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5G Green Network

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Advances in Computing, Informatics, Networking and Cybersecurity

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 289))

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Abstract

Compared with conventional regular hexagonal cellular models, random cellular network models resemble real cellular networks much more closely. However, most studies of random cellular networks are based on the Poisson point process (PPP) and do not take into account the fact that adjacent base stations (BSs) should be separated with a minimum distance to avoid strong interference among each other BSs. Moreover, the user distribution in ultra-dense networks (UDNs) plays a crucial role in affecting the performance of UDNs due to the essential coupling between the traffic and the service provided by the networks. Existing studies are mostly based on the assumption that users are uniformly distributed in space. The non-uniform user distribution has not been widely considered despite that it is much closer to the real scenario. This chapter proposes a multi-user multi-antenna random cellular network model with the aforementioned minimum distance constraint for adjacent BSs, based on the hardcore point process (HCPP). A spectrum efficiency model and an energy efficiency model are presented based on the random cellular network model, and the maximum achievable energy efficiency of the considered multi-user multi-antenna HCPP random cellular networks is investigated. Moreover, a radiation and absorbing model (R&A model) is first adopted to analyze the impact of the nonuniformly distributed users on the performance of 5G UDNs. Based on the R&A model and queueing network theory, the stationary user density in each hot area is investigated. Simulation results demonstrate that the energy efficiency of conventional PPP cellular networks is underestimated when the minimum distance between adjacent BSs is ignored. Furthermore, the simulation results indicate that non-uniform user distribution has a significant impact on the performance of UDNs, compared with the uniformly distributed assumption.

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Authors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    X. Ge, J. Yang & J. Ye

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  1. X. Ge
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  2. J. Yang
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  3. J. Ye
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Correspondence to X. Ge .

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Editors and Affiliations

  1. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Petros Nicopolitidis

  2. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India

    Sudip Misra

  3. Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada

    Laurence T. Yang

  4. Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA

    Bernard Zeigler

  5. Dalian University of Technology, Dalian, China

    Zhaolng Ning

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Ge, X., Yang, J., Ye, J. (2022). 5G Green Network. In: Nicopolitidis, P., Misra, S., Yang, L.T., Zeigler, B., Ning, Z. (eds) Advances in Computing, Informatics, Networking and Cybersecurity. Lecture Notes in Networks and Systems, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-030-87049-2_13

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