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 |
Hits:
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 |
Hits:
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 |
Hits:
Description: 对一个使用了线性时空编码的多输入多输出系统的盲信道估计-Blind Channel estimation for MIMO systems using Linear Space time codes Platform: |
Size: 7168 |
Author:水林声 |
Hits:
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 |
Hits:
Description: OFDM(Orthogonal frequency-division multiplexing)意即正交頻分複用技術對頻率偏移極為敏感,初期皆以導引信號作為偵測.
後期則著重在盲通道估測~此兩篇論文是盲通道的技術~有助於你學習更多知識
-OFDM (Orthogonal frequency-division multiplexing) means orthogonal frequency division multiplexing frequency offset pairs are extremely sensitive to begin with the initial guidance as to detect the signal. The later focus on the blind channel estimation ~ The two papers is a blind channel Technical ~ help you learn more knowledge Platform: |
Size: 815104 |
Author:Dephiroth |
Hits:
Description: It is a program for blind channel estimation for space time block codes in Multi- Input Multi Output aantennas Platform: |
Size: 7168 |
Author:bunny |
Hits:
Description: 用MATLAB写的信道辨识与盲估计的有关数据处理的源程序-MATLAB was used identification and blind channel estimation of the data processing of the source Platform: |
Size: 111616 |
Author:范麦麦 |
Hits:
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 |
Hits:
Description: MIMO-OFDM系统半盲信道估计算法的一篇transaction文章，和大家一起分享。-Semi-blind MIMO-OFDM system channel estimation algorithm for transaction an article to share with everyone. Platform: |
Size: 233472 |
Author:张健康 |
Hits:
Description: 基于MIMO-OFDM系统半盲信道估计算法的两篇经典transaction文章，和大家一起分享- Two classic transaction article based on the semi-blind channel estimation algorithm in MIMO-OFDM systems, and share with everyone Platform: |
Size: 1468416 |
Author:贾成松 |
Hits:
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
|
Hits:
Search - blind channel estimation