The problem of base station cooperation has recently been set within the framework of Stochastic Geometry. Existing works consider that a user dynamically chooses the set of stations that cooperate for his/her service. However, this assumption often does not hold. Cooperation groups could be predefined and static, with nodes connected by fixed infrastructure. To analyse such a potential network, in this work we propose a grouping method based on proximity. It is a variation of the so called Nearest Neighbour Model. We restrict ourselves to the simplest case where only singles and pairs of base stations are allowed to be formed. For this, two new point processes are defined from the dependent thinning of a Poisson Point Process, one for the singles and one for the pairs. Structural characteristics for the two are provided, including their density, Voronoi surface, nearest neighbour, empty space and J-function. We further make use of these results to analyse their interference fields and give explicit formulas to their expected value and their Laplace transform. The results constitute a novel toolbox towards the performance evaluation of networks with static cooperation.
翻译:最近,在Stochacistic 几何测量框架内确定了基地站合作问题。 现有工作认为用户动态地选择了配合其服务的一组台站。 但是,这一假设往往站不住脚。 合作小组可以预先确定,静态,通过固定基础设施连接节点。 为了分析这种潜在的网络,我们在这项工作中建议了一个基于近距离的分组方法。 这是所谓的近邻模型的变异。 我们仅限于一个最简单的案例,即只允许形成单体和对等基地台站。 对于这个案例,两个新点程序是从 Poisson点进程的依赖性减速中定义的,一个是单体的,一个是双体的。 提供了两个小组的结构特征,包括密度、Voronoi表面、近邻、空空间和J功能。 我们进一步利用这些结果来分析它们的干扰场,并给出其预期值和拉韦特变换的清晰公式。 其结果构成了一个用于静式合作网络绩效评估的新工具箱。