Name
Abstract | ||
|---|---|---|
Recently, research into autonomous driving and traffic safety has been drawing a great deal of attention. To realize autonomous driving and solve traffic safety problems, wireless access in vehicular environments (WAVE) technology has been developed, and IEEE 802.11p defines the physical (PHY) layer and medium access control (MAC) layer in the WAVE standard. However, the IEEE 802.11p frame structure, which has low pilot density, makes it difficult to predict the properties of wireless channels in a vehicular environment with high vehicle speeds; thus, the performance of the system is degraded in realistic vehicular environments. The motivation for this paper is to improve the channel estimation and tracking performance without changing the IEEE 802.11p frame structure. Therefore, we propose a channel estimation technique that can perform well over the entire SNR range of values by changing the method of channel estimation accordingly. The proposed scheme selectively uses two channel estimation schemes, each with outstanding performance for either high-SNR or low-SNR signals. To implement this, an adaptation algorithm based on a preamble is proposed. The preamble is a signal known to the transmitter-receiver, so that the receiver can obtain channel estimates without demapping errors, evaluating performance of the channel estimation schemes. Simulation results comparing the proposed method to other schemes demonstrate that the proposed scheme can selectively switch between the two schemes to improve overall performance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19132971 | SENSORS |
Keywords | Field | DocType |
IEEE 802,11p,Preamble,Adaptive Channel Estimation,Intelligent Transportation Systems,Vehicular Communications | IEEE 802.11p,Preamble,Wireless,Communication channel,Electronic engineering,Access control,PHY,Intelligent transportation system,Engineering | Journal |
Volume | Issue | ISSN |
19 | 13 | 1424-8220 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| joo young choi | 1 | 1 | 0.68 |
| Han-Shin Jo | 2 | 1205 | 75.15 |
| Cheol Mun | 3 | 292 | 27.01 |
| Jong-Gwan Yook | 4 | 326 | 41.15 |