The ambition of providing ubiquitous, fast, and mobile communication services to all types of devices, such as handheld, vehicular and IoT, has resulted in tremendous complexity in our wireless networks, and the trend is only likely to accelerate. As a result, it is becoming exponentially harder to create good analytical models to describe the behavior of systems. Even if models exist, they are complex enough that optimization of such a system is prohibitive in terms of complexity. A few concrete examples of such optimization problems can help illuminate the issue better.

中文翻译：

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基于 AI/ML 的下一代智能无线网络的培训、测试和验证挑战


为所有类型的设备（例如手持设备、车载设备和物联网）提供无处不在、快速的移动通信服务的雄心导致我们的无线网络变得极其复杂，而且这种趋势只会加速。因此，创建良好的分析模型来描述系统行为变得越来越困难。即使模型存在，它们也足够复杂，以至于对这种系统的优化在复杂性方面是令人望而却步的。此类优化问题的一些具体示例可以帮助更好地阐明该问题。