng Wang, Ruijin Sun, Ning Lu
Abstract : On-demand service provisioning is a critical yet challenging issue in 6G wireless communication networks, since emerging services have significantly diverse requirements and the network resources become increasingly heterogeneous and dynamic. In this paper, we study the on-demand wireless resource orchestration problem with the focus on the computing delay in orchestration decision-making process. Specifically, we take the decision-making delay into the optimization problem. Then, a dynamic neural network (DyNN)-based method is proposed, where the model complexity can be adjusted according to the service requirements. We further build a knowledge base representing the relationship among the service requirements, available computing resources, and the resource allocation performance. By exploiting the knowledge, the width of DyNN can be selected in a timely manner, further improving the performance of orchestration. Simulation results show that the proposed scheme significantly outperforms the traditional static neural network, and also shows sufficient flexibility in on-demand service provisioning
3. Exploration and Application of AI in 6G Field(arXiv)
Author : Renhao Xue, Jialei Tan, Yutao Shi
Abstract : The recent upsurge of diversified mobile applications, especially those supported by AI, is spurring heated discussions on the future evolution of wireless communications. While 5G is being deployed around the world, efforts from industry and academia have started to look beyond 5G and conceptualize 6G. We envision 6G to experience an unprecedented transformation that will make it completely different from the previous generations of wireless systems. In particular, 6G will go beyond mobile Internet and will be required to support AI services. Meanwhile, AI will play a critical role in designing and optimizing 6G architectures, protocols and operations. In this article, we discuss the features of 6G, and the difficulties of carrying out 6G, and AI-enabled methods for 6G network design and optimization.
