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PASS: power allocation and SIC order selection of cache-aided NOMA in vehicular networks

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Abstract

Non-orthogonal multiple access (NOMA) and caching are prominent technologies to support massive content delivery in wireless networks. By the advantage of superior data storage capability of the vehicles, a novel cache-aided NOMA paradigms has been introduced to vehicular networks for multimedia services, in which the cache utility and NOMA efficiency are both improved. However, the high mobility of vehicles causes a fast variation of channel state, which brings challenges in utilizing NOMA technology to guarantee the reliability of communication. In this context, we explore the optimization of power allocation and successive interference cancellation (SIC) ordering. Specially, we investigate the optimal Power Allocation and SIC ordering Selection (PASS) with imperfect channel estimation. To improve the quality of service and guarantee user fairness, we try to maximize the minimum achieved average outage data rate for all the vehicles under service. The PASS problem is non-convex because of the power and outage probability constraints. By Markov inequality, the probability constraint problem is firstly transformed into the non-probability problem for simplicity. Although the transformed problem is still non-convex, it is shown that the power allocation problem is quasi-concave when given the SIC ordering. Hence, we first solve the power allocation problem by the bisection method. Then, a greedy-meta schedule algorithm is proposed to determine the SIC ordering with low complexity. Numerical results show our proposed cache-aided scheme achieves a significant performance improvement.

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Notes

  1. We recognize that multi-antenna systems have been widely considered in current networks. The setting of single-antenna is to simplify the problem formulation and the derivation of the formulas in this paper. Extending the cache-aided NOMA paradigm to multi-antenna networks is an attractive topic for future research.

  2. The processing delay of SIC depends on the number of users, and a larger number of users brings a longer decoding time. Numerical results show that the processing time of the user who has the lowest decoding order in 12 users is \(3.5\times 10^{-10}\) seconds, while the user with the highest decoding order takes \(0.5\times 10^{-10}\) seconds to get its data [36]. Therefore, the number of users in a subcarrier must be strictly controlled according to service requirements, such as grouping users into several subcarriers when the number of users is large [37]. Therefore, we set the number of vehicles severed by NOMA simultaneously to 4 in our simulation.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 61731012,61801409,91638204.

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  1. Yanglong Sun and Lintao Zhang have contributed equally to this work.

Authors and Affiliations

  1. The School of Informatics, Xiamen University, Xiamen, 361005, Fujian, China

    Yanglong Sun, LinTao Zhang, Yuliang Tang & Jianxin Zhang

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  1. Yanglong Sun
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Correspondence to Yuliang Tang.

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Sun, Y., Zhang, L., Tang, Y. et al. PASS: power allocation and SIC order selection of cache-aided NOMA in vehicular networks. Wireless Netw 29, 173–187 (2023). https://doi.org/10.1007/s11276-022-03105-7

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