Benchmarking Software Defined Radio Based 5G Deployments With srsRAN: Lessons Learned

In recent years, the availability of open-source 5G stacks that support the use of Software-Defined Radios (SDRs) as Radio Frequency (RF)-frontends has significantly accelerated experimental 5G research. This has enabled researchers to deploy customized 5G networks and utilize them with both SDR-based and Commercial Off-The-Shelf (COTS) User Equipments (UEs) for various applications. However, SDRs, unlike commercial 5G Radio Units (RUs), are designed to support a wide range of frequencies and protocols, leading to limitations when used specifically for 5G deployments. These limitations include supported Sampling Rates (srates), inherent Local Oscillator (LO) leakages, and limited Transmit (Tx) and Receive (Rx) gains. In this work, we benchmark the throughput performance of 5G standalone networks using the srsRAN 5G stack, Open5GS core, and three SDRs from National Instruments (NI) (X310, N310, and B210) in an indoor Over-the-Air (OTA) environment at varying distances. Measured throughput is compared to the estimated theoretical maximum under identical configurations. Also, we demonstrate how srates and LO leakage affect OTA throughput, comparing results across the three SDR platforms. Additionally, we show that similar Received Signal Strength (RSS) can result in significantly different throughput due to LO leakage, correlating these effects with overall performance. We also provide the dataset of the measured OTA throughput and RSS values.

Authors

Institutions

Publication Details

Published
2025-03-24
DOI
https://doi.org/10.1109/wcnc61545.2025.10978285
Citations
1
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Benchmarking Software Defined Radio Based 5G Deployments With srsRAN: Lessons Learned

Asheesh Tripathi, Scott F. Midkiff, Mayukh Roy Chowdhury, André Felipe Bispo da Silva et al.
1 citations
Advanced MIMO Systems Optimization
0.73
article

Benchmarking Software Defined Radio Based 5G Deployments With srsRAN: Lessons Learned

Asheesh Tripathi, Scott F. Midkiff, Mayukh Roy Chowdhury, André Felipe Bispo da Silva, Fahim Bashar
article en
1 citations

Abstract

In recent years, the availability of open-source 5G stacks that support the use of Software-Defined Radios (SDRs) as Radio Frequency (RF)-frontends has significantly accelerated experimental 5G research. This has enabled researchers to deploy customized 5G networks and utilize them with both SDR-based and Commercial Off-The-Shelf (COTS) User Equipments (UEs) for various applications. However, SDRs, unlike commercial 5G Radio Units (RUs), are designed to support a wide range of frequencies and protocols, leading to limitations when used specifically for 5G deployments. These limitations include supported Sampling Rates (srates), inherent Local Oscillator (LO) leakages, and limited Transmit (Tx) and Receive (Rx) gains. In this work, we benchmark the throughput performance of 5G standalone networks using the srsRAN 5G stack, Open5GS core, and three SDRs from National Instruments (NI) (X310, N310, and B210) in an indoor Over-the-Air (OTA) environment at varying distances. Measured throughput is compared to the estimated theoretical maximum under identical configurations. Also, we demonstrate how srates and LO leakage affect OTA throughput, comparing results across the three SDR platforms. Additionally, we show that similar Received Signal Strength (RSS) can result in significantly different throughput due to LO leakage, correlating these effects with overall performance. We also provide the dataset of the measured OTA throughput and RSS values.

Virginia Tech (US)
Center for Cultural Innovation
Openalex Percentile: Top 29%
Advanced MIMO Systems Optimization
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.