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Millimeter-Wave Device-to-Device Networks With Heterogeneous Antenna Arrays
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Indexed by:期刊论文

First Author:Deng, Na

Correspondence Author:Deng, N (reprint author), Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China.

Co-author:Haenggi, Martin,Sun, Yi

Date of Publication:2018-09-01

Journal:IEEE TRANSACTIONS ON COMMUNICATIONS

Included Journals:SCIE、CPCI-S

Volume:66

Issue:9

Page Number:4271-4285

ISSN No.:0090-6778

Key Words:Stochastic geometry; Poisson point process; millimeter wave; D2D communication; interference distribution; success probability; rate distribution

Abstract:Millimeter-wave (mm-wave) device-to-device (D2D) communication is considered one of the most promising enabling technologies to meet the demanding requirements of future networks. Previous works on mm-wave D2D network analysis mostly considered the case that all devices were equipped with exactly the same number of antennas, whereas real networks are more complicated due to the coexistence of diverse devices. In this paper, we present a comprehensive investigation on the interference characteristics and link performance in mm-wave D2D networks where the concurrent transmission beams are varying in width. First, we establish a general and tractable framework for the target network with Nakagami fading and directional beamforming. To fully characterize the interference, we derive the mean and variance of the interference and then provide an approximation of the interference distribution by a mixture of the inverse gamma and the log-normal distributions. More importantly, the coexistence of varied beamwidths renders their interactions and thus the interference quite complicated and sensitive to the antenna pattern, highlighting the significance of adopting an accurate model for the antenna pattern. Second, to show the impact of heterogeneous antenna arrays on the link performance, we derive the signal-to-interference-plus-noise ratio and rate distributions of the typical receiver as well as their asymptotics, bounds, and approximations to get deep insights on the performance of the network.

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Gender:Female

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:信息与通信工程学院

Business Address:海山楼A420

Contact Information:lslwf@dlut.edu.cn

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