We present a new and efficient method for identifying the MODULATION type of a bursty QAM signal in the presence of additive white Gaussian noise (AWGN) in unknown fading channels and with unknown carrier phase. Our approach is based on an iterative combination of blind equalization and soft-clustering techniques, utilizes the constant modulus algorithm (CMA) for an initial reconstruction of the received signal constellation, and employs a nonparametric soft clustering method to identify a small set of possible MODULATIONs based on the partition coefficient (PC) criterion. We then use an iterative approach in utilizing the decision adjusted modulus algorithm (DAMA) to refine our choices until we reach two hypotheses. Besides, we propose a parallel implementation of the proposed method, and provide an asymptotic analysis as well as simulation results to demonstrate the validity and usefulness of the proposed method. Simulation results indicate that our proposed method achieves a significant gain as compared to the cumulant-based approach for burst mode transmissions in fading channels.

The automatic recognition of the MODULATION format of a detected signal is a major task of an intelligent receiver. This task becomes more difficult when the receiver has no information about the transmitted signal or the channel. At first, the maximum likelihood (ML) classifier for classifying phase-amplitude modulated schemes in coherent environment is presented. It is well known that the ML classifier requires a priori knowledge of the incoming signal and channel (including Amplitude, timing information, noise power and the roll-off factor of the pulse shaping filter). To relax this requirement, we introduce a novel estimator to estimate the parameters required by ML classifier which is blind to the MODULATION scheme of the received signal, and this gives rise to a new completely blind MODULATION classifier for digital amplitude-phase modulated signals over fading channels. Results are presented from simulations in terms of correct detection probability versus SNR for the class of BPSK, QPSK, 8-PSK, 16-QAM and 64-QAM MODULATION schemes. The results show that the performance of this classifier is very close to the ideal classifier with perfect estimates.

In this article, we present new research on the impact of various optical filters on the functionality of an orthogonal Optical Frequency Division Duplexing (OFDM) system for the first time. This paper focused on long-haul optical systems using four Quadrature Amplitude MODULATION (4-QAM) methods for OFDM systems. The analysis demonstrates the impact of choosing a Gaussian, Rectangular, or Trapezoidal optical Filter on the effectiveness of the optical system used for long-distance high data rate transmission. Compared with other systems for long-distance transmission using various filter types, 4-QAM OFDM showed a high Bit Error Rate (BER) performance. Significant findings like transmitting Power received Power, and Error Vector Magnitude (EVM) is compared with the system's propagation length.

This paper concentrates on the error rate analysis of wireless communication systems with diversity combining to derive exact closed-form expressions for QAM and PSK signals in order to provide system designers a precise and more convenient evaluation. Maximal ratio combining (MRC) with L independent and identical (i.i.d) diversity reception paths over slowly Nakagami-m fading channel is considered. The novel results obtained in this paper, via moment generation function (MGF) approach overcome the limitations of earlier works both in terms of generality and ease of simulation as they are presented in integral-free forms. At the end, several numerical results are included.

A direct conversion modulator-demodulator with even harmonic mixers with emphasis on noise analysis is presented. The circuits consist of even harmonic mixers (EHMs) realized with antiparallel diode pairs (APDPs). We evaluate the different levels of I/Q imbalances and DC offsets and use signal space concepts to analyze the bit error rate (BER) of the proposed transceiver using M-ary QAM schemes. Moreover, the simultaneous analysis of the signal and noise has been presented.