Research On Signal - To - Noise Ratio Estimation Of Dual Channel Based On Intelligent Distribution Network

With the rapid development of smart grid, communication technology is more and more important in the smart grid system. Smart grid communication technology is the key of if the smart grid can safely and efficiently transfer control information and data information. Therefore, proposing the dual-channel model based on the smart grid is of great significant. The dual-channel means that two independent and different channels transfer the same data information in the different environment, and it can make the transmission more safer under the same condition. Also, it makes possible for us to choose the most efficient channel to transfer information, especially when it is in some emergency cases. At the same time, because the SNR is one of the most remarkable factors among communication qualities. So, the most important job in this paper is bye doing SNR estimation in various channels and choose which channel is better one.Under this background, this paper discussed and simulated the different SNR algorithms with the two different signal modulations, mainly simulated and in-depth analysis the SNR estimation based on the dual-channel of PLC and Rayleigh wireless fading channel.First of all, this paper established and discussed the dual-channel model, which are two independent to each other with different channel characteristics. Deducing data aided SNR estimation algorithm in detail, which will lay theoretical foundation for the subsequent simulations. Secondly, because different algorithms applied to different signal modulation models, this paper compared the real signal and the complex signal in different situations. It shows that signal with Additive White Gaussian noise channel can meet the range of [-5,25]dB SNR estimation with a certain accuracy, and the real signal can reach a lower normalized deviation with the same algorithm. SNR estimation under Rayleigh fading channel is more complicated than AWGN channel, the decline factor will badly influence the signal. In this paper, adopting the M2M4 algorithm can achieve the result of normalized deviation of less than 0.5dB.Final chapter simulated SNR estimation under the PLC channel. According to different channel characteristics, the PLC channel with Narrowband Gaussian noise is a new challenge to these algorithms, and it really not easy to find a suitable one to simulate, but the M2M4 algorithm can guarantee SNR estimation’s Bias within 0.3 dB under the PLC channel.