5G异构网络中基于关联概率的RAT选择

Behrad Soleyman, Amirreza Zaman, Seyed Hamed Rastegar, V. Shah-Mansouri
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引用次数: 10

摘要

在未来的异构蜂窝网络中,使用多种无线接入技术是不可避免的。不同的RAT可以提供不同的吞吐量,因此RAT的选择在服务供应质量中起着重要的作用。本文针对具有两类吞吐量的异构网络,提出了一种实用的概率RAT选择方法。与常见的确定性方法相反,在该方案中,每个用户使用由网络中的中心单元确定的关联概率,以随机方式周期性地执行RAT选择。用户在一段特定的时间内保持与所选RAT的连接,然后再次执行选择。为了求出关联概率,给出了网络吞吐量最大化的公式。由于所得到的问题不是凸的,我们提出了两种替代方案,一种是次优解,但复杂性较低,另一种是使用最优解的变量变化。最后,数值模拟表明,与几种可能的方法相比,我们提出的方案具有优越的性能。此外,这些数值研究表明,我们的次优方法非常接近最优方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RAT selection based on association probability in 5G heterogeneous networks
The use of multiple radio access technologies (RATs) is inevitable in future heterogeneous cellular networks. Various RATs can offer different throughputs, and thus RAT selection plays an important role in quality of service provisioning. In this paper, considering a heterogeneous network with two throughput classes, we introduce a new practical probabilistic RAT selection approach. In contrary to the common deterministic approaches, in this scheme, each user performs the RAT selection periodically in a random manner using an association probability determined by a central unit in the network. The user remains connected to the selected RAT for a specific amount of time and then again performs the selection. To find the association probabilities, the network throughput maximization is formulated. Since the resulting problem is not convex, we propose two alternatives, one with sub-optimal solution but lower complexity and one with the use of change of variables with optimal solution. Finally, numerical simulations demonstrate the superior performance of our proposed schemes in comparison to several possible approaches. Also, these numerical investigations indicate that our sub-optimal method works very close to the optimal one.
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