Description: 基于子空间算法的ofdm系统半盲估计，希望对信道估计的同仁有帮助！-subspace algorithm based on the semi-blind system ofdm estimate, and I hope to channel estimation colleagues help! Platform: |
Size: 1852 |
Author:wangfuli |
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Description: 基于子空间算法的ofdm系统半盲估计，希望对信道估计的同仁有帮助！-subspace algorithm based on the semi-blind system ofdm estimate, and I hope to channel estimation colleagues help! Platform: |
Size: 2048 |
Author:wangfuli |
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Description: 基于子空间的MIMO-OFDM系统的盲信道估计，可直接运行-Subspace-based MIMO-OFDM system for blind channel estimation can be directly run Platform: |
Size: 2048 |
Author:王慧 |
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Description: Subspace Projection Based Blind Channel Order
Estimation of MIMO Systems
m file for a classical channel order estimation method -Subspace Projection Based Blind Channel OrderEstimation of MIMO Systemsm file for a classical channel order estimation method Platform: |
Size: 521216 |
Author:软猫 |
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Description: subspace method for blind channel estimation
Copyright: Xiaohua(Edward) Li, Assistant Professor
Department of Electrical and Computer Engineering
State University of New York at Binghamton
http://ucesp.ws.binghamton.edu/~xli
June 2003- subspace method for blind channel estimation
Copyright: Xiaohua(Edward) Li, Assistant Professor
Department of Electrical and Computer Engineering
State University of New York at Binghamton
http://ucesp.ws.binghamton.edu/~xli
June 2003 Platform: |
Size: 2048 |
Author:cryeh |
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Description: 实现UWB满信道估计中的子空间信道估计，属于盲信道估计的一种-Full realization of UWB channel estimation of the subspace channel estimation, blind channel estimation is a Platform: |
Size: 2048 |
Author:li |
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Description: The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files.
- space_time_coding.m (perform space time coding)
- subspace_channel_estimation_STBC.m (channel estimation)
- one_shot.m (show an example)
To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window.
Reference:
[1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202 - 217-The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files.
- space_time_coding.m (perform space time coding)
- subspace_channel_estimation_STBC.m (channel estimation)
- one_shot.m (show an example)
To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window.
Reference:
[1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202- 217 Platform: |
Size: 458752 |
Author:kamini gupta |
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Description: 基于子空间的盲信道估计算法，用的是奇异值的分解Subspace-based blind channel estimation algorithm, using a singular value decomposition -Subspace-based blind channel estimation algorithm, using a singular value decomposition Platform: |
Size: 1024 |
Author:李泽敏 |
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Description: The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files.
- space_time_coding.m (perform space time coding)
- subspace_channel_estimation_STBC.m (channel estimation)
- one_shot.m (show an example)
To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window.
Reference:
[1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202 - 217-The channel estimation algorithm is based on a subspace approach. The method works only for identifiable STBCs (excluding >=1-rate STBCs). See publication [1] for more detail about the algorithm and the identifiability conditions. The zip file contains three m files.
- space_time_coding.m (perform space time coding)
- subspace_channel_estimation_STBC.m (channel estimation)
- one_shot.m (show an example)
To use these files, extract the three files in the same folder. Then, call the script one_shot in the matlab command window.
Reference:
[1] Ammar, N. Ding, Z. "Blind Channel Identifiability for Generic Linear Space-Time Block Codes" IEEE Transactions on Signal Processing Volume 55, Issue 1, Jan. 2007 Page(s):202 - 217 Platform: |
Size: 3072 |
Author:xababa |
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Description: In this paper, we investigate blind channel estimation for Multiple Input Multiple Output (MIMO) multi-carrier
CDMA (MC-CDMA) systems in the uplink scenario. An Autocorrelation Contribution Matrix (ACM) method is proposed in
comparison with the subspace approach. Using only second order
statistics, the ACM approach shows similar performance to that
of subspace based approach. The added advantage is that it eliminates the need for rank estimation and noise power calculation
as in subspace technique. In particular we incorporate blind
channel estimation with Layered Space Frequency Equalisation
(LSFE),which employs successive interference cancellation and
therefore provides significant performance improvement over the
conventional linear minimum mean square error (MMSE) based
approach. Platform: |
Size: 109568 |
Author:Casper_z
|
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Search - Subspace-Based Blind Channel Estimation