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Innovative DFT-Based Channel Modeling and Estimation for mmWave Massive MIMO | ||
| Journal of Electrical and Computer Engineering Innovations (JECEI) | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 23 تیر 1405 | ||
| نوع مقاله: Original Research Paper | ||
| شناسه دیجیتال (DOI): 10.22061/jecei.2026.12699.905 | ||
| نویسندگان | ||
| Hossein Rashidi1؛ Hossein Khaleghi* 2 | ||
| 1Malek Ashtar University of Technology | ||
| 2Malek Ashtar University of Technology, Tehran, Iran | ||
| تاریخ دریافت: 23 اسفند 1404، تاریخ بازنگری: 22 خرداد 1405، تاریخ پذیرش: 23 تیر 1405 | ||
| چکیده | ||
| Background and Objectives: Massive Multiple-Input Multiple-Output (MIMO) systems operating in the millimeter-wave (mmWave) frequency bands offer high data rates and spectral efficiency, but accurate channel modeling remains challenging due to complex propagation characteristics. Existing channel models vary widely, and a unified framework for efficient channel estimation in next-generation systems is still lacking. This study aims to develop a simplified yet accurate channel model and a corresponding channel estimation method tailored for massive MIMO mmWave systems. Methods: A novel channel model is proposed based on the Saleh–Valenzuela (S-V) model and formulated using the Discrete Fourier Transform (DFT) to capture the spatial characteristics of mmWave channels efficiently. Leveraging this model, a DFT-based channel estimation method is developed, designed to reduce computational complexity while maintaining high accuracy. The performance of the proposed approach is evaluated through numerical simulations under various large-scale antenna array configurations. Results: Simulation results demonstrate that the proposed DFT-based channel model accurately approximates mmWave propagation characteristics and achieves higher channel estimation accuracy than conventional methods. Additionally, the method significantly reduces computational complexity and processing time. As the number of antennas increases, the performance of the proposed approach converges closely to that of traditional S-V models, confirming its scalability and effectiveness for massive MIMO scenarios. Conclusion: The study presents a practical and efficient framework for channel modeling and estimation in massive MIMO mmWave systems. The proposed DFT-based model and estimation method provide a balance between accuracy and computational efficiency, offering a valuable tool for the design and optimization of next-generation wireless networks. | ||
| کلیدواژهها | ||
| mmWave Communication Massive MIMO؛ Channel Modeling؛ DFT-Based Channel Estimation | ||
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