Indoor Genetic Algorithm-Based 5G Network Planning Using a Machine Learning Model for Path Loss Estimation
出版年份 2022 全文链接
标题
Indoor Genetic Algorithm-Based 5G Network Planning Using a Machine Learning Model for Path Loss Estimation
作者
关键词
-
出版物
Applied Sciences-Basel
Volume 12, Issue 8, Pages 3923
出版商
MDPI AG
发表日期
2022-04-14
DOI
10.3390/app12083923
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- The impact of 5G on the evolution of intelligent automation and industry digitization
- (2021) Mohsen Attaran Journal of Ambient Intelligence and Humanized Computing
- Use of Machine Learning for the Estimation of Down‐ and Up‐Link Field Exposure in Multi‐Source Indoor WiFi Scenarios
- (2021) Gabriella Tognola et al. BIOELECTROMAGNETICS
- A Practical Approach to Indoor Path Loss Modeling Based on Deep Learning
- (2021) Shengjie Ma et al. Journal of Computing Science and Engineering
- Genetic Algorithm for Path Loss Model Selection in Signal Strength-Based Indoor Localization
- (2021) Byeong-ho Lee et al. IEEE SENSORS JOURNAL
- Results of Large-Scale Propagation Models in Campus Corridor at 3.7 and 28 GHz
- (2021) Md Abdus Samad et al. SENSORS
- Testing a 5G Communication System: Kriging-Aided O2I Path Loss Modeling Based on 3.5 GHz Measurement Analysis
- (2021) Melissa Eugenia Diago-Mosquera et al. SENSORS
- Study and Investigation on 5G Technology: A Systematic Review
- (2021) Ramraj Dangi et al. SENSORS
- A Novel Bi-Tuning SSO Algorithm for Optimizing the Budget-Limited Sensing Coverage Problem in Wireless Sensor Networks
- (2021) Wenbo Zhu et al. Applied Sciences-Basel
- On Optimizing WiFi RSSI and Channel Assignment using Genetic Algorithm for WiFi Tuning
- (2021) Anya Apavatjrut et al. Transactions on Electrical Engineering, Electronics, and Communications
- Implementing Deep Learning Techniques in 5G IoT Networks for 3D Indoor Positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture)
- (2020) Brahim El Boudani et al. SENSORS
- A Novel Link-to-System Mapping Technique Based on Machine Learning for 5G/IoT Wireless Networks
- (2019) Eunmi Chu et al. SENSORS
- Path Loss Prediction Based on Machine Learning: Principle, Method, and Data Expansion
- (2019) Yan Zhang et al. Applied Sciences-Basel
- Multilayer Wall Correction Factors for Indoor Ray-Tracing Radio Propagation Modeling
- (2019) C. H. Teh et al. IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
- Air-to-Air Path Loss Prediction Based on Machine Learning Methods in Urban Environments
- (2018) Yan Zhang et al. WIRELESS COMMUNICATIONS & MOBILE COMPUTING
- Advanced Real-Time Indoor Tracking Based on the Viterbi Algorithm and Semantic Data
- (2015) Jens Trogh et al. International Journal of Distributed Sensor Networks
- Advanced Real-Time Indoor Tracking Based on the Viterbi Algorithm and Semantic Data
- (2015) Jens Trogh et al. International Journal of Distributed Sensor Networks
- Coverage prediction and optimization algorithms for indoor environments
- (2012) David Plets et al. EURASIP Journal on Wireless Communications and Networking
- Exposure Minimization in Indoor Wireless Networks
- (2010) George Koutitas et al. IEEE Antennas and Wireless Propagation Letters
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started