Facing a vast amount of connections, huge performance demands, and the need for reliable connectivity, the sixth generation of communication networks (6G) is envisioned to implement disruptive technologies that jointly spur connectivity, performance, and reliability. In this context, this paper proposes, and evaluates the benefit of, a hybrid central cloud (CC) computing and mobile edge computing (MEC) platform, especially introduced to balance the network resources required for joint computation and communication. Consider a hybrid cloud and MEC system, where several power-hungry multi-antenna unmanned aerial vehicles (UAVs) are deployed at the cell-edge to boost the CC connectivity and relieve part of its computation burden. While the multi-antenna base stations are connected to the cloud via capacity-limited fronthaul links, the UAVs serve the cell-edge users with limited power and computational capabilities. The paper then considers the problem of maximizing the weighted network sum-rate subject to per-user delay, computational capacity, and power constraints, so as to determine the beamforming vectors and computation allocations. Such intricate non-convex optimization problem is tackled using an iterative algorithm that relies on $\ell_0$-norm relaxation, successive convex approximation, and fractional programming, and has the compelling ability to be implemented in a distributed fashion across the multiple UAVs and the CC. The paper results illustrate the numerical prospects of the proposed algorithm for enabling joint communication and computation, and highlight the appreciable improvements of data processing delays and throughputs as compared to conventional system strategies.
翻译:面对大量连接、巨大的性能需求以及可靠的连通需求,第六代通信网络(6G)设想在第六代通信网络(6G)中采用干扰技术,共同促进连通性、性能和可靠性;在此背景下,本文件提出并评估混合中央云计算和移动边缘计算(MEC)平台的惠益,特别是为了平衡联合计算和通信所需的网络资源而引入的平台;考虑混合云和MEC系统,其中将几台超强饥饿多亚麻牛无人驾驶飞行器(UAVs)部署在细胞顶端,以提升CC连通性并减轻其计算负担的部分负担;多亚麻牛基地台站通过能力有限的前厅链接与云连接,而UAVS服务于电力和计算能力有限的细胞顶端用户。 本文随后审议了将加权网络总和比率最大化的问题,条件是每个用户延迟、计算能力以及电力限制,以便确定对矢量和计算量的改进度。 如此复杂的非碳化优化纸质文件问题正在通过不断更新的逻辑算算算算算算法来解决。