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Design of precoder for a MIMO–NOMA system using Gaussian mixture modelling

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Abstract

Multi-Input Multi-Output system (MIMO) is a wireless technology that employs transmitters and receivers for simultaneously transferring more amount of data. And Non-Orthogonal Multiple Access (NOMA) is a new technology that accommodates multiple users in the same spectrum to ensure efficient spectral usage. A combination of MIMO-NOMO systems meets the data demands of more users, while ensuring spectral efficiencies. This paper presents a new precoding algorithm using the Gaussian Mixture Modelling (GMM), which is a type of Machine Learning (ML) algorithm used for Clustering, for the MIMO–NOMA systems. Clustering refers to the grouping of data points into clusters. The use of optimal precoding methods would help eliminate inter–cluster interferences. The suggested precoding approach supports multi-layer transmission in multi-antenna wireless communications, incorporating the idea of GMM in a Multiple antenna system at both the transmitting and receiving ends along with a special case of its multiple access methodology being non-Orthogonal. Hence, the resultant MIMO–NOMA system would result in better spectral efficiency and energy efficiency. The simulation results prove this.

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References

  • Al-Imari, M., Xiao, P., Imran, M.A., and Tafazolli, R.: Uplink nonorthogonal multiple access for 5G wireless networks. In: Proceedings 11th International Symposium on Wireless Communications Systems (ISWCS), pp. 781–785, (2014)

  • Benjebbour, A., Li, A., Saito, Y., Kishiyama, Y., Harada, A., Nakamura, T.: System-level performance of downlink noma for future LTE enhancements. In: IEEE globecom workshops, pp. 66–70 (2013)

  • Choi, J.: Non-orthogonal multiple access in downlink coordinated two-point systems. IEEE Commun. Letters 18(2), 313–316 (2014)

    Article  MathSciNet  Google Scholar 

  • Dai, L., Wang, B., Yuan, Y., Han, S., Chih-Lin, I., Wang, Z.: Non-orthogonal multiple access for 5G: solutions challenges opportunities and future research trends. IEEE Commun. Mag. 53(9), 74–81 (2015)

    Article  Google Scholar 

  • Ding, Z., Yang, Z., Fan, P., Poor, H.V.: On the performance of non-orthogonal multiple access in 5G systems with randomly deployed users. IEEE Signal Process. Lett. 21(12), 1501–1505 (2014)

    Article  ADS  Google Scholar 

  • Ding, Z., Schober, R., Poor, H.V.: A general MIMO framework for NOMA downlink and uplink transmission based on signal alignment. IEEE Trans. Wirel. Commun. 15(6), 4438–4454 (2016)

    Article  Google Scholar 

  • Ding, Z., Lei, X., Karagiannidis, G.K.: A survey on non-orthogonal multiple access for 5G networks: research challenges and future trends. IEEE J. Select. Areas Commun. 35(10), 2181–2195 (2017)

    Article  Google Scholar 

  • Ding, Z., Fan P., Poor, H. V.: Impact of user pairing on 5G non-orthogonal multiple access. IEEE Trans. Vehicular Technology (submitted) Available on-line at arXiv:1412.2799.

  • Ding, Z., Adachi, F., Poor, H.V.: The application of MIMO to nonorthogonal multiple access, IEEE Trans. Wireless Commun. (submitted) Available on-line at arXiv:1503.05367.

  • Jain, M., Soni, S., Sharma N., Rawal, D.: Performance Analysis at near and far users of a NOMA System Over Fading Channels. In: 2019 IEEE 16th India Council International Conference (INDICON), pp. 1-4 IEEE, (2019)

  • Larsson, E.G., Edfors, O., Tufvesson, F., Marzetta, T.L.: Massive MIMO for next-generation wireless systems. IEEE Commun. Mag. 52(2), 186–195 (2014)

    Article  Google Scholar 

  • Liu, Y., Pan, G., Zhang, H., Song, M.: On the capacity comparison between MIMO–NOMA and MIMO-OMA. IEEE Access 4, 2123–2129 (2016)

    Article  Google Scholar 

  • Liu, Y., Pan, G., Zhang, H., Song, M.: On the capacity comparision between MIMO–NOMA and MIMO-OMA. IEEE 4, 2123–2129 (2016)

    Google Scholar 

  • Wang, B., Wang, K., Zhaohua, L., Xie, T., Quan, J.: Comparison study of non-orthogonal multiple access schemes for 5G. IEEE (2015). https://doi.org/10.1109/BMSB.2015.7177186

    Article  Google Scholar 

  • Wang, H., Zhang, R., Song, R., Leung, S.-H.: A novel power minimization precoding scheme for MIMO–NOMA uplink systems. IEEE Commun. Lett. 22, 1106–1109 (2018)

    Article  Google Scholar 

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Markkandan, S., Aggarwal, K., Ashok, K. et al. Design of precoder for a MIMO–NOMA system using Gaussian mixture modelling. Opt Quant Electron 56, 60 (2024). https://doi.org/10.1007/s11082-023-05655-2

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