Reliable group video call is one of the main services offered by future Mission-Critical Communications (MCC). To support its requirements, coordinated multi-point transmission in multi-cell environments is an attractive feature for MCC over Multimedia Broadcast Multicast Services owing to its potential for coverage improvement and multicast transmission. In such a scheme, full cooperation among all cells of an area achieves the highest cooperative gain, but has stringent impact on system capacity. A trade-off in the cluster’s size of serving cells thus arises between high Signal to Interference plus Noise Ratio (SINR) and network capacity. In this paper, we formulate an optimization problem to maintain an acceptable system blocking probability, while maximizing the average SINR of the multicast group users. For every multicast group to be served, a dynamic cluster of cells is selected based on the minimization of a submodular function that takes into account the traffic in every cell through some weights and the average SINR achieved by the group users. Traffic weights are then optimized using a modified Nelder-Mead simplex method with the objective of tracking a blocking probability threshold. The proposed clustering scheme is compared to full cooperation and to Single-Cell Point-To-Multipoint (SC-PTM) schemes. Results show that dynamic clustering offers the best trade-off between coverage and capacity for MCC.

中文翻译：

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任务关键型通信中多点传输的动态聚类算法

可靠的群组视频通话是未来关键任务通信 (MCC) 提供的主要服务之一。为了满足其要求，多小区环境中的协调多点传输对于多媒体广播多播服务上的 MCC 来说是一个有吸引力的功能，因为它具有改善覆盖范围和多播传输的潜力。在这样的方案中，一个区域内所有小区之间的充分合作可以获得最高的合作增益，但对系统容量的影响很大。因此，在高信号干扰加噪声比 (SINR) 和网络容量之间出现了服务小区集群大小的权衡。在本文中，我们制定了一个优化问题，以保持可接受的系统阻塞概率，同时最大化组播组用户的平均 SINR。对于每个要服务的多播组，基于子模块函数的最小化选择动态小区集群，该函数通过一些权重考虑每个小区中的流量和组用户实现的平均 SINR。然后使用改进的 Nelder-Mead 单纯形法优化流量权重，目的是跟踪阻塞概率阈值。将所提出的集群方案与完全合作和单小区点对多点 (SC-PTM) 方案进行比较。结果表明，动态聚类为 MCC 提供了覆盖范围和容量之间的最佳权衡。然后使用改进的 Nelder-Mead 单纯形法优化流量权重，目的是跟踪阻塞概率阈值。将所提出的集群方案与完全合作和单小区点对多点 (SC-PTM) 方案进行比较。结果表明，动态聚类为 MCC 提供了覆盖范围和容量之间的最佳权衡。然后使用改进的 Nelder-Mead 单纯形法优化流量权重，目的是跟踪阻塞概率阈值。将所提出的集群方案与完全合作和单小区点对多点 (SC-PTM) 方案进行比较。结果表明，动态聚类为 MCC 提供了覆盖范围和容量之间的最佳权衡。