Maximizing Signal to Interference Noise Ratio for Massive MIMO: A Stochastic Neurodynamic Approach
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-39764-6_15
Reference18 articles.
1. Lin, X., Xu, F., Fu, J., Wang, Y.: Resource allocation for TDD cell-free massive MIMO systems. Electronics 11(12), 1914 (2022). https://doi.org/10.3390/electronics11121914. https://www.mdpi.com/2079-9292/11/12/1914
2. Yin, H., Wang, H., Liu, Y., Gesbert, D.: Dealing with the mobility problem of massive MIMO using extended Prony’s method. In: ICC 2020–2020 IEEE International Conference on Communications (ICC), pp. 1–6 (2020). https://doi.org/10.1109/ICC40277.2020.9149225
3. Dikmen, O., Kulac, S.: Power allocation algorithms for massive MIMO system. Avrupa Bilim ve Teknoloji Dergisi (28), 444–452 (2021). https://doi.org/10.31590/ejosat.1005325
4. Salah, I., Mourad, M., Rahouma, K., Hussein, A.: Energy efficiency optimization in adaptive massive MIMO networks for 5G applications using genetic algorithm. Opt. Quant. Electron. 54, 125 (2022). https://doi.org/10.1007/s11082-021-03507-5
5. Adasme, P., Soto, I., Juan, E.S., Seguel, F., Firoozabadi, A.D.: Maximizing signal to interference noise ratio for massive MIMO: a mathematical programming approach. In: 2020 South American Colloquium on Visible Light Communications (SACVC), pp. 1–6 (2020). https://doi.org/10.1109/SACVLC50805.2020.9129889
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