Linear Approximation Signal Detection Scheme in MIMO-OFDM Systems

In this paper, we propose a field programmable gate array (FPGA) implementation of a one-dimensional convolution neural network (1D-CNN) demodulator for binary phase shift keying (BPSK). The 1D-CNN demodulator includes two 1D-CNNs and a decision module. Discrete time series of BPSK signals are imported into the well-trained 1D-CNNs. The 1D-CNNs detect the phase shifts' moment and type, including phase shift from 0 to π and that from π to 0. The decision module combines results of the two 1D-CNNs and outputs the demodulated data. In order to improve the efficiency of resource utilization and operation speed of the FPGA circuit, a time-delay network for convolutional calculation and a structure for piecewise approximation for the activation function were designed. To enhance the performance of the 1D-CNN demodulator, universal and diversity training data considering five impact factors were generated specially. Experimental results under different channel conditions show that the proposed demodulator has good adaptability to frequency offset and short latency. The demodulation loss of the proposed demodulator can almost be kept within 2 dB.

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Singular Value Decomposition Channel Estimation in STBC MIMO-OFDM System

Tang

Zhou

Wang

2019

Applied Sciences

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The multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is the combination of the OFDM and MIMO technologies, which could improve the system capacity and make efficient utilization of the frequency spectrum. This paper utilizes space-time block coding (STBC) to achieve diversity gains and combat the channel fading. However, channel estimation is an essential block for space-time block decoding (STBD). Many channel estimation methods are utilized for the single antenna OFDM system, but they cannot be directly applied to the multiple antennas system due to the interference from other antennas. In this paper, orthogonal pilot sequences are designed to suppress the interference of pilot symbols from other transmit antennas. This paper also derives a minimum mean square error (MMSE) channel estimation method in MIMO-OFDM systems. The MMSE method involves the inverse operation of the channel autocorrelation matrix, which has a large calculation complexity. To further reduce the complexity of the MMSE method, the singular value decomposition (SVD) is used to decompose the channel autocorrelation matrix, which avoids the inverse operation. Simulation results verify that the SVD channel estimation method with comb-type pilots and STBC can be effectively adapted to multipath propagation conditions. Keywords: channel estimation; multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM); space-time block coding (STBC); singular value decomposition (SVD); bit error rate (BER)

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Linear Approximation Signal Detection Scheme in MIMO-OFDM Systems

Cited by 3 publications

References 22 publications

Influence of Active Interference on the Capacity of a MIMO-OFDM System Using an Adaptive Processing Algorithm

Influence of Active Interference on the Capacity of a MIMO-OFDM System Using an Adaptive Processing Algorithm

FPGA Implementation of a BPSK 1D-CNN Demodulator

Singular Value Decomposition Channel Estimation in STBC MIMO-OFDM System

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