Flexible DRX Optimization for LTE and 5G

With the advancement of the next generation of cellular systems, flexible mechanisms for Discontinuous Reception (DRX) are needed in order to save energy. 5G will bring heterogeneous packet sizes and traffic types, as well as an increasing need for energy efficiency. The current static DRX mechanism is inadequate to meet these needs. In this paper we exploit channel prediction to develop integer programming models. We aim to minimize the energy usage of user devices while streaming video, as well as to create extended sleep opportunities, while simultaneously preventing buffer underflows. We also develop an online algorithm to obtain an efficient solution robust to prediction errors. Our results show that using a variable DRX cycle length can reduce the energy usage by up to 60 percent and 40 percent, in the offline and online cases, respectively, compared with a static DRX configuration. Our proposed online algorithm can also reduce the number of buffer underflows by up to 97 percent compared to the offline case. Both our online and offline solutions can provide extended DRX opportunities, which is required in 5G scenarios.

[1]  Brian W. Kernighan,et al.  AMPL: A Modeling Language for Mathematical Programming , 1993 .

[2]  Kai-Ten Feng,et al.  Design and Analysis of Traffic-Based Discontinuous Reception Operations for LTE Systems , 2017, IEEE Transactions on Wireless Communications.

[3]  Hossam S. Hassanein,et al.  Predictive green wireless access: exploiting mobility and application information , 2013, IEEE Wireless Communications.

[4]  Mingfu Li,et al.  Energy-Efficient Traffic Regulation and Scheduling for Video Streaming Services Over LTE-A Networks , 2019, IEEE Transactions on Mobile Computing.

[5]  M. Sajid Mushtaq,et al.  Power saving model for mobile device and virtual base station in the 5G era , 2017, 2017 IEEE International Conference on Communications (ICC).

[6]  Mahbub Hassan,et al.  Improving QoS in High-Speed Mobility Using Bandwidth Maps , 2012, IEEE Transactions on Mobile Computing.

[7]  Yang Liu,et al.  Grouping-Based Discontinuous Reception for Massive Narrowband Internet of Things Systems , 2018, IEEE Internet of Things Journal.

[8]  Huei-Wen Ferng,et al.  Exploring Flexibility of DRX in LTE/LTE-A: Design of Dynamic and Adjustable DRX , 2018, IEEE Transactions on Mobile Computing.

[9]  Gang Feng,et al.  Power-saving coercive sleep mode for machine type communications , 2017, 2017 23rd Asia-Pacific Conference on Communications (APCC).

[10]  Guizhong Liu,et al.  Playout buffer and DRX aware scheduling scheme for video streaming over LTE system , 2016, IET Commun..

[11]  Amitav Mukherjee,et al.  Energy Efficiency and Delay in 5G Ultra-Reliable Low-Latency Communications System Architectures , 2018, IEEE Network.

[12]  Mehmet Karaca,et al.  Optimizing DRX for video delivery over LTE: Utilizing channel prediction and in-network caching , 2017, 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[13]  Navrati Saxena,et al.  Hybrid Directional Discontinuous Reception (HD-DRX) for 5G Communication , 2017, IEEE Communications Letters.

[14]  Optimizing stored video delivery for mobile networks: The value of knowing the future , 2013, 2013 Proceedings IEEE INFOCOM.

[15]  Navrati Saxena,et al.  Directional-DRX for 5G wireless communications , 2016 .

[16]  Hung-Yu Wei,et al.  Energy-Efficient Millimeter-Wave M2M 5G Systems with Beam-Aware DRX Mechanism , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[17]  Pavlos I. Lazaridis,et al.  Video performance using adaptive DRX switching for LTE-A , 2017, 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB).

[18]  Hossam S. Hassanein,et al.  Energy-Efficient Adaptive Video Transmission: Exploiting Rate Predictions in Wireless Networks , 2014, IEEE Transactions on Vehicular Technology.

[19]  Jyh-Cheng Chen,et al.  Adjustable Extended Discontinuous Reception Cycle for Idle-State Users in LTE-A , 2016, IEEE Communications Letters.

[20]  Gang Feng,et al.  Online Learning-Based Discontinuous Reception (DRX) for Machine-Type Communications , 2019, IEEE Internet of Things Journal.

[21]  Gunnar Mildh,et al.  A novel state model for 5G Radio Access Networks , 2016, 2016 IEEE International Conference on Communications Workshops (ICC).

[22]  Andreas Ermedahl,et al.  Data driven selection of DRX for energy efficient 5G RAN , 2017, 2017 13th International Conference on Network and Service Management (CNSM).