Abstract
This work proposes an effective source separation technique based on a semi-blind multi-modulus approach for an embedded pilot scenario in a Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication system. A jointly hybrid cost function is developed based on the Multi-Modulus (MM) and Least Squares (LS) for a semi-blind channel estimation. A straightforward yet effective semi-blind block gradient descent optimization approach is used. In addition, a technique for optimizing the step size is introduced to improve the convergence rate of the proposed algorithm. The proposed semi-blind technique for a superimposed pilot scheme is compared to the Time-division Multiplexed pilots (i.e., block pilot arrangement) in terms of the symbol error rate and the throughput. The extensive simulation results demonstrate that the inherent ambiguity in the blind estimation is preserved, and the result shows excellent performance and bandwidth trade-offs.
| Original language | English |
|---|---|
| Title of host publication | Conference Record of the 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024 |
| Editors | Michael B. Matthews |
| Publisher | IEEE Computer Society |
| Pages | 1547-1551 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350354058 |
| DOIs | |
| State | Published - 2024 |
| Event | 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024 - Hybrid, Pacific Grove, United States Duration: 27 Oct 2024 → 30 Oct 2024 |
Publication series
| Name | Conference Record - Asilomar Conference on Signals, Systems and Computers |
|---|---|
| ISSN (Print) | 1058-6393 |
Conference
| Conference | 58th Asilomar Conference on Signals, Systems and Computers, ACSSC 2024 |
|---|---|
| Country/Territory | United States |
| City | Hybrid, Pacific Grove |
| Period | 27/10/24 → 30/10/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Least Squares (LS)
- MIMO-OFDM
- Multi-Modulus
- Semi-blind source separation
- Superimposed pilot schemes
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications
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