A Network-Coded Cooperation Protocol for Efficient Massive Content Distribution
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Massive content delivery in cellular networks is in the spotlight of the research community as data traffic is increasing at an incredibly fast pace. The existing LTE-A implementation for content broadcast presents several issues such as indoor coverage, along with low energy and spectral efficiency. Therefore, novel systems that provide efficient massive content delivery and reduced energy consumption are needed. In this paper we present a massive content distribution protocol that combines the benefits of cooperative mobile clouds (CMCs) with Random Linear Network Coding (RLNC) through multicast WiFi links. Our main goal is to offload data traffic from the LTE-A link and to reduce the energy consumption at the cooperating UEs. We solve the problem of excessive signaling that oftentimes arises in cooperative approaches by eliminating feedback messages within the CMCs. Instead, we provide a simple but accurate analytic model to correctly configure the number of coded transmissions to be performed within the CMCs. Results show that energy savings of more than 37 percent can be achieved with our protocol when compared to direct content download from the cellular base station. Furthermore, bandwidth utilization at the LTE-A link is sharply reduced.
Details
Original language | English |
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Title of host publication | 2018 IEEE Global Communications Conference (GLOBECOM) |
Pages | 1-7 |
ISBN (electronic) | 978-1-5386-4727-1 |
Publication status | Published - 2018 |
Peer-reviewed | Yes |
Publication series
Series | IEEE Conference on Global Communications (GLOBECOM) |
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ISSN | 1930-529X |
Conference
Title | 2018 IEEE Global Communications Conference, GLOBECOM 2018 |
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Duration | 9 - 13 December 2018 |
City | Abu Dhabi |
Country | United Arab Emirates |
External IDs
ORCID | /0000-0001-7008-1537/work/158767481 |
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ORCID | /0000-0001-8469-9573/work/161891243 |