Exploring 6G Wireless Communication: Application Technologies, Challenges and Future Direction

Abstract

The data traffic has increased significantly along with the quick development of smart wireless technologies, and current 5G networks are still not completely prepared to handle future huge data traffic in the areas of services, data transfer, data storage, and processing. 6G is expected to offer very high-level extended 5G capabilities, such as a Tbps data transfer rate and a sub-millisecond response time. The main objective of this study is to be aware of new technologies being enhanced day by day and provide existing research content, issues, and directions for the future regarding 6G wireless networks. Therefore, a systematic literature review of research articles is provided by categorizing the selected studies published between 2019 and 2022 in terms of enabling technologies. First, the researcher discussed the need for 6G by predicting the explosive growth of mobile traffic from 2022 to 2030. Second, 6G requirements, trends, and services are addressed and contrasted with 5G in terms of a group of key performance indicators. Third, conduct a comparative analysis of 6G challenges and gaps, such as security and privacy, the need for a decentralized network, Omnipresent service coverage, and storage efficiency. So, it is essential to develop an accurate, faster, and well-organized system for the 6G wireless network. We have presented an efficient and secure mode R6GS, which combines blockchain and 6G to improve security from the lower to upper layers while also improving storage efficiency. Cybertwin technologies are used at the edge layer of the 6G network in the proposed model R6GS to improve security. The smart contracts, IPFS and Ethereum blockchain are used in the proposed R6GS model to enhance the 6G network's data integrity and data storage. It also processes and stores massive amounts of data at various network layers, which removes the large storage capacity issue of traditional P2P and Client/Server (C/S) networks due to centralized servers in 6G technology. For the performance evaluation, the model is evaluated through expert opinion. Moreover, the proposed R6GS model also improves time efficiency through the edge layer, because if a task is available at the edge layer, there is no need to send a request to the core layer. The server at the edge layer efficiently delivers data to end nodes. Furthermore, a taxonomy is presented in this study. To the best of our knowledge, the proposed methodology worked efficiently.