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Brahim Bakkas, Reda Benkhouya, Idriss Chana and Hussain Ben-Azza
Orthogonal frequency division multiplexing (OFDM) is the key technology used in high-speed communication systems. One of the major drawbacks of OFDM systems is the high peak-to-average power ratio (PAPR) of the transmitted signal. The transmitted signal ...
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Omar Daoud,Qadri Hamarsheh,Saleh Saraireh
Pág. pp. 14 - 19
This work proposes a solution to overcome the effect for one of the main drawbacks of these days? wireless systems, where Multiple-Input Multiple-Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) combinations has been used. High peak-to-ave...
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Yujie Xia and Jinwei Ji
Orthogonal frequency-division multiplexing (OFDM) is an attractive multicarrier technique for the simplicity of equalization and high data throughput. However, the transmitted OFDM signal has a very high peak-to-average power ratio (PAPR), which severely...
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Omar Daoud,Qadri Hamarsheh,Wael Al-Sawalmeh
Pág. pp. 4 - 8
This work proposes a new algorithm to enhance the performance of the speaker verification over the communication systems based Multiple-Input Multiple-Output (MIMO) - Orthogonal Frequency Division Multiplexing (OFDM) techniques. The algorithm mainly tac...
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Bo Tang, Kaiyu Qin, Changwei Chen and Yong Cao
Orthogonal frequency division multiplexing (OFDM) is a widely used technology for wireless broadband communications. However, it also suffers from some drawbacks. One of the critical limitations is the problem of high peak-to-average power ratio (PAPR), ...
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Han Wang
The filter bank multicarrier employing offset quadrature amplitude modulation (FBMC/OQAM) is a candidate transmission scheme for 5G wireless communication systems. However, it has a high peak-to-average power ratio (PAPR). Due to the nature of overlapped...
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Xuefei Ma, Waleed Raza, Zhiqiang Wu, Muhammad Bilal, Ziqi Zhou and Amir Ali
Machine learning and deep learning algorithms have proved to be a powerful tool for developing data-driven signal processing algorithms for challenging engineering problems. This paper studies the modern machine learning algorithm for modeling nonlinear ...
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