Master Thesis: Adaptive Mixed Periodic and Aperiodic SRS Allocation for MU-MIMO

Join our Team About This Opportunity We are looking for master thesis students who want to explore how periodic and aperiodic SRS resources can be allocated efficiently for MU-MIMO under varying traffic load, UE capabilities, mobility, and TDD configurations. SRS resources are critical for channel estimation and MU-MIMO performance, but SRS capacity can become a bottleneck when many UEs require measurements. This thesis investigates when mixed periodic and aperiodic SRS operation can outperform using either mode alone. The work is closely aligned with current SRS-capacity challenges and mixed-mode development, with a focus on improving SRS utilization, MU-MIMO layers, throughput, and spectral efficiency. What You Will Do

• Evaluate how periodic and aperiodic SRS resources should be shared under different traffic loads, UE capabilities, mobility conditions, and TDD configurations.
• Study when mixed P-SRS/AP-SRS operation outperforms either mode alone.
• Investigate prioritization strategies when SRS capacity is exhausted.
• Analyze the impact on SRS utilization, RAT MU-MIMO layers, throughput, and spectral efficiency.
• Design and evaluate experiments using relevant simulation, trace, counter, or log data.

The Skills You Bring

• MSc studies in wireless communications, telecommunications, signal processing, computer engineering, or a related field.
• Solid understanding of 4G/5G NR radio concepts, TDD, uplink and downlink channels, MIMO, beamforming, precoding, CSI, channel estimation, SRS, and DMRS.
• Understanding of link adaptation and channel measurement parameters such as CQI, RI, MCS, SINR, and BLER.
• Ability to read technical specifications and internal design documents.
• Good Python skills for data processing, visualization, and experimentation.
• Excellent Java skills if Redhawk is used for simulation.
• Linux and Git experience.
• Ability to design experiments, analyze logs, and document results clearly.
• Familiarity with GenAI tools for coding and verification.