<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the development of communication technology and the general trend of interconnection and intercommunication, people’s demand for high-quality information and communication is increasing day by day. Therefore, the intensive deployment of base stations has become the development trend of the construction of a new generation of communication network. In this paper, in order to solve the urban and rural electric scenarios such as traditional transport unreachable problem, on the basis of the operator site cost at the same time, keep the quality of signal transmission, give full play to the advantages of the traditional planning concept and artificial intelligence algorithm, integrated “pieces”, “step by step optimization”, “local optimal”, “the results of reverse”, such as ideas, set up a wireless back mathematical analysis model of network topology programming problem.</p>
<p>The purpose of this paper is to reduce the cost and reduce the return path loss. Aiming at the lower cost problem, a local optimal model is constructed. First division, through the K - Means algorithm is divided into K, for each region is also based on K - Means algorithm is further split into its n tribal groups, limited each tribal group one and only one host station, recently to tribal group of perimeter centroid position of butterfly stand stand as a host, the rest of the site as a child, according to the type of tribal group of judge whether the number of sub station meet the qualification, if not satisfied, change the K value and the adjustable radius, respectively, until meet the qualification, the best solution is calculated. For the lower return path loss problem, if only the loss problem is considered, the loss result is obtained by changing the distance between the first jump and the second jump based on the model. Through the comparison of the results, the best scheme is obtained when only loss is considered.</p>
</abstract>

With the development of communication technology and the general trend of interconnection and intercommunication, people’s demand for high-quality information and communication is increasing day by day. Therefore, the intensive deployment of base stations has become the development trend of the construction of a new generation of communication network. In this paper, in order to solve the urban and rural electric scenarios such as traditional transport unreachable problem, on the basis of the operator site cost at the same time, keep the quality of signal transmission, give full play to the advantages of the traditional planning concept and artificial intelligence algorithm, integrated “pieces”, “step by step optimization”, “local optimal”, “the results of reverse”, such as ideas, set up a wireless back mathematical analysis model of network topology programming problem.
The purpose of this paper is to reduce the cost and reduce the return path loss. Aiming at the lower cost problem, a local optimal model is constructed. First division, through the K - Means algorithm is divided into K, for each region is also based on K - Means algorithm is further split into its n tribal groups, limited each tribal group one and only one host station, recently to tribal group of perimeter centroid position of butterfly stand stand as a host, the rest of the site as a child, according to the type of tribal group of judge whether the number of sub station meet the qualification, if not satisfied, change the K value and the adjustable radius, respectively, until meet the qualification, the best solution is calculated. For the lower return path loss problem, if only the loss problem is considered, the loss result is obtained by changing the distance between the first jump and the second jump based on the model. Through the comparison of the results, the best scheme is obtained when only loss is considered.

Application of Wireless Return Topology Planning Based on K-Means

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Application of Wireless Return Topology Planning Based on K-Means"}

With the development of communication technology and the general trend of interconnection and intercommunication, people’s demand for high-quality information...

First jump/second jump	Host station	child station	satellite	Average loss (dB)
20/10	222	778	28	111.79
15/8	385	610	49	109.44
12/6	588	410	74	107.30

symbols	Meaning
LOS	Line-of-sight transmission capability
ROI	Return on investment
NLOS	Non-line-of-sight transmission capability
RRN	The infinite return device of the infinite return scheme
RN	Relay station
UE	Ordinary mobile phone
PL	Path to the consumption
APL	Average path consumption
D	Site spacing
F	Transmission frequency
R	Radius of the earth
S	The distance between the spheres
αi	I point longitude
β i	I point the dimension
i	Base station identification
Xi	The host site
Yi	The child site
Zi	Satellite point
C	The overall cost
FD	The first jump distance
ND	After each jump distance
FXi	Butterfly host station
RXi	Star host station
WL	Microwave connections between host stations
WBL	Wireless return connection between host station and sub-station and between sub-stations
JS	The number of hops from a substation to a host station
Ceil	The function that rounds up

transport	cost
host station	10
child station	5
satellite	50

Radius (km)	Host station	child station	satellite	Overall cost (WUSD)
20	222	778	28	7510
25	136	858	17	6500
30	110	871	14	6155

Application of Wireless Return Topology Planning Based on K-Means

Data publikacji: 08 paź 2019

Zakres stron: 61 - 68

DOI: https://doi.org/10.21307/ijanmc-2019-048

Słowa kluczowe
Wireless Return, Base Station Deployment, K-Means Algorithm, Piecemeal Optimization

© 2019 Yang Weixia et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

NUMBER OF SITES AND AVERAGE WASTAGE

NOTATION TABLE

SHOWS THE COSTS OF VARIOUS MODES OF TRANSMISSION IN WUSD

COST COMPARISON TABLE

Application of Wireless Return Topology Planning Based on K-Means

Data publikacji: 08 paź 2019

Zakres stron: 61 - 68

DOI: https://doi.org/10.21307/ijanmc-2019-048

Słowa kluczoweWireless Return, Base Station Deployment, K-Means Algorithm, Piecemeal Optimization

© 2019 Yang Weixia et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

NUMBER OF SITES AND AVERAGE WASTAGE

NOTATION TABLE

SHOWS THE COSTS OF VARIOUS MODES OF TRANSMISSION IN WUSD

COST COMPARISON TABLE

Słowa kluczowe
Wireless Return, Base Station Deployment, K-Means Algorithm, Piecemeal Optimization