Design and Implementation of Blind Modulation Classification for Asynchronous MIMO-OFDM System

Abstract

In this paper, we design and implement a tree-based blind modulation classification algorithm for asynchronous multiple-input multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) systems. It can classify many of the linearly modulated signals, such as binary phase-shift keying (BPSK), quadrature PSK (QPSK), offset QPSK, minimum shift keying, and 16-quadrature amplitude modulation. The proposed classifier works in the presence of unknown frequency, timing, and phase offsets and with no prior knowledge of channel state information. Classification is performed in three steps. In the first step, pre-processing is done on the received signal to nullify the effect of timing offset. In the second step, key features are extracted by calculating higher-order cumulants of the frequency-domain signal. In the third step, thresholds are determined by using the likelihood ratio test. A closed-form theoretical derivation for the probability of correct classification is obtained. The Monte Carlo simulations are conducted to compare the performance of the proposed algorithm with the existing algorithms. Finally, the proposed algorithm is validated through radio frequency testbed measurements over an indoor propagation environment.