Proportional Fairness-Based Resource Allocation for LTE-U Coexisting With Wi-Fi

To further boost the performance of LTE to meet the ever-increasing mobile traffic demand in a cost-effective way, applying LTE in unlicensed spectrum, known as LTE-U technology, is considered as a promising complementary solution for achieving the ultra-capacity foreseen in 5G and beyond. In the un...

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Bibliographic Details
Main Authors: Hongli He, Hangguan Shan, Aiping Huang, Lin X. Cai, Tony Q. S. Quek
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7558177/
Description
Summary:To further boost the performance of LTE to meet the ever-increasing mobile traffic demand in a cost-effective way, applying LTE in unlicensed spectrum, known as LTE-U technology, is considered as a promising complementary solution for achieving the ultra-capacity foreseen in 5G and beyond. In the unlicensed spectrum, LTE-U will share the channel with other unlicensed networks, e.g., Wi-Fi. However, the centralized control architecture of LTE networks is inherently different from the distributed channel access of Wi-Fi network, which poses great challenges to achieve fair coexistence of the two networks. To this end, in this paper, we propose a cross-layer proportional fairness (PF)-based framework to jointly optimize the protocol parameters of the medium access control layer and physical layer of an LTE-U network. Specifically, to achieve throughput-oriented PF between the two heterogeneous networks, the cross-layer optimization framework can be decoupled into a device number weighted time occupation ratio-oriented PF optimization problem and a channel-power allocation-based instantaneous transmission rate-oriented PF optimization problem. Given that LTE-U base stations adopt a listen-before-talk-based channel access scheme, the interactions between the LTE-U and the Wi-Fi networks are modeled by two interactive Markov chains. The effectiveness and the superior performance of the proposed cross-layer PF-based optimization framework are demonstrated and verified by simulations.
ISSN:2169-3536