面向5G网络中D2D通信的分布式人工智能解决方案
Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks
AI总结：
针对5G网络中D2D通信的落地挑战，提出用带扩展能力的BDI智能体（BDIx）分布式自主管控D2D节点，通过兼顾计算负载的传输模式决策优化速率与功耗，仿真验证了方案的可行性。
摘要：
设备到设备（Device to Device, D2D）通信是演进中的5G架构的技术组成部分之一，它有望提升能源效率、频谱效率、系统整体容量并实现更高的数据速率。上述网络性能的提升推动了D2D领域的大量研究，这些研究也指出了若干重大挑战，要在新兴5G网络中充分发挥D2D的潜力，必须先解决这些挑战。为此，本文提出采用一种分布式智能方法来管控D2D网络的生成。更具体地说，所提方法使用具备扩展能力的信念-愿望-意图（Belief-Desire-Intention, BDI）智能体（BDIx），在无需基站协助的情况下独立、自主地管理每个D2D节点。本文包含用于传输模式决策的详细算法描述，该决策可在考虑计算负载的同时最大化数据速率、最小化功耗。仿真结果表明，BDI智能体可应用于联合解决D2D相关挑战。
英文摘要：
Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
