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

作者：Asheesh Tripathi, Fahim Bashar, M. R. Chowdhury, Aloizio Da Silva, S. Midkiff · 发表于：IEEE Wireless Communications and Networking Conference · 年份：2025 · DOI：10.1109/wcnc61545.2025.10978285 · 被引用次数：4 · 研究领域：Computer Science

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.