论文标题
物联网的压缩大量访问：云计算或雾计算？
Compressive Massive Access for Internet of Things: Cloud Computing or Fog Computing?
论文作者
论文摘要
本文考虑了无赠款的大规模访问的支持，并解决了大量用户数量的主动用户检测和渠道估计的挑战。通过利用用户活动的稀疏性，相关问题被提出为压缩感应问题，其解决方案是通过近似消息传递（AMP）算法获得的。考虑到多个访问点的合作，对于AMP算法的部署，我们就两个处理范式，云计算和雾计算进行了比较，以保证超可靠的低延迟访问权限。对于云计算，访问点以云无线电访问网络（C-RAN）方式连接，并且在所有访问点接收到的信号都集中并在云基频带单元中共同处理。对于雾计算，基于雾无线电访问网络（F-RAN），则分割了用户活动和整个网络的相应渠道的估计，并且相关处理任务是在接近用户的访问点和FOG处理单元上执行的。与基于传统C-RAN的云计算范式相比，仿真结果证明了基于F-RAN的雾计算部署的优势。
This paper considers the support of grant-free massive access and solves the challenge of active user detection and channel estimation in the case of a massive number of users. By exploiting the sparsity of user activities, the concerned problems are formulated as a compressive sensing problem, whose solution is acquired by approximate message passing (AMP) algorithm. Considering the cooperation of multiple access points, for the deployment of AMP algorithm, we compare two processing paradigms, cloud computing and fog computing, in terms of their effectiveness in guaranteeing ultra reliable low-latency access. For cloud computing, the access points are connected in a cloud radio access network (C-RAN) manner, and the signals received at all access points are concentrated and jointly processed in the cloud baseband unit. While for fog computing, based on fog radio access network (F-RAN), the estimation of user activity and corresponding channels for the whole network is split, and the related processing tasks are performed at the access points and fog processing units in proximity to users. Compared to the cloud computing paradigm based on traditional C-RAN, simulation results demonstrate the superiority of the proposed fog computing deployment based on F-RAN.
