Conditional handover (CHO) is one of several promising mobility enhancements in 5G networks. By making preparation decisions earlier than in LTE HO, CHO can provide an improved HO success rate. This article, analyzes the strengths and weaknesses of CHO by comparing CHO to 5G baseline HO. Since millimeter-wave communications are vulnerable to blockages, sudden changes in signal reception power can mislead CHO into making undesired early preparations in 5G networks. To enhance the robustness of CHO, current studies propose using an increased number of preparations, resulting in considerable signaling overhead. This article offers a novel prediction-based CHO (PCHO) scheme that uses deep-learning technology to overcome the weaknesses of CHO and make more intelligent preparation decisions. Based on the changes in the signal patterns of the base stations, PCHO uses former blockage information to predict the best next base station to which to conduct HO. Performance evaluation demonstrates that PCHO can improve the early preparation success rate while reducing signaling overhead compared to current CHO schemes.

中文翻译：

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用于 5G 毫米波网络的基于预测的条件切换：一种深度学习方法

条件切换 (CHO) 是 5G 网络中几种有前途的移动性增强功能之一。通过比 LTE HO 更早地做出准备决策，CHO 可以提供改进的 HO 成功率。本文通过比较 CHO 和 5G 基线 HO 来分析 CHO 的优缺点。由于毫米波通信容易受到阻塞，信号接收功率的突然变化可能会误导 CHO 在 5G 网络中进行不必要的早期准备。为了提高 CHO 的稳健性，目前的研究建议使用更多的制剂，从而导致相当大的信号开销。本文提供了一种新颖的基于预测的 CHO (PCHO) 方案，该方案使用深度学习技术来克服 CHO 的弱点，并做出更智能的准备决策。PCHO根据基站信号模式的变化，利用前一个阻塞信息来预测下一个最佳的HO基站。性能评估表明，与当前的 CHO 方案相比，PCHO 可以提高早期准备成功率，同时减少信号开销。