Base station deployment optimization method based on dynamic adjustment quantum genetic algorithm
In previous research on 5 G wireless networks, the optimization of base station deployment primarily relied on human expertise, simulation software, and algorithmic optimization.
Therefore, the base station coverage optimization method proposed in this paper effectively mirrors real-world scenarios, visually exposes signal blind spots, and accurately identifies instances where users cannot connect to base stations due to complex environmental factors such as high-rise obstructions or areas beyond the coverage range. Fig. 9.
Moreover, we propose a dynamically adjusted quantum genetic algorithm (DAQGA) to optimize base station layout, with coverage and construction cost as objective functions. A signal reception strength metric is introduced to evaluate the effectiveness of the optimal layout.
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With the maturity and large-scale deployment of 5G technology, the proportion of energy consumption of base stations in the smart grid is increasing, and there is an urgent …
In previous research on 5 G wireless networks, the optimization of base station deployment primarily relied on human expertise, simulation software, and algorithmic …
Recently, 5G communication base stations have steadily evolved into a key developing load in the distribution network. During the operation process, scientific dispatching …
ABSTRACT Base station location selection and network optimization are critical to improving the performance of wireless communication networks in terms of latency reduction. To this end, …
The application requirements of 5G have reached a new height, and the location of base stations is an important factor affecting the signal. Based on factors such as base station …
Abstract: Base station location selection and network optimization are critical to improving the performance of wireless communication networks in terms of latency reduction. …
Most of the current research is based on the performance of the base station (BS) itself or the operation mode of the communication operator without considering the users’ …
The coverage area of base stations has shrunk due to the rapid growth of 5G technology in China, but the quantity of base stations needed to cover the same region has …
A base station control algorithm based on Multi-Agent Proximity Policy Optimization (MAPPO) is designed. In the constructed 5G UDN model, each base station is considered as …
The rapid evolution and integration of next-generation Internet-of-things (NG-IoT) applications present new complexities for sixth-generation (6G) mobile communication …
With the large-scale deployment of 5G technology, the rationality of communication base station siting is crucial for network performance, construction costs, and operational …
Integrated access and backhaul (IAB) networks are a technology proposed in recent 3rd generation partnership project releases for 5th generation (5G)-new radio (NR) …
In communication network planning, a rational base station layout plays a crucial role in improving communication speed, ensuring service quality, and reducing investment …
Utilizing unmanned aerial vehicle (UAV) to carry 5G base stations to build emergency communication networks can flexibly provide stable and reliable wireless access in …
The developed model can facilitate the rollout of 5G technology. Due to the high propagation loss and blockage-sensitive characteristics of millimeter waves (mmWaves), …
With the advent of the 5G era, mobile users have higher requirements for network performance, and the expansion of network coverage has become an inevitable trend. …
Reference (Post et al., 2021) proposes an optimization model for base station sleep mode and user allocation under low communication traffic loads, and uses a self-organizing …
This paper proposes two models for enhancing QoS through efficient and sustainable resource allocation and optimization of base stations. The first model, a Hybrid …
The Silent Crisis in Network Management Did you know over 68% of 5G base stations operate below 60% efficiency despite consuming 90% peak energy? Communication base station AI …
We developed a mixed integer programming model to provide the optimal location of base stations at different time periods with the network''s minimum total cost (i.e., installation …
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