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Joint Spectrum Partition and Performance Analysis of Full-Duplex D2D Communications in Multi-Tier Wireless Networks

Yueping Wang1,*, Xuan Zhang2, Yixuan Zhang3

Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Huawei Corporation, Nanjing, China.
Huawei Research Center, Singapore.

* Corresponding Author: Yueping Wang. Email: email.

Computers, Materials & Continua 2019, 61(1), 171-184. https://doi.org/10.32604/cmc.2019.06204

Abstract

Full-duplex (FD) has been recognized as a promising technology for future 5G networks to improve the spectrum efficiency. However, the biggest practical impediments of realizing full-duplex communications are the presence of self-interference, especially in complex cellular networks. With the current development of self-interference cancellation techniques, full-duplex has been considered to be more suitable for device-to-device (D2D) and small cell communications which have small transmission range and low transmit power. In this paper, we consider the full-duplex D2D communications in multi-tier wireless networks and present an analytical model which jointly considers mode selection, resource allocation, and power control. Specifically, we consider a distance based mode selection scheme. The performance analysis of different D2D communications modes are performed based on stochastic geometry, and tractable analytical solutions are obtained. Then we investigate the optimal resource partitions between dedicated D2D mode and cellular mode. Numerical results validate the theoretical anlaysis and indicate that with appropriate proportions of users operated in different transmission modes and optimal partitioning of spectrum, the performance gain of FD-D2D communication can be achieved.

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Cite This Article

Y. Wang, X. Zhang and Y. Zhang, "Joint spectrum partition and performance analysis of full-duplex d2d communications in multi-tier wireless networks," Computers, Materials & Continua, vol. 61, no.1, pp. 171–184, 2019. https://doi.org/10.32604/cmc.2019.06204

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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