Offset method for distortion of OFDM system: parabolic model
In this paper, by using the parabolic model, the distortion parameters are estimated according to the frequency domain pilot signals in the OFDM system, thereby recovering the distortion signal and performing distortion cancellation. The simulation results show that compared with the traditional method, using the new method proposed in this paper, there is about 2dB performance gain at high SNR. 1 system model The transmitter of the OFDM system is shown in Figure 1. The transmitter first maps the binary source to a complex point on the fixed constellation and converts it into a parallel data stream. The number of parallel data per OFDM symbol is determined by the number of subcarriers in the system. Then, a pilot signal whose position and size are predetermined is inserted into the designated pilot position. The information transmitted by these pilot signals is known to the receiver and can therefore be used to estimate the effects of the external environment on the transmitted signal, such as time-varying channel effects, which are used herein to estimate the distortion signal. The data stream is converted into a time domain signal by performing an IFFT operation, and finally converted into a serial data stream and passed through a digital-to-analog converter and a power amplifier, and the analog signal is transmitted, as shown in FIG. Figure 1: OFDM system transmitter block diagram For hard limiting systems, signal distortion can be modeled as a parabola with random parameters, as shown in Figure 2. Figure 2: Parabolic model of signal distortion 2 method of offset cancellation production For the cancellation of the distorted signal, first use the known information to estimate the distortion we get, and then have different effects on the offset distortion that occurs in the original signal: The key is how to make a better recovery of the signal that appears to be distorted in the OFDM system. The parabolic method is used to study the model to solve the problem. First, the characteristics of the frequency domain characteristic of the distorted signal are analyzed. According to the analysis of the parabolic model, we can make a DFT transform, and we can analyze the frequency domain estimation by the specific correlated distortion signal. The effect of random variables we understand is mainly the effect on amplitude, but the most important effect is phase. The length of the frequency domain estimation is first performed. The Minimum Mean Square Error (MMSE) criterion is calculated from the frequency domain estimation of the points in the sample, that is, the estimated multiple values ​​in the frequency domain are found, and the result is calculated. Finally, through calculation, using the recovered frequency domain estimated distortion signal, we can cancel out the distortion from the signal received from the frequency domain estimation and restore the original original signal. It needs to be explained lastly. Since the method of approximation is adopted in the derivation, it is necessary to satisfy the required conditions as much as possible. The frequency domain of the demodulation performed during the frequency domain estimation should satisfy the condition of the frequency domain estimation to ensure the accuracy of the estimation data. It is also possible to use the estimation of the subcarrier points with lower frequency estimates as much as possible.
This one is Cyclone Vacuum Cleaner. It is turely a cyclone Vacuum Cleaner always with strong power. It s cleaning efficiency is always high. Its filter system is 5 stages,so it can use for a long time. We have gotten international patent for the cyclone system used on our vacuum cleaner. So you can use more reliablely. In a word,iIt is worth to own this vacuum cleaner.
Cyclone Vacuum Cleaner Cyclone Vacuum Cleaner, Dual Cyclone Vacuum Cleaner, Cyclone Bagless Vacuum Cleaner Ningbo ChinaClean Household Appliances Manufacture Co., Ltd. , https://www.chinaclean-elec.com
