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Characterizing Resource Allocation Trade-Offs in 5G NR Serving Multicast and Unicast Traffic

Research output: Contribution to journalArticleScientificpeer-review

44 Citations (Scopus)
49 Downloads (Pure)

Abstract

The use of highly directional antenna radiation patterns for both the access point (AP) and the user equipment (UE) in the emerging millimeter-wave (mmWave)-based New Radio (NR) systems is inherently beneficial for unicast transmissions by providing an extension of the coverage range and eventually resulting in lower required NR AP densities. On the other hand, efficient resource utilization for serving multicast sessions demands narrower antenna directivities, which yields a trade-off between these two types of traffic that eventually affects the system deployment choices. In this work, with the tools from queuing theory and stochastic geometry, we develop an analytical framework capturing both the distance- and traffic-related aspects of the NR AP serving a mixture of multicast and unicast traffic. Our numerical results indicate that the service process of unicast sessions is severely compromised when (i) the fraction of unicast sessions is significant, (ii) the spatial session arrival intensity is high, or (iii) the service time of the multicast sessions is longer than that of the unicast sessions. To balance the multicast and unicast session drop probabilities, an explicit prioritization is required. Furthermore, for a given fraction of multicast sessions, lower antenna directivity at the NR AP characterized by a smaller NR AP inter-site distance (ISD) leads to a better performance in terms of multicast and unicast session drop probabilities. Aiming to increase the ISD, while also maintaining the drop probability at the target level, the serving of multicast sessions is possible over the unicast mechanisms, but it results in worse performance for the practical NR AP antenna configurations. However, this approach may become feasible as arrays with higher numbers of antenna elements begin to be available. Our developed mathematical framework can be employed to estimate the parameters of the NR AP when handling a mixture of multicast and unicast sessions as well as drive a lower bound on the density of the NR APs, which is needed to serve a certain mixture of multicast and unicast traffic types with their target performance requirements.

Original languageEnglish
Article number9003488
Pages (from-to)3421-3434
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume19
Issue number5
DOIs
Publication statusPublished - 1 May 2020
Publication typeA1 Journal article-refereed

Funding

Manuscript received July 4, 2019; revised November 9, 2019; accepted February 1, 2020. Date of publication February 19, 2020; date of current version May 8, 2020. The publication has been prepared with the support of the “RUDN University Program 5-100” (recipient Samouylov K.E.). This work was supported in part by RFBR under Project 19-07-00933 (Gaidamaka Yu.V.) and Project 20-07-01064 (Kovalchukov R.N.), in part by the Business Finland 5G-FORCE Project, in part by the Academy of Finland under Project RADIANT, in part by the framework of the COST Action CA15104, and in part by the Inclusive Radio Communication Networks for 5G and beyond (IRACON). The associate editor coordinating the review of this article and approving it for publication was W. Chen. (Corresponding author: Rustam Pirmagomedov.) Andrey Samuylov, Dmitri Moltchanov, Roman Kovalchukov, Rustam Pirmagomedov, Sergey Andreev, and Yevgeni Koucheryavy are with Tampere University, 33720 Tampere, Finland (e-mail: andrey.samuylov@ tuni.fi; [email protected]; [email protected]; rustam. [email protected]; [email protected]; [email protected]).

Keywords

  • 5G mobile communication
  • directional multicasting
  • millimeter wave communication
  • multicast communication
  • resource management

Publication forum classification

  • Publication forum level 3

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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