In this paper, we study the problem of topology optimization and routing in integrated access and backhaul (IAB) networks, as one of the promising techniques for evolving 5G networks. We study the problem from different perspectives. We develop efficient genetic algorithm-based schemes for both IAB node placement and non-IAB backhaul link distribution, and evaluate the effect of routing on bypassing temporal blockages. Here, concentrating on millimeter wave-based communications, we study the service coverage probability, defined as the probability of the event that the user equipments' (UEs) minimum rate requirements are satisfied. Moreover, we study the effect of different parameters such as the antenna gain, blockage and tree foliage on the system performance. Finally, we summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on routing in IAB networks, and discuss the main challenges for enabling mesh-based IAB networks. As we show, with a proper network topology, IAB is an attractive approach to enable the network densification required by 5G and beyond.

中文翻译：

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集成接入和回程网络中的拓扑优化和路由：基于遗传算法的方法

在本文中，我们研究了集成接入和回程（IAB）网络中的拓扑优化和路由问题，这是发展5G网络的有希望的技术之一。我们从不同角度研究问题。我们为IAB节点放置和非IAB回程链路分配开发了基于遗传算法的高效方案，并评估了绕过临时性阻塞的路由效果。在这里，我们集中在基于毫米波的通信上，研究服务覆盖概率，服务覆盖概率定义为满足用户设备（UE）最低速率要求的事件的概率。此外，我们研究了不同参数（例如天线增益，阻塞和树木枝叶）对系统性能的影响。最后，我们总结了最近的Rel-16以及即将进行的Rel-17 3GPP关于IAB网络中路由的讨论，并讨论了启用基于网状IAB网络的主要挑战。正如我们所展示的那样，通过适当的网络拓扑，IAB是一种有吸引力的方法，可以实现5G及更高版本所需的网络致密化。