Smart Edge Caching-Aided Partial Opportunistic Interference Alignment in HetNets
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Smart Edge Caching-Aided Partial Opportunistic Interference Alignment in HetNets Jie Zheng1
· Ling Gao2 · Hai Wang1 · Jinping Niu1 · Jie Ren3 · Hongbo Guo1 · Xudong Yang1 · Yi Liu1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The development of the next-generation wireless networks are regarded as the essentials to embrace of Internet of Things (IoT) and edge computing in heterogeneous networks (HetNets). Due to the the spectrum scarcity problem and the large number of connectivity demand of IoT users, intelligent interference management for IoT is worthy of thorough investigation and should be well discussed with consideration on edge computing in heterogeneous networks (HetNets). Two crucial challenges in the context are: 1) placing edge cache based on dynamic request of IoT users, and 2) cache-enabled interference management with time-varying wireless channels. In this paper, we proposed smart edge caching-aided partial opportunistic interference alignment(POIA) with deep reinforcement learning for IoT downlink system in HetNets. Towards this end, the proposed scheme can update the base station (BS) cache dynamically, and then select the optimal cache-enabled POIA user group considering the time-varying user’s requests and time-varying wireless channels. To solve this problem efficiently, the reinforcement learning is exploited that can take advantage of a deep Q-learing to replace the system action. Extensive evaluations demonstrate that the proposed method is effectiveness according to sum rate and energy efficiency of IoT downlink transmission for HetNets. Keywords Heterogeneous networks · Internet of things · Opportunistic interference alignment · Edge computing · Deep reinforcement learning · Edge caching
1 Introduction As the evolution of edge computing for future wireless Internet of Things (IoT) networks, edge caching has been Jie Zheng
[email protected] Ling Gao [email protected] Jinping Niu [email protected] 1
State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, School of Information Science and Technology, Northwest University, Xi’an, 710127, Shaanxi, China
2
State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Services, College of Computer Science, Xi’an Polytechnic University, Xi’an, 710600, Shaanxi, China
3
School of Computer Science, Shaanxi Normal University, Xi’an 710119, China
used to improve the spectral efficiency, download delay, and energy efficiency of wireless networks [1–4]. Proactively placing the frequently requested data (e.g. update code or popular contents) in edge cache would mitigate the heavy load of the backhaul links by cutting down the repetition content for wireless transmission. Moreover, the cacheaided at base station (BS) and IoT devices can relieve the interference to boost the system capacity for wireless IoT network [5]. The downlink transmission in cellular network with base station (BS) cache has been studied to aug
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