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2 Journal of Telecommunications and Information Technology

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Improving Performance of MC-CDMA Systems Using UTTCM Channel Coding

Bendjillali Ridha Ilyas, Bendelhoum Mohammed Sofiane, Abderraouf Elarbi, Lahcene Mohamed

Journal of Telecommunications and Information Technology

2024

nr 2

58--65

Over the past decade, personal communications have witnessed exponential growth, fueled by the increasing number of connected users and the diversity of transmitted data types. This expansion necessitates a boost in the transmission systems' capacity to accommodate higher user numbers and data rates, simultaneously striving to optimize cost and complexity. Consequently, future communication systems are pivoting towards multi-carrier spread spectrum techniques (MC-CDMA), capitalizing on the robustness of OFDM multi-carrier transmissions against multipath propagation and leveraging the flexibility of the code division multiple access (CDMA) technique. \\This study addresses data transmission quality-related concerns within an MC-CDMA system by implementing UTTCM error correction codes. These codes aim to enhance channel spectrum efficiency and mitigate error probability. Simulation results demonstrate that the proposed transmission scheme offers significant improvements in terms of bit error rate and signal-to-noise ratio, while maximizing the bandwidth shared among users. Additionally, the incorporation of such equalization techniques as zero forcing (ZF) and minimum mean square error (MMSE), ensures extensive compensation for the channel selectivity effect

Deep Learning-Powered Beamforming for 5G Massive MIMO Systems

Bendjillali Ridha Ilyas, Bendelhoum Mohammed Sofiane, Tadjeddine Ali Abderrazak, Kamline Miloud

Journal of Telecommunications and Information Technology

2023

nr 4

38--45

In this study, a ResNeSt-based deep learning approach to beamforming for 5G massive multiple-input multipleoutput (MIMO) systems is presented. The ResNeSt-based deep learning method is harnessed to simplify and optimize the beamforming process, consequently improving performance and efficiency of 5G and beyond communication networks. A study of beamforming capabilities has revealed potential to maximize channel capacity while minimizing interference, thus eliminating inherent limitations of the traditional methods. The proposed model shows superior adaptability to dynamic channel conditions and outperforms traditional techniques across various interference scenarios.