Joint Transmit and Receive Antenna Selection for Spatial Modulation Systems Using Deep Learning

Importance of the signal reliability has started to increase in today's communication technologies. One of the most important methods of increasing signal reliability for communication systems is the selection of antennas at the receiver, transmitter, or both. On the other hand, having low complexity, low processing times and high performance, deep learning (DL) based technologies have started to find a place in various fields such as communication, warehouse management, health services, image processing, and so on. In this letter, we first introduce the joint transmit and receive antenna selection (JTRAS) for spatial modulation (SM) systems, which, as far as we know, has not been studied in detail before, and second, we perform the DL algorithms for JTRAS instead of its exhaustive search.

Automated summary

The importance of signal reliability is increasing in today's communication technologies. The selection of antennas at the receiver, transmitter, or both is an important method for increasing signal reliability. Deep learning based technologies, known for their low complexity, low processing times, and high performance, have found applications in various fields including communication, warehouse management, health services, and image processing. This letter introduces a joint transmit and receive antenna selection method for spatial modulation systems and replaces the exhaustive search with deep learning algorithms.