Flexible DRX Optimization for LTE and 5G
(2020) In IEEE Transactions on Vehicular Technology 69(1). p.607-621- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/a51045a5-6f47-42d5-a1ef-47364fece7c4
- author
- Moradi, Farnaz LU ; Fitzgerald, Emma LU ; Pioro, Michal LU and Landfeldt, Björn LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- 5G mobile communication, channel capacity, streaming media, optimization, prediction algorithms, DRX, Integer programming, resource allocation, video streaming, energy efficiency
- in
- IEEE Transactions on Vehicular Technology
- volume
- 69
- issue
- 1
- pages
- 607 - 621
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85078456091
- ISSN
- 0018-9545
- DOI
- 10.1109/TVT.2019.2952251
- project
- Cyber Security for Next Generation Factory (SEC4FACTORY)
- language
- English
- LU publication?
- yes
- id
- a51045a5-6f47-42d5-a1ef-47364fece7c4
- date added to LUP
- 2019-12-03 11:22:20
- date last changed
- 2023-04-10 04:18:34
@article{a51045a5-6f47-42d5-a1ef-47364fece7c4, abstract = {{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.}}, author = {{Moradi, Farnaz and Fitzgerald, Emma and Pioro, Michal and Landfeldt, Björn}}, issn = {{0018-9545}}, keywords = {{5G mobile communication; channel capacity; streaming media; optimization; prediction algorithms; DRX; Integer programming; resource allocation; video streaming; energy efficiency}}, language = {{eng}}, number = {{1}}, pages = {{607--621}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Vehicular Technology}}, title = {{Flexible DRX Optimization for LTE and 5G}}, url = {{http://dx.doi.org/10.1109/TVT.2019.2952251}}, doi = {{10.1109/TVT.2019.2952251}}, volume = {{69}}, year = {{2020}}, }