Delphi: Computing the Maximum Achievable Throughput in SD-RAN Environments

Arled Papa, Polina Kutsevol, Fidan Mehmeti, Wolfgang Kellerer

Research output: Contribution to journalArticlepeer-review


Software-Defined Radio Access Networks (SD-RANs) foster the concepts of programmability and flexibility, which are vital for next generation cellular networks. However, SD-RANs render network management and orchestration very challenging. Indeed, related works indicate that when thousands of connected devices are spread across the underlying network, SD-RAN approaches with a single controller become deficient and exhibit undesired behavior. Despite this, state-of-the-art research papers lack concrete solutions and evaluations with respect to throughput predictability, where the latter is jeopardized by irregularities in the SD-RAN control plane, specifically in realistic testbeds. In order to overcome the aforementioned issues, in this work, we present Delphi: a novel platform that provides both analytical and experimental methods to achieve our goal, which is computing the maximum achievable throughput in SD-RAN environments. Analyzing the results provided by Delphi, we can capture the impact of the SD-RAN control plane on throughput. Moreover, we can design important guidelines as to which policy to choose given objectives such as throughput maximization or robustness. Providing a platform for SD-RAN evaluations based on open-source components, Delphi enables new avenues for research in the mobile network community. Focusing on FlexRAN SD-RAN controller for our initial results, overall, our findings show that when the number of Base Stations (BSs) and User Equipment (UEs) in the network increases beyond 5000, due to non-timely received control packets for the maximum Channel Quality Indicator (maxCQI) policy the overall throughput decreases by more than 20%.

Original languageEnglish
Article number3276880
Pages (from-to)4846-4860
Number of pages15
JournalIEEE Transactions on Network and Service Management
Issue number4
StatePublished - 1 Dec 2023


  • 5G
  • RAN virtualization
  • SD-RAN
  • SD-RAN experimentation
  • resource management


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