In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain–even if they are located outside the carrier sense range of each other–in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.

中文翻译：

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空间分布式高密度 WLAN 中的动态信道绑定

在本文中，我们讨论了空间分布式高密度无线局域网 (WLAN) 中动态信道绑定 (DCB) 对吞吐量和公平性的影响。首先，我们提出了一个基于连续时间马尔可夫网络 (CTMN) 的分析框架，用于描述不同 DCB 策略在空间分布式场景中的行为，其中节点不需要在彼此的载波侦听范围内。然后，我们通过仿真评估 DCB 在高密度 IEEE 802.11ac/ax WLAN 中的性能。我们表明，空间域中的节点之间可能存在关键的相互关系——即使它们位于彼此的载波侦听范围之外——以连锁反应的方式。结果还表明，虽然总是选择最宽的可用信道通常可以最大限度地提高个人长期吞吐量，它通常会导致其他 WLAN 饿死的不公平情况。此外，我们展示了在某些情况下，具有随机通道宽度选择的 DCB 在个人吞吐量和公平性方面改进了后一种方法。因此，对于每种情况都没有唯一的最优 DCB 策略。相反，在下一代 WLAN 的挑战性场景中需要更智能的带宽适应。