In this article, an algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver is proposed. The received signal model uses approximations with a small number of parameters to reduce the computational complexity of the resulting algorithm. The estimation algorithm is obtained under the assumption of a priori uncertainty about the characteristics of the communication channel and noise distribution using the linear least squares method. Estimation is performed first by the test sequence, then by the information symbols obtained after detection. In addition, an analysis of the noise immunity of quadrature amplitude modulation (QAM) signal reception is carried out using different approximating structures in the estimation algorithm for systems with a single transmitting and receiving antenna (SISO) and for systems with multiple transmitting and receiving antennas (MIMO). Furthermore, this article examines the influence of the duration of the test signal, the number of sessions of its transmission, and the channel extrapolation interval on the quality of signal reception.

The synthesis of a nonlinear algorithm for joint estimation of signal parameters under conditions of a priori uncertainty about the laws of noise distribution using the theory of regularization and the method of nonlinear filtering in a sliding time window of constant length is considered. It is shown that noise immunity of the proposed algorithm is higher than that of nonlinear filtering, and also that it has a computational complexity less than the known joint estimation procedure and allows in some cases reducing the number of arithmetic operations in comparison with the regularizing algorithm.

Научный журнал «Вестник ЮУрГУ», серия «Математическое моделирование и программирование»