Intelligent Optimization of PC-GFDM Transceiver

Abstract

Generalized frequency division multiplexing (GFDM) presents an outstanding performance in out-of-band, latency, and peak-to-average power ratio, Thus, promoting it to be the most contender for the fifth generation and beyond. This paper evaluates the performance of the GFDM transceiver system with polar code (PC) and interleavers based on the bit error rate (BER). The proposed system is enhanced by artificial intelligence, which is the genetic algorithm (GA) used to optimize the parameters of the pulse shaping filter (G) and the artificial neural network (ANN) used in improving method-based least square (LS) channel estimation dataset. At each step of evaluating the performance computed based on BER vs. SNR. The optimized PC-GFDM enhances over standard GFDM by 0.0649 in BER at 28 SNR.