Blind co-channel interference cancellation using fast Fourier convolutions
- Author
- Mostafa Naseri (UGent) , Eli De Poorter (UGent) , Ingrid Moerman (UGent) , H. Vincent Poor and Adnan Shahid (UGent)
- Organization
- Abstract
- Addressing long-range dependencies in blind co-channel interference waveforms typically requires convolutional networks with large kernels or significant depth, which are resource-intensive. This paper presents a streamlined UNet architecture integrated with fast Fourier convolution blocks and a long short-term memory in the bottleneck, designed to efficiently capture these dependencies. By leveraging the Fourier domain for global feature processing, our architecture reduces the model's complexity without compromising performance. Compared to the leading benchmark model (a deep UNet), our approach yields a 26.5% improvement in mean square error, while reducing multiply-accumulate operations and the number of model parameters by 76.8% and 76.3% respectively, demonstrating a significant enhancement in both accuracy and efficiency for interference cancellation in constrained computational environments.
- Keywords
- Fast Fourier Convolution (FFC), co-channel interference, interference cancellation, UNet, long short-term memory (LSTM)
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JGX8ERBWDVZF8RHSXTBQNDDG
- MLA
- Naseri, Mostafa, et al. “Blind Co-Channel Interference Cancellation Using Fast Fourier Convolutions.” 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING, IEEE, 2024, doi:10.1109/VTC2024-SPRING62846.2024.10683131.
- APA
- Naseri, M., De Poorter, E., Moerman, I., Poor, H. V., & Shahid, A. (2024). Blind co-channel interference cancellation using fast Fourier convolutions. 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING. Presented at the IEEE 99th Vehicular Technology Conference (VTC-Spring), Singapore, Singapore. https://doi.org/10.1109/VTC2024-SPRING62846.2024.10683131
- Chicago author-date
- Naseri, Mostafa, Eli De Poorter, Ingrid Moerman, H. Vincent Poor, and Adnan Shahid. 2024. “Blind Co-Channel Interference Cancellation Using Fast Fourier Convolutions.” In 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING. IEEE. https://doi.org/10.1109/VTC2024-SPRING62846.2024.10683131.
- Chicago author-date (all authors)
- Naseri, Mostafa, Eli De Poorter, Ingrid Moerman, H. Vincent Poor, and Adnan Shahid. 2024. “Blind Co-Channel Interference Cancellation Using Fast Fourier Convolutions.” In 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING. IEEE. doi:10.1109/VTC2024-SPRING62846.2024.10683131.
- Vancouver
- 1.Naseri M, De Poorter E, Moerman I, Poor HV, Shahid A. Blind co-channel interference cancellation using fast Fourier convolutions. In: 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING. IEEE; 2024.
- IEEE
- [1]M. Naseri, E. De Poorter, I. Moerman, H. V. Poor, and A. Shahid, “Blind co-channel interference cancellation using fast Fourier convolutions,” in 2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING, Singapore, Singapore, 2024.
@inproceedings{01JGX8ERBWDVZF8RHSXTBQNDDG,
abstract = {{Addressing long-range dependencies in blind co-channel interference waveforms typically requires convolutional networks with large kernels or significant depth, which are resource-intensive. This paper presents a streamlined UNet architecture integrated with fast Fourier convolution blocks and a long short-term memory in the bottleneck, designed to efficiently capture these dependencies. By leveraging the Fourier domain for global feature processing, our architecture reduces the model's complexity without compromising performance. Compared to the leading benchmark model (a deep UNet), our approach yields a 26.5% improvement in mean square error, while reducing multiply-accumulate operations and the number of model parameters by 76.8% and 76.3% respectively, demonstrating a significant enhancement in both accuracy and efficiency for interference cancellation in constrained computational environments.}},
author = {{Naseri, Mostafa and De Poorter, Eli and Moerman, Ingrid and Poor, H. Vincent and Shahid, Adnan}},
booktitle = {{2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING}},
isbn = {{9798350387421}},
issn = {{1090-3038}},
keywords = {{Fast Fourier Convolution (FFC),co-channel interference,interference cancellation,UNet,long short-term memory (LSTM)}},
language = {{eng}},
location = {{Singapore, Singapore}},
pages = {{2}},
publisher = {{IEEE}},
title = {{Blind co-channel interference cancellation using fast Fourier convolutions}},
url = {{http://doi.org/10.1109/VTC2024-SPRING62846.2024.10683131}},
year = {{2024}},
}
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