期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Channel Estimation for One-Bit Massive MIMO Based on Improved CGAN 被引量:2
1
作者 Yongli An Jinking Yue +1 位作者 Lei Chen Zhanlin Ji 《Journal of Communications and Information Networks》 EI CSCD 2022年第2期214-220,共7页
In the one-bit massive multiple-input multiple-output(MIMO)channel scenario,the accurate channel estimation becomes more difficult because the signals received by the low-resolution analog-to-digital converters(ADC)ar... In the one-bit massive multiple-input multiple-output(MIMO)channel scenario,the accurate channel estimation becomes more difficult because the signals received by the low-resolution analog-to-digital converters(ADC)are quantized and affected by channel noise.Therefore,a one-bit massive MIMO channel estimation method is proposed in this paper.The channel matrix is regarded as a two-dimensional image.In order to enhance the significance of noise features in the image and remove them,the channel attention mechanism is introduced into the conditional generative adversarial network(CGAN)to generate channel images,and im-prove the loss function.The simulation results show that the improved network can use a smaller number of pilots to obtain better channel estimation results.Under the same number of pilots and signal-to-noise ratio(SNR),the channel estimation accuracy can be improved by about 7.5 dB,and can adapt to the scenarios with more antennas. 展开更多
关键词 channel estimation MASSIVE MIMO condi-tional GENERATIVE adversarial network ATTENTION mecha-nism DENOISING
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部