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BER Performance Evaluation of Downlink MUSA over Rayleigh Fading Channel

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Abstract

Downlink multi-user shared access (MUSA) is a non-orthogonal multiple access scheme (NOMA) based on the traditional power domain superposition and uses a mirror constellation to optimize the modulated symbol mapping of the paired users. In this paper, bit error ratio (BER) performance of MUSA with successive interference cancellation (SIC) is investigated in a cellular downlink scenario over Rayleigh fading channel. Firstly, we elaborate downlink MUSA system based on NOMA and spreading sequences in detail. Then, we compare the BER performance of MUSA with pure NOMA under different power allocation schemes. On this basis, we further study the system average BER performance in downlink MUSA and NOMA with respect to the power difference of the users, respectively. In addition, BER performance of MUSA with different spreading sequences is evaluated. Finally, the simulation results show that MUSA with appropriate spreading sequences is able to obtain better BER performance than NOMA under the same simulation conditions, and a reasonable power allocation is the key to improve BER performance of MUSA and NOMA.

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Acknowledgement

This work is supported in part by National Natural Science Foundation of China (No. 61671184, No. 61401120, No. 61371100) and National Science and Technology Major Project of China (No. 2015ZX03001041).

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Correspondence to Gang Wang .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Xu, Y., Wang, G., Zheng, L., Liu, R., Zhao, D. (2018). BER Performance Evaluation of Downlink MUSA over Rayleigh Fading Channel. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-73564-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-73564-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73563-4

  • Online ISBN: 978-3-319-73564-1

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