In order to integrate AI algorithms, e.g. in the form of neural networks, into wireless communications systems, it is necessary to drastically reduce their resource consumption with regard to an embedded implementation. This begins with the selection of a suitable model architecture and often involves well-known optimization methods such as quantization and pruning.
