Читать книгу Intelligent Connectivity - Abdulrahman Yarali - Страница 34

The 5G networks must present a chaotic and confusing structure in its innate formation that has not yet been anticipated by those present in the telecommunication industry. If there is no proper mode of assurance, the sheer growth that should occur horizontally across the board could result in extremely critical scenarios (Sánchez, Sánchez‐Picot, and De Rivera 2015). Moreover, the entire scenario is quite inimitably challenging, to say the least (Al‐Falahy and Alani 2017). Therefore, the AI routines applicable in the form of machine and deep learning, alongside the potential algorithms, could nevertheless prove to be extremely beneficial and could lead to the necessary innovations required across both technologies.

It is essential to consider that the MIMO possibilities are achievable, especially considering the case of what deep learning brings to the table. With the help of such a technology, it is entirely plausible that cell site distribution and leveraging associated processes will become completely possible (Katsaros and Dianati 2017). In addition to this, site maintenance and repair operations could also be managed better, especially when considering that the 5G Network case is spread quite widely. Many learning algorithms could be implemented to satisfactorily deal with the multidimensional data in 5G that will often coalesce, transform, or shift from one specific type to another (Akyildiz, Wang, and Lin 2015). Essentially speaking, the chaotic nature of 5G would be best brought under control by the effective use across its systems.

Conversely, the AI routines bring forth the recognition of a large quantity of data for them to operate in a desirable way. This is especially related to the entire case of self‐improvement, which has also been noted as an essential potential of deep learning ANN systems (Siau and Wang 2018). The 5G technology would supposedly put all concerns to rest by processing data without any possibility of delays or other limitations. Experts predict that this will ensure that the current projected increase in connectivity speed of 15–20% would almost double if AI is specifically brought and implemented through this approach (Chen and Zhao 2014). Moreover, it must not be denied what it would mean for the future of both these technologies. There should be a potential for creating even more capable and powerful systems if definite results are derived from such an arrangement.

However, there are also risk considerations. It must not be forgotten that the large amounts of data that need to be produced for the AI to work properly will require a great availability of sources (Palattella et al. 2016). Therefore, it can be assumed that there could be a critically threatening scenario for all those involved in the industry when there could be a great and constant demand for more data (Duan and Wang 2015). In the past, many software companies illegally sold the private data of users to many unscrupulous entities who remain active throughout the internet. Thus, cybersecurity is an issue that must be considered to a critical extent.