We target the planning of a 5G cellular network under 5G service and ElectroMagnetic Fields (EMFs) constraints. We initially model the problem with a Mixed Integer Linear Programming (MILP) formulation. The pursued objective is a weighed function of next-generation Node-B (gNB) installation costs and 5G service coverage level from a massive Multiple Input Multiple Output (MIMO) system. In addition, we precisely model restrictive EMF constraints and we integrate scaling parameters to estimate the power radiated by 5G gNBs. Since the considered planning problem is NP-Hard, and therefore very challenging to be solved even for small problem instances, we design an efficient heuristic, called PLATEA, to practically solve it. Results, obtained over a realistic scenario that includes EMF exposure from pre-5G technologies (e.g., 2G, 3G, 4G), prove that the cellular planning selected by PLATEA ensures 5G service and restrictive EMF constraints. However, we demonstrate that the results are strongly affected by: i) the relative weight between gNB installation costs and 5G service coverage level, ii) the scaling parameters to estimate the exposure generated by 5G gNBs, iii) the amount of exposure from pre-5G technologies and iv) the adopted frequency reuse scheme.
翻译:我们的目标是在5G服务和电磁场的限制下规划5G蜂窝网络,我们最初用混合整形线性编程(MILP)的配方来模拟问题,我们追求的目标是从大规模多输入多重输出系统(MIIMO)中权衡下一代节点-B(GNB)安装成本和5G服务覆盖水平的权重功能;此外,我们精确地模拟限制性EMF限制,并结合规模化参数来估计5GGGNB所辐射的电量;由于考虑的规划问题是NP-Hard,因此即使是小问题也非常难以解决,我们设计了一种高效的脂质(称为PLATEA),以切实解决这一问题。结果是在现实的假设中取得的,其中包括5G前技术(例如2G、3G、4G)对EMF的暴露程度。此外,我们证明PLATEATEA选定的蜂窝规划确保了5G服务和限制性的EMF限制。然而,我们证明,结果受到以下因素的严重影响:i)GNBB安装成本与5G服务覆盖水平之间的相对重量和5G服务覆盖水平,通过5G接触频率水平,根据NBV技术对5G接触率的估算得出的标准。