Research Of Channel Prediction In Wireless Communication System

The basic characteristic of wireless communication is transmitting information in the free space by radio wave. In comparison with other communication channels, wireless channel is the most complicated one. So the wireless communication has to face such a big challenge. During the courses between transmitting aerials and receiving antennas, the signal will pass through all kinds of complicated pathways, including point-blank pathway, reflected pathway, diffractive pathway, dispersed pathway, and the random combination of the pathways above. At the same time, when the radio wave is transmitting, the useful signal will be disturbed by all kinds of noise, including AWGN, multiplicative noise. So the signal is distorted, even can not be resumed. The radio wave is not only affected by the free space, but also affected by the buildings and the landform. The fading will change randomly as the mobile terminal and the environment of channel change.The wireless mobile communication channel limits the performance of the wireless communication system a lot. The path between the transmitter and the receiver becomes very complex due to terrain and man-made element which cause the multipath problem between the transmitter and the receiver. The fast moving terminal will also cause Doppler affect when it receives the signal. All this result in the amplitude and phase of the receive signal vary fast which is called feeding. It is the influence of the deep feeding that limits the performance of the communication system very much. The new modulation, coding and power control methods are needed in the feeding channel efficiently. The new adaptive transmitter techniques are investigated, such as adaptive modulation, adaptive coding, adaptive power control adaptive and adaptive transmitter antenna diversity and so on. These adaptive transmitter schemes all vary the constellation size, symbol rate, coding rate, transmitted power level weights of transmission antennas or any combination of these parameters by instantaneously monitoring channel conditions. They are trying to use both power and spectrum more efficiently without sacrificing the bit error rate performance that can realize the higher information transmitter rate. To implement adaptive transmission methods in practice, the channel state (CSI) must be available at the transmitter. With the sampling data of the receiver samples in the past interval, we use the arithmetic of channel predictions to predict the fading channel coefficient. Afterwards, transmit the fading channel coefficient to transmitter in the feedback channel. The transmitter will decide the transmission power, modulation methods, coding methods and the transmission antennas, to fit the transmission conditions of the time. Thus, transmitter is optimized, and the communication performance is improved at the same time. But the restriction of adaptive method such as the delay of the wane channel coefficient, delay of compute process and coding modulate will influence design of adaptive transmission method. To slow decline channel, the adaptive system could be designed with the CSI of long time delay. But to fast decline channel, even short delay may make the performance of the adaptive transmission system sharply. Because Doppler Frequency Shifting is bigger and channel changes quickly, the CSI of feeding back to transmitter are not ones at the same time, which make the performance of the adaptive transmission system sharply. To different channels, the range of channel prediction is decided by practical condition, but for exerting the advantage of adaptive transmission it need to process the decline channel prediction before hundreds of transmission data.In the article, frequency selectivity decline prediction arithmetic is researched deeply. The application channel prediction is very important, which is researched by many people not researched in this article.In the article, I introduced channel transmission mechanism and the characteristics of fading channels, and then introduced two channels models at these characteristic-Clarke channel model and Jake channel model. Due to the frequency selectivity of, there are two kinds of channel prediction algorithm. One is the same with flat fast fading channel and another is the same with frequency selectivity fading channel. I gathered some flat fast fading channel prediction algorithm, which includes classical MMSE prediction algorithm, subspace prediction based on subspace left carry wave and adaptive prediction algorithm.Based on flat fading channel prediction, I advanced two kinds of frequency selectivity fading channel prediction algorithm, which is frequency domain channel prediction and Walsh domain channel prediction. At last, I advanced a linear channel prediction based on pilot signals. As simulation estimate, the interval of the pilot signals is smaller, the performance is better, but frequency spectrum of system will come down. Increasing prediction steps could advance prediction definition, but the system will become more complex. So in practical system, we have to look for balance.