Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA
In order to further improve the vehicle-to-everything (V2X) communication performance of the Internet of vehicles, a basis expansion model (BEM) was adopted and suitable for high-speed mobile scenarios to transform the channel estimation into a sparse signal reconstruction.Furthermore, it was proved...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-04-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021081/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539311626878976 |
|---|---|
| author | Yong LIAO Zhirong CAI |
| author_facet | Yong LIAO Zhirong CAI |
| author_sort | Yong LIAO |
| collection | DOAJ |
| description | In order to further improve the vehicle-to-everything (V2X) communication performance of the Internet of vehicles, a basis expansion model (BEM) was adopted and suitable for high-speed mobile scenarios to transform the channel estimation into a sparse signal reconstruction.Furthermore, it was proved that the BEM coefficients were sparse, and an improved regularized orthogonal matching pursuit (iROMP) channel estimation algorithm based on BEM (BEM-iROMP) was proposed.BEM coefficients were acquired by the iROMP, and finally the feedback results were iterated to achieve the optimal channel estimation.Simulation results show that in comparison with the least square (LS), linear minimum mean squared error (LMMSE), and BEM-LS channel estimation algorithms, the proposed algorithm can effectively improve the normalized mean square error (NMSE) and bit error rate (BER) performance. |
| format | Article |
| id | doaj-art-cf51a0f287de48c48cdfe42c1ffea7e9 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-04-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-cf51a0f287de48c48cdfe42c1ffea7e92025-01-14T07:22:02ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-04-014217718459741656Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMAYong LIAOZhirong CAIIn order to further improve the vehicle-to-everything (V2X) communication performance of the Internet of vehicles, a basis expansion model (BEM) was adopted and suitable for high-speed mobile scenarios to transform the channel estimation into a sparse signal reconstruction.Furthermore, it was proved that the BEM coefficients were sparse, and an improved regularized orthogonal matching pursuit (iROMP) channel estimation algorithm based on BEM (BEM-iROMP) was proposed.BEM coefficients were acquired by the iROMP, and finally the feedback results were iterated to achieve the optimal channel estimation.Simulation results show that in comparison with the least square (LS), linear minimum mean squared error (LMMSE), and BEM-LS channel estimation algorithms, the proposed algorithm can effectively improve the normalized mean square error (NMSE) and bit error rate (BER) performance.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021081/channel estimationvehicle-to-everythinghigh-speed mobilitycompressed sensingbasis expansion modelregularized orthogonal matching pursuitSC-FDMA |
| spellingShingle | Yong LIAO Zhirong CAI Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA Tongxin xuebao channel estimation vehicle-to-everything high-speed mobility compressed sensing basis expansion model regularized orthogonal matching pursuit SC-FDMA |
| title | Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA |
| title_full | Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA |
| title_fullStr | Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA |
| title_full_unstemmed | Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA |
| title_short | Basis expansion model-based improved regularized orthogonal matching pursuit channel estimation for V2X fast time-varying SC-FDMA |
| title_sort | basis expansion model based improved regularized orthogonal matching pursuit channel estimation for v2x fast time varying sc fdma |
| topic | channel estimation vehicle-to-everything high-speed mobility compressed sensing basis expansion model regularized orthogonal matching pursuit SC-FDMA |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021081/ |
| work_keys_str_mv | AT yongliao basisexpansionmodelbasedimprovedregularizedorthogonalmatchingpursuitchannelestimationforv2xfasttimevaryingscfdma AT zhirongcai basisexpansionmodelbasedimprovedregularizedorthogonalmatchingpursuitchannelestimationforv2xfasttimevaryingscfdma |