A Social-Energy Based Cluster Management Scheme for User-Centric Ultra-Dense Networks

• Main Authors: Zhaolong Huang, Hui Tian, Cheng Qin, Shaoshuai Fan, Xixi Zhang
• Format: Article
• Language: English
• Published: IEEE 2017-01-01
• Series: IEEE Access
• Subjects: Ultra-dense network; mmWave; AP cluster; matching game; personalized recommendation
• Online Access: https://ieeexplore.ieee.org/document/7933971/

With the exponential growth of traffic demand, ultra-dense networks are proposed to increase the network capacity. However, the high-density access point (AP) deployment will increase the complexity of AP coordination, and AP cluster (APC) needs to be considered in practical implementations. Due to the dynamic changes in spatiotemporal distribution of users and service demand, we propose a social-energy-based cluster management (SECM) scheme in order to reduce APC update frequency. Specifically, in social domain, we propose a congeniality-based personalized recommendation (CPR) algorithm to predict users' incoming requests. We further propose a CPR-based AP cluster algorithm to solve the matching problem among users, APs, and content. In energy domain, we propose an inter-cluster energy cooperation scheme to avoid the shutting down of members in AP cluster and reduce the update of clusters. Numerical results demonstrate that our proposed scheme can achieve a gain of 77.8% in the APC management utility averagely, without loss of fairness compared with the other state-of-the-art schemes.