An adaptive subsystem based algorithm for channel equalization in a SIMO system
The principle of multiple input/output inversion theorem (MINT) has been employed for multi-channel equalization. In this work, we propose to partition a single-input multiple-output system into two subsystems. The equivalence between the deconvoluted signals of the two subsystems is termed as auto-...
Saved in:
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/84915 http://hdl.handle.net/10220/17255 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The principle of multiple input/output inversion theorem (MINT) has been employed for multi-channel equalization. In this work, we propose to partition a single-input multiple-output system into two subsystems. The equivalence between the deconvoluted signals of the two subsystems is termed as auto-relation and we subsequently exploit this relation as an additional constraint to the existing adaptive MINT algorithm. In addition, we provide analysis of the auto-relation constraint and show that this constraint confines the solution of equalization filters within a multi-dimensional space. We also explain through the use of convergence analysis why our proposed algorithm can achieve a higher rate of convergence compared to the existing MINT-based algorithms. Simulation results, using both synthetic and recorded channel impulse responses, show that our proposed auto-relation aided MINT algorithm can achieve a fast convergence compared to the existing MINT-based algorithms. |
|---|