GPU: A New Enabling Platform for Real-Time Optimization in Wireless Networks
GPU: A New Enabling Platform for Real-Time Optimization in Wireless Networks
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DOI：
10.1109/mnet.011.2000016
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发表时间：
2020-11
期刊：
影响因子：
9.3
通讯作者：
Yan Huang;Shaoran Li;Yongce Chen;Y. T. Hou;Wenjing Lou;J. Delfeld;Vikrama Ditya
中科院分区：
文献类型：
--
作者：
Yan Huang;Shaoran Li;Yongce Chen;Y. T. Hou;Wenjing Lou;J. Delfeld;Vikrama Ditya
优化方法是最大化无线网络和系统性能的常用工具。当解决无线网络中的复杂优化问题时，一个关键的技术挑战是实时找到最优或接近最优的解决方案，特别是当这种时间约束非常短时。由于这一挑战，系统可以实现的最佳效果（如果在真实的时间内找到最佳解决方案）与现场实际实现的效果（由于使用快速算法）之间通常存在严重差异。在本文中，我们提出了一种新的方法，利用问题分解技术和GPU平台的大规模并行处理能力来解决这一挑战。该方法首先将一个复杂的优化问题分解为多个相互独立的子问题。然后将产生的子问题装入大规模并行GPU内核中并同时求解。从GPU并行求解的所有子问题的解中选择最优（或接近最优）解。我们使用5G蜂窝网络中的经典比例公平（PF）调度问题作为案例研究来说明这种方法。最后，我们简要回顾了应用这种方法解决无线网络中各种实时优化问题的最新进展。
Optimization methods are a common tool to maximize the performance of wireless networks and systems. When addressing complex optimization problems in wireless networks, a key technical challenge is to find an optimal or near-optimal solution in real-time, especially when such a timing constraint is extremely short. Due to this challenge, there is usually a serious disparity between what a system can achieve optimally (if an optimal solution were found in real time) and what is actually achieved in the field (due to the use of fast heuristics). in this article, we present a novel approach that exploits problem decomposition techniques and the massive parallel processing capability of GPU platforms to address this challenge. Under the new approach, an original complex optimization problem is first decomposed into a large number of small and mutually independent sub-problems. Then the resulting sub-problems are fitted into massively parallel GPU cores and solved simultaneously. The optimal (or near-optimal) solution is chosen among the solutions from all the parallel sub-problems solved by GPU. We use the classic proportional-fair (PF) scheduling problem in 5G cellular networks as a case study to illustrate this approach. Finally, we briefly review recent advances in applying this approach to addressing a wide array of real-time optimization problems in wireless networks.