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A Real-Time Solution for Underlay Coexistence with Channel Uncertainty
Conference proceeding   Peer reviewed

A Real-Time Solution for Underlay Coexistence with Channel Uncertainty

Shaoran Li, Yan Huang, Chengzhang Li, Brian Jalaian, Stephen Russell, Y. Thomas Hou, Wenjing Lou and Benjamin MacCall
IEEE Global Communications Conference (Online), 9014147
Global Communications Conference (GLOBECOM) (Waikoloa, Hawaii, USA, 12/09/2019–12/13/2019)
12/2019
DOI: https://doi.org/10.1109/GLOBECOM38437.2019.9014147
Web of Science ID: WOS:000552238605087

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Abstract

Underlay coexistence is an effective mechanism to improve spectrum effïciency by having picocells coexist with macrocell on the same spectrum. Due to a lack of cooperation between the primary users (PUs) in the macrocell and secondary users (SUs) in the picocell, it is impossible to have complete knowledge of channel gains between them. Under such circumstance, chance-constrained programming (CCP) is shown to be the ideal optimization tool to address such uncertainty. However, solutions to CCP are computationally intensive and cannot meet 5G's timing requirement. To address this problem, we propose a novel scheduler called GUC (stands for GPU-based Underlay Coexistence) to find an approximate solution to CCP in real-time. The essence of GUC is to decompose the original optimization problem into a large number of small problems that are suitable for parallel computation on GPU platforms. Through extensive experiments, we show that GUC reduces the scheduling computation time by at least 10,000 times comparing to commercial solvers (on CPU) while achieving an average of 90% optimality.

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