Power Allocation Schemes Based on Machine Learning for Distributed Antenna Systems
| Autor: | Ce Zhang, Xingquan Li, Chunlong He, Liu Ying, Chun Tian |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Computational complexity theory Iterative method Computer science 02 engineering and technology Machine learning computer.software_genre 01 natural sciences 0202 electrical engineering electronic engineering information engineering General Materials Science energy efficiency power allocation schemes Artificial neural network business.industry 010401 analytical chemistry General Engineering 020206 networking & telecommunications Spectral efficiency spectral efficiency 0104 chemical sciences Power (physics) Nonlinear system machine learning lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence Antenna (radio) business lcsh:TK1-9971 computer Distributed antenna systems Communication channel Efficient energy use |
| Zdroj: | IEEE Access, Vol 7, Pp 20577-20584 (2019) |
| ISSN: | 2169-3536 |
| Popis: | In recent years, a lot of power allocation algorithms have been proposed to maximize spectral efficiency (SE) and energy efficiency (EE) for the distributed antenna systems (DAS). However, the traditional iterative power allocation algorithms are difficult to be implemented in reality because of their high computational complexity. With the development of machine learning algorithms, it has been proved that the machine learning method has excellent learning ability and low computational complexity, which can approximate the traditional iterative power allocation well and be easily to be implemented in reality. In this paper, we propose a new deep neural network (DNN) model for DAS. From the perspective of machine learning, traditional iterative algorithms can be regarded as a nonlinear mapping between user channel realizations and optimal power allocation schemes. Therefore, we train the DNN to learn the nonlinear mapping between the user channel realizations and the corresponding power allocation schemes based on the traditional iterative algorithm. Then, a power allocation schemes based on DNN method is developed to maximize SE and EE for DAS. The simulation results show that the proposed scheme can not only obtain the almost similar performance as the traditional iterative algorithm, but also reduce much online computational time. |
| Databáze: | OpenAIRE |
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