Seleção de símbolos piloto em sistemas de comunicação sem fio

Abstract

In order to achieve gains on the transmission capacity with lower error probability so the current requirements of mobile communication applications can be met, the way of how data is processed is crucial to improve system performance. In order to improve the quality of the transmission in multi-antenna systems, this work uses techniques of preprocessing of the transmitted signal to improve the system performance measured by the SNR (Signal to Noise Ratio) under a space-time transmit antenna array channel model, where the temporal dynamics of the channel is modeled by a Gauss-Markov process and the spatial correlation by a Kronecker model. Based on the statistical properties of the channel, we use the optimal linear algorithm, also known as a Kalman filter, associated with the transmitted pilot symbols for its estimation. From several sequences of defined pilot symbols, this work proposes an algorithm capable of selecting the best sequences of pilot symbols that maximize the received SNR. In the numerical simulations, we analyze the performance of the proposed method for pilot symbols selection and, as benchmark, the performance of the method of random pilot symbols selection. The results show the proposed method outperforms the random selection one.