Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks
This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specific...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Tian, Daxin [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on vehicular technology - New York, NY : IEEE, 1967, 65(2016), 6, Seite 3845-3859 |
|---|---|
| Übergeordnetes Werk: |
volume:65 ; year:2016 ; number:6 ; pages:3845-3859 |
| Links: |
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| DOI / URN: |
10.1109/TVT.2016.2567062 |
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| Katalog-ID: |
OLC1977330223 |
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| 520 | |a This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. | ||
| 650 | 4 | |a Vehicular communications | |
| 650 | 4 | |a MIMO transmissions | |
| 650 | 4 | |a cognitive radio | |
| 650 | 4 | |a Array signal processing | |
| 650 | 4 | |a MIMO | |
| 650 | 4 | |a Vehicles | |
| 650 | 4 | |a Mathematical model | |
| 650 | 4 | |a Robustness | |
| 650 | 4 | |a Interference | |
| 650 | 4 | |a Optimization | |
| 650 | 4 | |a energy efficiency | |
| 700 | 1 | |a Zhou, Jianshan |4 oth | |
| 700 | 1 | |a Sheng, Zhengguo |4 oth | |
| 700 | 1 | |a Leung, Victor C. M |4 oth | |
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10.1109/TVT.2016.2567062 doi PQ20160719 (DE-627)OLC1977330223 (DE-599)GBVOLC1977330223 (PRQ)c70b-e337ffac334528cd06599c393f52bc1d646f13b7a8f32c2771c4a935c22e62ba0 (KEY)0030991520160000065000603845robustenergyefficientmimotransmissionforcognitivev DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Tian, Daxin verfasserin aut Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency Zhou, Jianshan oth Sheng, Zhengguo oth Leung, Victor C. M oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 6, Seite 3845-3859 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:6 pages:3845-3859 http://dx.doi.org/10.1109/TVT.2016.2567062 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 6 3845-3859 |
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10.1109/TVT.2016.2567062 doi PQ20160719 (DE-627)OLC1977330223 (DE-599)GBVOLC1977330223 (PRQ)c70b-e337ffac334528cd06599c393f52bc1d646f13b7a8f32c2771c4a935c22e62ba0 (KEY)0030991520160000065000603845robustenergyefficientmimotransmissionforcognitivev DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Tian, Daxin verfasserin aut Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency Zhou, Jianshan oth Sheng, Zhengguo oth Leung, Victor C. M oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 6, Seite 3845-3859 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:6 pages:3845-3859 http://dx.doi.org/10.1109/TVT.2016.2567062 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 6 3845-3859 |
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10.1109/TVT.2016.2567062 doi PQ20160719 (DE-627)OLC1977330223 (DE-599)GBVOLC1977330223 (PRQ)c70b-e337ffac334528cd06599c393f52bc1d646f13b7a8f32c2771c4a935c22e62ba0 (KEY)0030991520160000065000603845robustenergyefficientmimotransmissionforcognitivev DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Tian, Daxin verfasserin aut Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency Zhou, Jianshan oth Sheng, Zhengguo oth Leung, Victor C. M oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 6, Seite 3845-3859 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:6 pages:3845-3859 http://dx.doi.org/10.1109/TVT.2016.2567062 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 6 3845-3859 |
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10.1109/TVT.2016.2567062 doi PQ20160719 (DE-627)OLC1977330223 (DE-599)GBVOLC1977330223 (PRQ)c70b-e337ffac334528cd06599c393f52bc1d646f13b7a8f32c2771c4a935c22e62ba0 (KEY)0030991520160000065000603845robustenergyefficientmimotransmissionforcognitivev DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Tian, Daxin verfasserin aut Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency Zhou, Jianshan oth Sheng, Zhengguo oth Leung, Victor C. M oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 6, Seite 3845-3859 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:6 pages:3845-3859 http://dx.doi.org/10.1109/TVT.2016.2567062 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 6 3845-3859 |
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10.1109/TVT.2016.2567062 doi PQ20160719 (DE-627)OLC1977330223 (DE-599)GBVOLC1977330223 (PRQ)c70b-e337ffac334528cd06599c393f52bc1d646f13b7a8f32c2771c4a935c22e62ba0 (KEY)0030991520160000065000603845robustenergyefficientmimotransmissionforcognitivev DE-627 ger DE-627 rakwb eng 620 DNB 53.70 bkl 53.74 bkl Tian, Daxin verfasserin aut Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency Zhou, Jianshan oth Sheng, Zhengguo oth Leung, Victor C. M oth Enthalten in IEEE transactions on vehicular technology New York, NY : IEEE, 1967 65(2016), 6, Seite 3845-3859 (DE-627)129358584 (DE-600)160444-2 (DE-576)014730871 0018-9545 nnns volume:65 year:2016 number:6 pages:3845-3859 http://dx.doi.org/10.1109/TVT.2016.2567062 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2061 53.70 AVZ 53.74 AVZ AR 65 2016 6 3845-3859 |
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620 DNB 53.70 bkl 53.74 bkl Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks Vehicular communications MIMO transmissions cognitive radio Array signal processing MIMO Vehicles Mathematical model Robustness Interference Optimization energy efficiency |
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ddc 620 bkl 53.70 bkl 53.74 misc Vehicular communications misc MIMO transmissions misc cognitive radio misc Array signal processing misc MIMO misc Vehicles misc Mathematical model misc Robustness misc Interference misc Optimization misc energy efficiency |
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ddc 620 bkl 53.70 bkl 53.74 misc Vehicular communications misc MIMO transmissions misc cognitive radio misc Array signal processing misc MIMO misc Vehicles misc Mathematical model misc Robustness misc Interference misc Optimization misc energy efficiency |
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ddc 620 bkl 53.70 bkl 53.74 misc Vehicular communications misc MIMO transmissions misc cognitive radio misc Array signal processing misc MIMO misc Vehicles misc Mathematical model misc Robustness misc Interference misc Optimization misc energy efficiency |
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Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks |
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Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks |
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Tian, Daxin |
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robust energy-efficient mimo transmission for cognitive vehicular networks |
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Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks |
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This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. |
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This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. |
| abstract_unstemmed |
This work investigates a robust energy-efficient solution for multiple-input-multiple-output (MIMO) transmissions in cognitive vehicular networks. Our goal is to design an optimal MIMO beamforming for secondary users (SUs), considering imperfect interference channel-state information (CSI). Specifically, we optimize the energy efficiency (EE) of SUs, given that the transmission power constraint, the robust interference power constraint, and the minimum transmission rate are satisfied. To solve the optimization problem, we first characterize the uncertainty of CSI by bounding it in a Frobenius-norm-based region and then equivalently convert the robust interference constraint to a linear matrix inequality (LMI). Furthermore, a feasible ascent direction approach is proposed to reduce the optimization problem into a sequential linearly constrained semidefinite program, which leads to a distributed iterative optimization algorithm for deriving the robust and optimal beamforming. The feasibility and convergence of the proposed algorithm is theoretically validated, and the final experimental results are also supplemented to show the strength of the proposed algorithm over some conventional schemes in terms of the achieved EE performance and robustness. |
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Robust Energy-Efficient MIMO Transmission for Cognitive Vehicular Networks |
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http://dx.doi.org/10.1109/TVT.2016.2567062 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7468546 |
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Zhou, Jianshan Sheng, Zhengguo Leung, Victor C. M |
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