Exploring blockchain and artificial intelligence for next generation wireless networks

Future wireless communication networks are exploring the 0.1 to 10 terahertz (THz) band, which presents opportunities for creative usage. However, the management of growing privacy and security issues while allocating resources efficiently to support many devices is a critical activity. Complicated technology affects resource allocation (RA) and network management as it permeates devices and infrastructure. Upgrading from fifth-generation (5G) to next-generation represents breakthroughs in ultra-low latency, fast data speeds, and artificial intelligence (AI) integration for innovative services and applications. However, these developments convey the challenges that include data processing, RA, network administration, and privacy. Integrating blockchain (BC) as well as machine learning (ML) is a potential alternative to tackle these challenges. This paper presents a comprehensive review, which explores their combined contributions to trust, decentralization, and network security in ML decisions, immutability, and streamlined model sharing. Moreover, it delves into various areas such as rate splitting, next-generation radaroriented communication, BC-oriented spectrum reframing, reconfigurable intelligent surfaces (RIS), and integrated sensing and communication. In addition, it investigates using ML and BC in emerging next-generation communication technologies, which include semantic, molecular, and holographic communications. Finally, the authors deal with the essential unsolved issues, challenges, prospective solutions, and the wide range of opportunities for additional research in this rapidly evolving fields.

Authors

Institutions

Publication Details

Journal
Journal of Communications and Networks
Published
2025-08-26
DOI
https://doi.org/10.23919/jcn.2025.000008
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring blockchain and artificial intelligence for next generation wireless networks

Vuppula Roopa, Himansu Shekhar Pradhan
1 citations
Journal of Communications and Networks
Brain Tumor Detection and Classification
0.84
article

Exploring blockchain and artificial intelligence for next generation wireless networks

Vuppula Roopa, Himansu Shekhar Pradhan
article en
1 citations

Abstract

Future wireless communication networks are exploring the 0.1 to 10 terahertz (THz) band, which presents opportunities for creative usage. However, the management of growing privacy and security issues while allocating resources efficiently to support many devices is a critical activity. Complicated technology affects resource allocation (RA) and network management as it permeates devices and infrastructure. Upgrading from fifth-generation (5G) to next-generation represents breakthroughs in ultra-low latency, fast data speeds, and artificial intelligence (AI) integration for innovative services and applications. However, these developments convey the challenges that include data processing, RA, network administration, and privacy. Integrating blockchain (BC) as well as machine learning (ML) is a potential alternative to tackle these challenges. This paper presents a comprehensive review, which explores their combined contributions to trust, decentralization, and network security in ML decisions, immutability, and streamlined model sharing. Moreover, it delves into various areas such as rate splitting, next-generation radaroriented communication, BC-oriented spectrum reframing, reconfigurable intelligent surfaces (RIS), and integrated sensing and communication. In addition, it investigates using ML and BC in emerging next-generation communication technologies, which include semantic, molecular, and holographic communications. Finally, the authors deal with the essential unsolved issues, challenges, prospective solutions, and the wide range of opportunities for additional research in this rapidly evolving fields.

Journal of Communications and NetworksVol. 27(5)
National Institute of Technology Warangal (IN)
Openalex Percentile: Top 22%
Brain Tumor Detection and Classification
0.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.