A novel convex power adaptation strategy for multicast communications using Random Linear Network Coding schemes

Andrea Tassi*, Dania Marabissi, Romano Fantacci, David Di Lorenzo, Mirko Maischberger

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)

Abstract

3GPP's Long Term Evolution (LTE) represents the one of the most valuable alternatives to offer a wireless broadband access in fully mobile network context. In particular LTE is able to manage several communication flows characterized by different QoS constrains. This paper deals with a network topology where the mobile users are clustered in Multicast Groups and the base station broadcasts a different traffic flow to each cluster. In order to improve the network throughput on a per-user basis, all communications rely on a Random Linear Network Coding (RLNC) scheme. A key aspect in the QoS management is represented by the power adaptation strategy in use. This paper proposes a novel convex formulation to the power adaptation problem for the downlink phase taking into account the specific RLNC scheme adopted by each communication flow. By the proposed convex formalization, an optimal solution of the problem can be early found in real time. Moreover, the proposed power adaptation strategy shows good performance for what concern throughput and fairness among the users when compared with other alternatives.

Original languageEnglish
Title of host publicationIEEE International Conference on Communications
Pages5270-5274
Number of pages5
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Conference on Communications, ICC 2012 - Ottawa, ON, Canada
Duration: 10 Jun 201215 Jun 2012

Conference

Conference2012 IEEE International Conference on Communications, ICC 2012
CountryCanada
CityOttawa, ON
Period10/06/1215/06/12

Fingerprint Dive into the research topics of 'A novel convex power adaptation strategy for multicast communications using Random Linear Network Coding schemes'. Together they form a unique fingerprint.

Cite this