M.A. Romashchenko – Dr.Sc.(Eng.), Professor, 

Department Radio Equipment Engineering and Manufacturing, Voronezh State Technical University

O.N. Chirkov – Senior Lecturer, 

Department Radio Equipment Engineering and Manufacturing, Voronezh State Technical University E-mail: chir_oleg@mail.ru

P.P. Churakov – Dr.Sc.(Eng.), Professor, Dean, 

Faculty «Testing, Information Technologies and Systems», Penza State University E-mail: fait@pnzgu.ru

Methods of elementary detection of signals ESE suggest that in the receiving path known perfect knowledge of the radio channel. However, in practice, for noise-tolerant data reception, it is necessary to obtain the channel impulse response using the estimate. This article presents an improved method for estimating a radio link based on a Wiener filter with iterative interference suppression (IIC) for multi-user multi-antenna MIMO OFDM systems.

With the continuous development of high-speed wireless access systems, methods of noise-resistant signal detection will be improved. Elementary detection methods ESE suggest that in the receiving path, perfect knowledge of the radio link is known. However, in practice, for noise-tolerant data reception, it is necessary to obtain the channel impulse response using the estimate. This article proposes an improved method for estimating a radio link based on a Wiener filter with iterative interference suppression (IIC) for multi-user multi-antenna MIMO OFDM systems.

Today, in any remote access system, knowledge about changing the communication channel at the receiver is the key to achieving reliable coherent reception of the transmitted signal. The accuracy of the radio channel estimate is directly proportional to the performance of remote access systems. Today’s iterative detection schemes for multi-user multi-antenna systems using orthogonal channel frequency multiplexing are based on perfect knowledge of the wireless communication channel (PCK) and provide nearly optimal BER performance for a two-user communication system. However, with an increase in the number of users in the system, methods based on a fully known channel do not provide high data recognition efficiency.

Simulation results show that iterative channel estimation can provide greater gain and get much better BER performance.

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