Abstract
Introduction: The procedure for detecting a quadrature amplitude modulation (QAM) signal in a communication system with multiple transmitting and receiving antennas (MIMO) is considered, which consists of two stages: obtaining soft solutions using the recurrent Kalman filtering algorithm, finding hard solutions by criterion of minimum distance between soft decision vectors and possible information symbols on each receiving antenna. The Kalman algorithm evaluates symbols at i-th time point in iterations. A comparison is made of noise immunity of QAM signal reception obtained using the Zero Forcing methods, the minimum mean square error (RMS), and recurrent Kalman procedure. Signal processing takes place under channel conditions with Rayleigh fading and Doppler spread spectrum. Cases are considered when the channel matrix is known exactly and when it is estimated by least squares method (LSM) using a first-order polynomial approximation for channel matrix elements. The channel matrix takes into account not only signal distortions due to the propagation medium, but also distortions obtained in the direct conversion receiver, such as amplitude and phase imbalance between signal quadratures, frequency shift due to non-ideal demodulation procedure, as well as DC drift. Result: The computational complexity of the detector based on Kalman algorithm is analyzede.
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