A GLRT Based Modulation Recognition for Identifying OFDM from M-QAM

This paper proposes a novel algorithm to discriminate Orthogonal Frequency-Division Multiplexing (OFDM) from Quadrature Amplitude Modulation (QAM). Despite the development of modulation recognition algorithms for single-carrier and multi-carrier modulations, most of the algorithms suffer from disability in distinguishing QAM and OFDM. This issue deteriorates when the Signal-to- Noise Ratio (SNR) is low. As a result, this paper utilizes Generalized Likelihood Ratio Test (GLRT) to obtain an optimum solution for recognition in presence of additive white Gaussian noise. Moreover, the maximum likelihood (ML) is applied for data sequence estimation which is considered unknown. The performance of the proposed method is tested by using Monte-Carlo simulations and the superiority of the algorithm is demonstrated efficiently