# Research on the Performance of an End-to-End Intelligent Receiver with Reduced Transmitter Data
## 4 Simulation Result  
In this section, we will explore whether the intelligent receiver had the performance of accurate decoding when the data at the transmitter side was reduced in the communication system. For this reason, we designed two ways to reduce the data at the transmitter side, namely, data end cropping and data equal interval cropping, for multiple input multiple output MIMO systems. In the experimental setup of the communication system, we used the MIMO communication system similar to that in document [18]. At the transmitter side, the original number of binary bits was 32, first (7, 4) with Hamming coding, a modulation method using BPSK modulation, after a modulation of the signal into the STBC coding module, then after Alamouti space-time coding to form a two-way length of 56 code streams. An up sampling module was set at the receiving end, and the number of sampling points of each symbol was 8. The design of the intelligent receiver was the same as in the literature of [18], where the receiver input data was the IQ data arriving at the receiver after channel interference and the output data was the original 32-bit length binary bit data. First, we explored whether the intelligent receiver had an accurate decoding ability when reducing the data at the transmitter in the AWGN channel. In this experiment, the data after the STBC encoding was end-cropped and the data was reduced in the process shown in Figure 10a. The original transmitter sent data as a two-way code stream of length 56, and the data length of each stream was cut from the end to 2, 4, 6 and 8, respectively. There were two reasons for conducting the end data cropping experiment first. On the one hand, end cropping is the easiest way to implement data cropping. On the other hand, when the end clipped data is small (e.g., the cropped data length is two), if the intelligent  
Figure 9: Matrix multiplication to realize equal interval cutting of data. receiver can achieve accurate decoding, it will provide a theoretical basis for the later, equally-spaced data clipping, i.e., when there is a small amount of data reduction, while the depth receiver still has the ability to accurately decode. The results of the clipping experiment at the end of the transmitter data are shown in Figure 11a below. Figure 11: Data end-crop receiver performance. (**a**) Intelligent receiver performance under different cropped data in AWGN channel. (**b**) Performance of different end-crop receivers with end data removed. Figure 10: Data cutting method at the transmitting end. With the increase in clipped data at the end of the data, the decoding accuracy of the intelligent receiver decreased. When the clipped data at the end was two, it could be observed that the BER of the intelligent receiver was between the decoding BER of the deep receiver under the complete data and the decoding BER of the traditional receiver. This shows that the intelligent receiver still had a certain decoding ability when the data was reduced in a small amount, and the intelligent receiver could accurately complete the decoding through the nonlinear fitting ability of the neural network. Moreover, its decoding performance was better than the traditional decoding methods. When the end data cropping exceeded two, the decoding BER of the intelligent receiver was higher than that of the conventional receiver, which indicates that as the end cropped data increased, the missing information increased and the receiver was unable to extract features from the missing data; therefore, its decoding capability decreased. Then, the reasons for the receiver's inability to decode accurately when the end-crop data lengths were 4, 6, and 8 were investigated.