# A Review of Deep Learning Applications for the Next Generation of Cognitive Networks
## 2 Materials and Methods  
### Search Strategy  
The present work corresponds to a systematic search in the databases IEEE Xplore, Elsevier, and Springer databases, focused on deep learning in the context of cognitive networks.  
The words used in the search were: network, wireless, spectrum, traffic prediction, resource allocation, and deep learning. To ensure the effectiveness of the search, the words \"deep learning\" were combined with the rest of the terms. In addition, the selection criteria prioritized works published within the last 5 years or less, published in journals (but not limited), indexed in JCR (Journal Citation Reports), with at least one citation, avoiding works that were literature reviews, and clearly indicating which was the DL method used. Table 1 shows the search queries by database.  
Because many results involve these search criteria, works dedicated to spectrum use, traffic flow prediction, and resource allocation were chosen. We found a total of 1623 papers, and following the selection criteria, 14 works were selected, of which 10 were journal papers (89%), 3 were conference papers, and 1 was a book (Table 2).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Database** & \multicolumn{1}{c}{**Search Query**} & **Results** \\ \hline \multirow{7}{*}{IEEE Xplore} & (“Document Title”:network) AND (“Document Title”:“resource allocation”) AND (“Document Title”:“deep learning) & 69 \\  & (“Document Title”:wireless) AND (“Document Title”:communications) AND (“Document Title”:“deep learning”) & 32 \\  & (“Document Title”:network) AND (“Document Title”:traffic prediction) AND (“Document Title”:deep learning) & 24 \\  & (“Document Title”:network) AND (“Document Title”:“congestion control”) AND (“Document Title”:deep learning) & 6 \\  & (“Document Title”:wireless) AND (“Document Title”:spectrum) AND (“Document Title”:“deep learning”) & 5 \\ \hline \multirow{7}{*}{ScienceDirect} & TITLE (“deep learning”) AND (network) AND (“resource allocation”) & 159 \\  & TITLE (“deep learning”) AND (wireless) AND (communications) & 218 \\  & TITLE (“deep learning”) AND (wireless) AND (spectrum) & 118 \\  & TITLE (“deep learning”) AND (network) AND (“traffic prediction”) & 19 \\  & TITLE (“deep learning”) AND (network) AND (“congestion control”) & 14 \\ \hline \multirow{7}{*}{Springer Link} & TITLE = (“deep learning”) AND (wireless) AND (communications) & 620 \\  & TITLE = (“deep learning”) AND (wireless) AND (spectrum) & 152 \\  & TITLE = (“deep learning”) AND (network) AND (“resource allocation”) & 118 \\  & TITLE = (“deep learning”) AND (network) AND (“traffic prediction”) & 63 \\  & TITLE = (“deep learning”) AND (network) AND (“congestion control”) & 6 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Search strategy and queries used in each database.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Title** & **Publisher/Organizer** & **Type** & \(n\) \\ \hline IEEE Access & IEEE & Journal & 5 \\ IEEE Transactions on Green Communications and Networking & IEEE & Journal & 1 \\ IEEE Transactions on Vehicular Technology & IEEE & Journal & 1 \\ IEEE Internet of Things Journal & IEEE & Journal & 1 \\ Wireless Communications and Mobile Computing & HINDAWI & Journal & 1 \\ Ad Hoc Networks & ELSEVIER & Journal & 1 \\ Multidisciplinary Approaches to Neural Computing & Springer & Book & 1 \\ International Conference on Signal and Information Processing, Networking, And Computers & Springer & Conference & 1 \\ International Conference on Electronics, Information, and Communications & IEEE & Conference & 1 \\ International Symposium on Wireless Communication Systems & IEEE & Conference & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: List of journals, books, and conferences where the reviewed papers were published.  
All the journal articles are JCR indexed with an Impact Factor (IF) greater than 2 (min = 2.336, max = 25.249).  
The complete search strategy can be seen in Figure 2, which is based on the flow chart of the PRISMA Statement [23].