This paper considers a mobile edge computing-enabled cell-free massive MIMO wireless network. An optimization problem for the joint allocation of uplink powers and remote computational resources is formulated, aimed at minimizing the total uplink power consumption under latency constraints, while simultaneously also maximizing the minimum SE throughout the network. Since the considered problem is non-convex, an iterative algorithm based on sequential convex programming is devised. A detailed performance comparison between the proposed distributed architecture and its co-located counterpart, based on a multi-cell massive MIMO deployment, is provided. Numerical results reveal the natural suitability of cell-free massive MIMO in supporting computation-offloading applications, with benefits over users' transmit power and energy consumption, the offloading latency experienced, and the total amount of allocated remote computational resources.
翻译:本文考虑的是移动边缘计算机化无细胞型大型MIMO无线网络。在联合分配上行链路电力和远程计算资源方面出现了一个优化问题,目的是在延迟限制下最大限度地减少总上行电力消耗,同时将整个网络的最低SE最大化。由于所考虑的问题是非convex,因此设计了一个基于连续连接编程的迭接算法。提供了在多细胞大规模部署MIMO的基础上对分布式架构及其合用对应方进行的详细绩效比较。数字结果表明,无细胞大型MIMO在支持计算卸载应用方面自然适合,对用户传输电能和能源消耗、脱载延用时间经验以及分配的远程计算资源总量都有好处。