<p>All the devices are interconnected each other in digital form, for different applications the input data is encoded for error correcting and detecting purpose. The paper describes the transmission of QAM signals with two level encoded stages, i.e. convolutional and hamming coded GFDM system with 256-point IFFT at transmitter and FFT at the receiver using LABVIEW software. GFDM is a non-orthogonal, digital multicarrier transmission scheme which digitally implements the classical filter bank approach. GFDM transmits a block of frame composed by M time slots with K subcarriers. The higher order QAM is used because of transmitting more data but is less reliable when compared to lower order QAM. Based on GFDM specifications for the IEEE 802.11, latest 5G physical layer standards, the coding is provided by ½ rate encoder at the input side, and Maximum Likelihood decoder at the receiver side is used. The standard convolution code (7, [171, 133]), is used as encoder for the GFDM system. The GFDM complex values are displayed in the front panel, along with FFT and power spectrum is plotted for GFDM signal. The array of input bits and output bits are shown with green colour LED’s. The van de Beek algorithm is used at the receiver for maximum likelihood detection acts as convolutional decoder of GFDM signal. Next the signal is subjected to remove cyclic prefix and zero padding and applied to channel estimation algorithm. The un-equalized data and equalized data graph is shown in the front panel, before and after channel estimation VI. With BER VI available in the LABVIEW the data is normalized and its response is plotted with respect to SNR. BER values for different levels of encoders have shown in table for SNR values. This paper concludes the 32.91% improvement in BER for two levels of concatenated codes.Thus the GFDM signal outperforms the OFDM signal interms of BER for series levels of coding using labVIEW software.</p>
Iterative estimation of undesired signal power for superposed multicarrier transmission with channel estimation error
