Name
Title | ||
|---|---|---|
Hybrid Frequency Band Communication Scheme in Device to Device Based on Convolutional Neural Network |
Abstract | ||
|---|---|---|
To reduce the traffic pressure brought by dense access to the Base Station (BS) and improve the signal transmission performance in Device to Device (D2D), we propose a hybrid frequency band communication scheme based on Convolutional Neural Network (CNN). In this scheme, the receiver obtains the link information (power and arrival angle), fed back to the BS where have well-trained CNN, and CNN through the link information can classify the D2D link. After obtaining classification results, the line-of-sight (LoS) link uses millimeter wave (mmW) band for transmission, the non-line-of-sight (NLoS) link uses microwave. To verify the effectiveness of this scheme, we performed signal to interference plus noise ratio (SINR) analysis and simulations for hybrid-band and single-band. The results show that the proposed scheme can flexibly select the communication frequency band with the user and obstruction increase, and improve the SINR coverage probability, which has good application prospects. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ICAIT56197.2022.9862612 | 2022 IEEE 14th International Conference on Advanced Infocomm Technology (ICAIT) |
Keywords | DocType | ISSN |
device to device,convolutional neural network,millimeter wave | Conference | 2010-1430 |
ISBN | Citations | PageRank |
978-1-6654-7157-2 | 0 | 0.34 |
References | Authors | |
15 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Peng | 1 | 0 | 0.34 |
| Chongfu Zhang | 2 | 16 | 7.96 |
| Ying Zhang | 3 | 163 | 25.25 |
| Huan Huang | 4 | 0 | 0.34 |