Multiple Access Techniques for Intelligent and Multi-Functional 6G: Tutorial, Survey, and Outlook

January 02, 2024 Β· Declared Dead Β· πŸ› Proceedings of the IEEE

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Authors Bruno Clerckx, Yijie Mao, Zhaohui Yang, Mingzhe Chen, Ahmed Alkhateeb, Liang Liu, Min Qiu, Jinhong Yuan, Vincent W. S. Wong, Juan Montojo arXiv ID 2401.01433 Category cs.IT: Information Theory Cross-listed eess.SP Citations 95 Venue Proceedings of the IEEE Last Checked 4 months ago
Abstract
Multiple access (MA) is a crucial part of any wireless system and refers to techniques that make use of the resource dimensions to serve multiple users/devices/machines/services, ideally in the most efficient way. Given the needs of multi-functional wireless networks for integrated communications, sensing, localization, computing, coupled with the surge of machine learning / artificial intelligence (AI) in wireless networks, MA techniques are expected to experience a paradigm shift in 6G and beyond. In this paper, we provide a tutorial, survey and outlook of past, emerging and future MA techniques and pay a particular attention to how wireless network intelligence and multi-functionality will lead to a re-thinking of those techniques. The paper starts with an overview of orthogonal, physical layer multicasting, space domain, power domain, ratesplitting, code domain MAs, and other domains, and highlight the importance of researching universal multiple access to shrink instead of grow the knowledge tree of MA schemes by providing a unified understanding of MA schemes across all resource dimensions. It then jumps into rethinking MA schemes in the era of wireless network intelligence, covering AI for MA such as AI-empowered resource allocation, optimization, channel estimation, receiver designs, user behavior predictions, and MA for AI such as federated learning/edge intelligence and over the air computation. We then discuss MA for network multi-functionality and the interplay between MA and integrated sensing, localization, and communications. We finish with studying MA for emerging intelligent applications before presenting a roadmap toward 6G standardization. We also point out numerous directions that are promising for future research.
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