Channel Estimation in MIMO TFT-OFDM Using Hybrid BESOA- CSOA Algorithms

Autor: M. Venkatramanan, M. Chinnadurai
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Tehnički Vjesnik, Vol 31, Iss 1, Pp 151-155 (2024)
Druh dokumentu: article
ISSN: 1330-3651
1848-6339
DOI: 10.17559/TV-20230502000598
Popis: In wireless communication systems, maximizing spectral efficiency and enhancing link reliability are key objectives. One effective solution is the combination of Orthogonal Frequency Division Multiplexing (OFDM) and Multiple-Input Multiple-Output (MIMO) techniques. OFDM divides the frequency band into non-overlapping sub-bands, enabling parallel data transmission. This helps overcome the limitations of traditional wireless communication systems with high-rate input data streams. MIMO-OFDM has emerged as a promising technology for achieving high data rates and robustness in wireless communications by supporting multiple inputs and outputs. However, optimizing both spectral efficiency and performance in rapidly fading channels can be challenging. To address these issues, we propose Time Frequency Training Orthogonal Frequency Division Multiplexing (TFT-OFDM). This approach utilizes group pilots for spectrum efficiency and shared channel estimates to maintain system performance stability. Channel estimation plays a critical role in TFT-OFDM, and both Least Square (LS) and Minimum Mean Square Error (MMSE) methods are considered. LS estimation has a simple approach but lower performance, while MMSE significantly reduces mean square error at the cost of computational complexity. To estimate the channel in TFT-OFDM, joint time and frequency channel estimation techniques are employed. This involves using sophisticated algorithms to optimize parameters such as maximum or minimum function values in the solution space. The intelligent algorithms, specifically the Bald Eagle Search Optimization (BESOA) technique and the Cat Swarm Optimization Algorithm (CSOA), are utilized to estimate the channel efficiently in spectrally efficient MIMO-OFDM wireless networks. Performance improvement is observed with the intelligent algorithms. For instance, at a signal-to-noise ratio (SNR) of 15 dB, the proposed BESOA method achieves a Bit Error Rate (BER) of 10-6, while TFT-OFDM with group pilots achieves a BER of 10-3, and conventional CP-OFDM yields a BER of 10-2. Furthermore, the CSOA method outperforms the Firefly Algorithm in terms of BER performance.
Databáze: Directory of Open Access Journals
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