이동통신 환경에서 합성곱 신경망 기반 최적의 송신 안테나 선택
Optimum Transmit Antenna Selection Based on Convolutional Neural Network in Mobile Communication Environment
- Resource Type
- Article
Text
- Authors
- 오정은; 조아민; 최재웅; 정의림; Jeong-Eun Oh; A-Min Jo; Jae-Woong Choi; Eui-Rim Jeong
- Source
- 차세대융합기술학회논문지, 03/31/2023, Vol. 7, Issue 3, p. 350-357
- Subject
- 안테나 다이버시티
안테나 선택
다중입출력
딥러닝
합성곱 신경망
분류
Antenna diversity
Antenna selection
MIMO
Deep learning
CNN
Classification
- Language
- 한국어(KOR)
- ISSN
- 2508-8270
This paper proposes a new technique for selecting optimal transmit antennas using convolutional neural network(CNN) in mobile communication environments. The communication system considered in this paper has multiple antennas and two-way communication is performed in a time-division duplexing(TDD) manner. The system uses all of the antennas in receiver mode but only one in transmitter mode. The input of the CNN is the signal to noise ratios(SNRs) for the past received signals. The conventional method selects the optimal antenna based on the average of the past received SNRs or the most recently received SNR. We compare the proposed method with two conventional methods through computer simulation. According to the results, by changing the mobile speed and the probability(or frequency) of receiving, the proposed CNN method has the highest accuracy in wideband signals while the conventional method using the recently received SNR has the highest accuracy in narrowband signals.