## 2 Wireless B5G Difficulties with DL-Based Mm-Wave
### DL-Based Mm-Wave
The high bandwidths of mm-wave signals make them well-suited for applications that require large amounts of data, such as video streaming, while the directional nature of mm-wave signals makes them ideal for vehicular communication and remote sensing applications [67]. * The challenges and opportunities associated with mm-wave technology. The high frequency and directional nature of mm-wave signals require new antenna designs, signal processing techniques, and RA strategies. DL techniques can be used to address these challenges and optimize the performance of mm-wave systems [13; 68; 69; 70; 71]. \begin{table}
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**Current Issues** & **Mm-Wave Solution** \\ \hline Lack of bandwidth or the need for additional bandwidth, particularly for D2D or sophisticated UAV applications, is the issue [62; 63]. & For applications like UAV or D2D communications, in particular, the high B.W. need requirements can be accommodated by the ample vacant mm-wave bandwidth. The mm-wave clocks in at less than 10 milliseconds, demonstrating very little latency. This feature allows for improved performance and resolves latency problems that are frequently associated with wireless data transmission. The wavelengths of mm-wave transmissions range from 10 mm to 1 mm, making them ideal for creating extremely small antenna designs for data transmission and wireless power. & The mm-wave clocks in at less than 10 milliseconds, demonstrating very little latency. This feature allows for improved performance and resolves latency problems that are frequently associated with wireless data transmission. The wavelengths of mm-wave transmissions range from 10 mm to 1 mm, making them ideal for creating extremely small antenna designs for data transmission and wireless power. & Applications based on mm-waves can improve end-user experience, increase the capacity of front-end links with limited bandwidth, and reduce backhaul burden in the core network due to the ample bandwidth available around 250 GHz. \\ \hline \hline \end{tabular}
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Table 2: Solutions based on mm-wave application for existing challenges [62; 63; 64; 65; 66]. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Research Challenges** & **Future Perspectives** \\ \hline Processing data in high dimensions under dynamic channel conditions [62; 63; 64]. & Create scalable DL models for high-dimensional channel estimation in real-time. \\ Accurate capture of CSI for effective beamforming [64]. & For accurate CSI reconstruction and beamforming optimization, use sophisticated DNN frameworks. \\ Intricate relationships between antenna arrays, performance measures, and channel circumstances [65]. & Develop adaptive beamforming techniques for different situations by utilizing DL. \\ Managing higher mm-wave path loss while maintaining reliable signal processing. & Combine DL with spatial data to enhance signal tracking and channel estimation. \\ Computational complexity in DL model training and activation in real-time [66]. & Optimize DL models for edge processing-appropriate, lightweight implementations. \\ \hline \hline \end{tabular}
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Table 3: Solutions based on mm-wave application for existing challenges [62; 63; 64; 65; 66].