Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity
In wireless communication systems, accurate channel state information plays a fundamental role in achieving optimal transmission efficiency at the base station (BS). We introduce a deep learning-based channel prediction designed to address the challenges posed by imperfect channel reciprocity in tim...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | ICT Express |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405959525000566 |
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| _version_ | 1850118607819767808 |
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| author | Heecheol Yang |
| author_facet | Heecheol Yang |
| author_sort | Heecheol Yang |
| collection | DOAJ |
| description | In wireless communication systems, accurate channel state information plays a fundamental role in achieving optimal transmission efficiency at the base station (BS). We introduce a deep learning-based channel prediction designed to address the challenges posed by imperfect channel reciprocity in time-division duplex multiple-input multiple-output systems. We propose two models that not only facilitate accurate channel prediction but also perform channel calibration that can alleviate the impact of imperfect channel reciprocity between BS and users. We evaluate the performance through the simulations in line-of-sight and non-line-of-sight scenarios, demonstrating efficacy in enhancing the accuracy of predicted future downlink channels. |
| format | Article |
| id | doaj-art-b74cc57ea7124160b96a601f32b5147a |
| institution | OA Journals |
| issn | 2405-9595 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | ICT Express |
| spelling | doaj-art-b74cc57ea7124160b96a601f32b5147a2025-08-20T02:35:50ZengElsevierICT Express2405-95952025-06-0111359059610.1016/j.icte.2025.04.011Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocityHeecheol Yang0Division of Computer Convergence, Chungnam National University, Daejeon, 34134, Republic of KoreaIn wireless communication systems, accurate channel state information plays a fundamental role in achieving optimal transmission efficiency at the base station (BS). We introduce a deep learning-based channel prediction designed to address the challenges posed by imperfect channel reciprocity in time-division duplex multiple-input multiple-output systems. We propose two models that not only facilitate accurate channel prediction but also perform channel calibration that can alleviate the impact of imperfect channel reciprocity between BS and users. We evaluate the performance through the simulations in line-of-sight and non-line-of-sight scenarios, demonstrating efficacy in enhancing the accuracy of predicted future downlink channels.http://www.sciencedirect.com/science/article/pii/S2405959525000566Channel predictionChannel calibrationChannel reciprocityLong short-term memoryTransformer |
| spellingShingle | Heecheol Yang Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity ICT Express Channel prediction Channel calibration Channel reciprocity Long short-term memory Transformer |
| title | Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity |
| title_full | Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity |
| title_fullStr | Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity |
| title_full_unstemmed | Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity |
| title_short | Deep learning-based channel prediction for TDD MIMO systems with imperfect channel reciprocity |
| title_sort | deep learning based channel prediction for tdd mimo systems with imperfect channel reciprocity |
| topic | Channel prediction Channel calibration Channel reciprocity Long short-term memory Transformer |
| url | http://www.sciencedirect.com/science/article/pii/S2405959525000566 |
| work_keys_str_mv | AT heecheolyang deeplearningbasedchannelpredictionfortddmimosystemswithimperfectchannelreciprocity |