The field of video encoding and 5G networking is witnessing significant developments, driven by the growing demand for high-quality, real-time video streaming and the increasing capabilities of 5G networks. Researchers are exploring innovative techniques to improve video encoding efficiency, reduce latency, and enhance overall network performance. Notably, the use of GPU-based video encoders and advanced coding techniques such as HEVC and AV1 are being investigated to achieve better rate-distortion performance and lower latency. Furthermore, the deployment of 5G networks is being optimized with features like UL-MIMO, UL-256QAM, and HPUE to improve uplink throughput, spectral efficiency, and user experience.

Some noteworthy papers in this area include: The Evaluation of NVENC Split-Frame Encoding for UHD video transcoding shows that SFE can nearly double encoding throughput with a negligible RD performance penalty, making it suitable for real-time 4K and 8K encoding. The Evaluation of GPU Video Encoder for low-latency real-time 4K UHD encoding demonstrates that hardware encoders can achieve significantly lower end-to-end latency than software solutions with better RD performance. The Performance Evaluation of Uplink 256QAM on commercial 5G networks reveals that enabling UL-256QAM can lower latency when the link is fully loaded, with an average improvement of 7.97 ms in TCP latency observed across various test cases.