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) and machine learning (ML) is a impending approach 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 radar-oriented 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 field.
Index terms : Artificial Intelligence, Wireless Networks, Machine Learning, Blockchain