Blind source separation algorithms for mitigating co-channel interference and noise in wireless communication systems
Blind Source Separation (BSS) algorithms have been applied with considerable success in a variety of fields. In case of communication signals, these BSS algorithms can be applied for blind beamforming and channel estimation. In this thesis, these BSS algorithms are employed to solve the co-channel i...
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| Format: | Theses and Dissertations |
| Language: | English |
| Published: |
2009
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| Online Access: | https://hdl.handle.net/10356/20693 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Blind Source Separation (BSS) algorithms have been applied with considerable success in a variety of fields. In case of communication signals, these BSS algorithms can be applied for blind beamforming and channel estimation. In this thesis, these BSS algorithms are employed to solve the co-channel interference problem in wireless communication systems. Algorithms such as Joint Approximate Diagonalization of Eigen-matrices (JADE) and Analytical Constant Modulus Algorithm (ACMA) can handle source separation in the complex domain. We propose a modified version of the JADE source separation algorithm
based on the alternating row updating of the un-mixing matrix. This proposed algorithm
is called the Alternating Row Diagonalization - Joint Approximate Diagonalization of
Eigen-matrices (ARD-JADE). Simulation results show improvement in the Bit Error Rate
(BER) and the output Signal to Interference plus Noise ratio (SINR) by application of these source separation algorithms for various SNR levels. |
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