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UAV-MIMO Ricean fading通道的新确定性和随机模拟模型
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本文主要探讨了在实际模拟和评估无人航空器(UAV)多输入多输出(MIMO)瑞利衰落信道性能时,开发精确的UAV-MIMO通道模拟模型的重要性,尤其是在非均匀散射的现实场景中。研究者针对这一需求,提出了基于两圆柱体参考模型的新确定性和随机性模拟方法。 两圆柱体模型被用来描述散射体的分布,这有助于更准确地反映非对称的无线环境。在确定性模拟模型部分,作者构建了一个理论框架,通过精确计算来预测信道特性,如信道容量、误码率等关键性能指标。这种模型的优点在于其结果具有确定性,可以提供直观且可预测的仿真结果,但可能在处理复杂环境变化时缺乏随机性。 而随机性模拟模型则采用了统计方法,通过概率分布函数来模拟实际信道行为。这种方法能够更好地捕捉到散射环境中的不确定性,从而得到更接近真实情况的结果。尽管随机性模型的计算复杂度可能会稍高,但其在性能预测上的优势使得它在需要高精度预测的应用中更具吸引力。 通过分析和数值结果的对比,论文展示了两种模型都能有效地逼近参考模型的统计特性。然而,随机性模拟模型在保持与确定性模型相近计算复杂度的同时,其性能表现更优。因此,对于需要考虑真实散射效应且对仿真效率有较高要求的UAV-MIMO系统设计,随机性模拟模型可能是更为合适的选择。 关键词包括:UAV-MIMO信道、两圆柱体模型、确定性模拟模型、随机性模拟模型以及信道的统计特性。这项研究不仅提升了UAV-MIMO通信系统的仿真技术,也为未来无线通信领域,特别是在无人机通信中的性能优化和系统设计提供了有价值的参考依据。
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Journal of Communications and Information Networks, Vol.3, No.4, Dec. 2018
DOI: 10.1007/s41650-018-0033-2 Research paper
New Deterministic and Stochastic Simulation
Models for UAV-MIMO Ricean Fading Channels
Xi Zhang, Xiang Cheng
Abstract—For the practical simulation and perfor-
mance evaluation of unmanned aerial vehicle (UAV)
multiple-input multiple-output (MIMO) Ricean fading
channels, it is desirable to develop accurate UAV-MIMO
channel simulation models for more realistic scenarios
of non-isotropic scattering. In this study, using a two-
cylinder reference model to describe the distribution of
scatterers, we propose new deterministic and stochastic
simulation models. Analytical and numerical results
indicate that both simulation models provide good ap-
proximations to the desired statistical properties of the
reference model, and the stochastic simulation model
results in a better performance under comparable com-
putational complexity.
Keywords—UAV-MIMO channel, two-cylinder model,
deterministic simulation model, stochastic simulation
model, statistical properties
I. INTRODUCTION
R
ecently, unmanned aerial vehicle (UAV) communica-
tions have received particular attention owing to sev-
eral new applications, such as extending wireless coverage
and enabling communication relay
[1,2]
. Compared with terres-
trial networks, UAV systems can be used in new propagation
environments. For example, the propagation environment of
UAV communications is the first environment that fully con-
sists of both horizontal and vertical domains in a real three-
dimensional (3D) environment, where UAVs can move freely
in 3D space and near obstacles with relatively high veloci-
ties. Moreover, the height of the UAV compared with the
Manuscript received Sept. 13, 2018; revised Oct. 29, 2018; ac-
cepted Nov. 28, 2018. This work was in part supported by the Major
Project from Beijing Municipal Science and Technology Commission (No.
Z181100003218007), the National Science and Technology Major Project
(No. 2018ZX03001031), and the National Natural Science Foundation of
China (Nos. 61622101 and 61571020). The associate editor coordinating the
review of this paper and approving it for publication was L. Bai.
X. Zhang, X. Cheng. State Key Laboratory of Advanced Optical Com-
munication Systems and Networks, School of Electronics Engineering and
Computer Science, Peking University, Beijing 100871, China (e-mail: zhang-
xi@pku.edu.cn; xiangcheng@pku.edu.cn).
ground station (GS) is not negligible. Therefore, the cor-
responding channel characteristics of UAV systems are dif-
ferent from those in cellular and vehicular communications,
and traditional channel models for terrestrial networks cannot
be used directly for UAV communications channel modeling.
Moreover, multiple-input multiple-output (MIMO) technolo-
gies, where multiple antennas are deployed at both the UAV
and GS, have been widely adopted in advanced UAV systems.
Therefore, the development of UAV-MIMO channel models
is desirable for the design and performance analysis of UAV-
aided systems for non-isotropic scattering environments.
Currently, some research groups have conducted channel
measurements and developed modeling approaches to char-
acterize UAV channels. UAV channel models provided in
literature can be classified into deterministic models
[3,4]
and
stochastic models; the latter can be further divided into non-
geometrical stochastic models (NGSMs) (also known as para-
metric models) and geometry-based stochastic models (GB-
SMs). NGSMs perform random modeling purely based on pa-
rameters such as delay spread and Doppler spread without as-
suming any specific geometry
[5,6]
. Therefore, this method not
only results in higher complexity but also fails to offer a gen-
eralized framework for different scenarios. Unlike NGSMs,
GBSMs assume random scatterers and characterize the wire-
less channel by utilizing simplified ray-tracing rules
[7]
. Such
a model can be applied easily to different scenarios by chang-
ing the distribution of scatterers
[8]
. GBSMs have been widely
used in the mathematical modeling and characteristics anal-
ysis of UAV wireless channels
[9-15]
owing to their generality
and low complexity.
However, these aforementioned GBSMs belong to the so-
called reference models because they assume an infinite num-
ber of effective scatterers, which cannot be implemented in
practice. This will increase the computational complexity sig-
nificantly, and therefore restrict the applications to practical
simulation and performance evaluation. To handle the draw-
backs of the reference models, corresponding simulation mod-
els with comparatively low complexity and high accuracy are
required for non-isotropic scattering UAV-MIMO Ricean fad-
ing channels. To the best of the authors’ knowledge, only
Ref. [16] has developed simulation models based on a 3D one-
cylinder GBSM for UAV channels; however, it only focused
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