Performance Analysis of Reliable Adaptive Transmission for Mobile Radio Slow Frequency Hopping Channels Aided by Long Range Prediction

Abstract

Due to correlated fading in frequency hopping (FH) wireless communication systems, it is possible to predict the future channel state information (CSI) for one frequency based on the channel observations of other frequencies. As a result, the performance of slow FH systems can be improved by utilizing adaptive transmission techniques. We propose the optimal Minimum Mean Square Error (MMSE) Long Range Prediction algorithm for slow FH systems that employ coherent detection. A recursive autocorrelation update method and a simplified prediction algorithm are explored to reduce the complexity. Statistical model of the prediction accuracy is developed and used in the design of the reliable adaptive transmission systems. We investigate the performance of adaptive transmission for high-speed data transmission in SFH systems based on the proposed Long Range Prediction algorithms. For slow frequency hopping communications in the presence of partial-band interference, we propose to employ adaptive transmitter frequency diversity and adaptive modulation to mitigate the effects of partial-band interference and fading. Both standard Jakes model and realistic physical model are used to test the performance. Analysis and simulation results show that significant performance gains can be achieved relative to non-adaptive methods.