Emulators in JINSP
Abstract: JINSP(Jiutian Intelligence Network Simulation Platform) describes a series of basic emulators and their combinations, such as the simulation of the protocol stack for dynamic users in a real environment, which is composed of user behavior simulation, base station simulation, and terminal simulation. It is applied in specific business scenarios, such as multi-target antenna optimization, compression feedback, and so on. This paper provides detailed descriptions of each emulator and its combination based on this foundation, including the implementation process of the emulator, integration with the platform, experimental results, and other aspects.
- Design of jiutian intelligent network simulation platform. arXiv preprint arXiv:2310.06858, 2023.
- Overview of deep learning-based csi feedback in massive mimo systems. IEEE Transactions on Communications, 70(12):8017–8045, 2022.
- Practical synthetic human trajectories generation based on variational point processes. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 4561–4571, 2023.
- Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114, 2013.
- Learning to simulate human mobility. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining, pages 3426–3433, 2020.
- A review of recurrent neural networks: Lstm cells and network architectures. Neural computation, 31(7):1235–1270, 2019.
- Nathaniel R Goodman. Statistical analysis based on a certain multivariate complex gaussian distribution (an introduction). The Annals of mathematical statistics, 34(1):152–177, 1963.
- Fixing a broken elbo. In International conference on machine learning, pages 159–168. PMLR, 2018.
- Spatially consistent street-by-street path loss model for 28-ghz channels in micro cell urban environments. IEEE Transactions on Wireless Communications, 16(11):7538–7550, 2017.
- Reinforcement learning-based radio resource control in 5g vehicular network. IEEE Wireless Communications Letters, 9(5):611–614, 2019.
- Narrowband internet of things (nb-iot): From physical (phy) and media access control (mac) layers perspectives. Sensors, 19(11):2613, 2019.
- An introduction to deep learning for the physical layer. IEEE Transactions on Cognitive Communications and Networking, 3(4):563–575, 2017.
- Hybrid automatic repeat request (harq) in wireless communications systems and standards: A contemporary survey. IEEE Communications Surveys & Tutorials, 23(4):2711–2752, 2021.
- Sinr, rsrp, rssi and rsrq measurements in long term evolution networks. International Journal of Wireless & Mobile Networks, 2015.
- Analysis of rsrp measurement accuracy. IEEE Communications Letters, 20(3):430–433, 2016.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.