Data Fitting-based SNR estimation algorithm for the Adaptive Transmission

Adaptive transmission system selects the suitable transmission rate on the basis of the current channel state. In this paper, we exploit the signal to noise ration (SNR) as a benchmark of standard to measure the channel state. We employ data fitting (DF) to estimate SNR, which is a key technology of the adaptive transmission, and we change the transmission rate according to the estimation of SNR. The proposed algorithm can obtain a low computational complexity and can have performance improvement of SNR estimation. The superiority of the proposed algorithm is revealed by simulations.. Introduction Adaptive transmission technique is a significant method of judging the channel condition and adjusting the transmission rate of the system according to the stand or fall of the channel state [1-2]. Higher transmission rate is chosen with a good channel state while the data throughput will be degrading with the channel quality getting poor. In this paper, an adaptive transmission scheme is studied, which applies adaptive variable-rate technique to change the data rate of the communication system. In this paper, the signal to noise ration (SNR) is taken as the benchmark of channel condition. The receiver first estimates the SNR of the receiving signal in real time. According to the result of comparison between the SNR estimation and the give threshold, the receiver chooses a suitable transmission rate and gives a feedback to transmitter in the form of control information. Finally the transmitter gives a command to switch the rate while detecting the control information. SNR estimation method consists of time domain method and frequency domain method. For the time domain method, it can be divided into data aided (DA) method and non-data aided (NDA) method [3]. DA method has a higher estimation accuracy than NDA method, but involving the insertion of periodic pilot sequence, which is inefficient. In time domain method, the SNR estimation algorithms based on DA include minimum mean square error (MMSE), maximum likelihood (ML), separating character matrix estimation (SSME) and high-order-cumulants signal-noise separation method, while the SNR estimation algorithms based on NDA contain M2M4, Signal-to-Variation Ratio (SVR) and squared Signal-to-Noise Variance (SNV) [5-12]. In this paper, we use Data Fitting (DF) method for SNR estimation, which is a key technology in field of adaptive transmission. The proposed algorithm can obtain a low computational complexity and can have performance improvement of SNR estimation. The superiority of the proposed algorithm is revealed by simulations. The reminder of this paper is structured as follows. The adaptive transmission scheme Adjusting the transmission rate based on SNR is a process that first detecting the present SNR value in real-time through the receiving signal, and then deciding the transmission rate according to the SNR value. Adaptive rate transmission based on SNR reflects the present channel state. In this 4th International Conference on Machinery, Materials and Information Technology Applications (ICMMITA 2016) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Computer Science Research, volume 71