The research in the sixth generation of communication networks needs to tackle new challenges in order to meet the requirements of emerging applications in terms of high data rate, low latency, high reliability, and massive connectivity. To this end, the entire communication chain needs to be optimized, including the channel and the surrounding environment, as it is no longer sufficient to control the transmitter and/or the receiver only. Investigating large intelligent surfaces, ultra massive multiple-input multiple-output, and smart constructive environments will contribute to this direction. In addition, to allow the exchange of high dimensional sensing data between connected intelligent devices, semantic and goal oriented communications need to be considered for a more efficient and context-aware information encoding. In particular, for multi-agent systems, where agents are collaborating together to achieve a complex task, emergent communications, instead of hard coded communications, can be learned for more efficient task execution and communication resources use. Moreover, new physics phenomenon should be exploited such as the thermodynamics of communication as well as the the interaction between information theory and electromagnetism to better understand the physical limitations of different technologies, e.g, holographic communications. Another new communication paradigm is to consider the end-to-end approach instead of block-by-block optimization, which requires exploiting machine learning theory, non-linear signal processing theory, and non-coherent communications theory. Within this context, we identify twelve scientific challenges for rebuilding the theoretical foundations of communications, and we overview each of the challenges while providing research opportunities and open questions for the research community.
翻译:第六代通信网络的研究需要应对新的挑战,以便满足在高数据率、低潜度、高可靠性和大规模连通性方面新兴应用的要求。为此,需要优化整个通信链,包括频道和周围环境,因为已不再足以控制发射机和/或接收机。调查大型智能表面、超大型多投入多产出和智能建设性环境将有助于这一方向。此外,需要考虑在连通智能设备、语义和面向目标的通信之间交换高维感测数据,以提高效率和对背景有认识的信息编码。特别是,对于多代理系统,包括频道和周围环境,整个通信链需要优化,因为这已经不足以控制发射机和/或接收机接收器。调查大型智能表面、超大型多投入多产出和智能建设性环境将有助于这一方向。此外,应当利用新的物理现象,例如通信的热力以及信息理论与电磁学之间的相互作用,以便更好地了解不同技术的物理局限性,例如,理论、血液学和以环境为导向的通信的理论基础,同时,需要我们进行理论的理论性理论的理论的再研究。