Blind Carrier Phase Recovery for General 2{\pi}/M-rotationally Symmetric Constellations

This paper introduces a novel blind carrier phase recovery estimator for general 2{\Pi}/M-rotationally symmetric constellations. This estimation method is a generalization of the non-data-aided (NDA) nonlinear Phase Metric Method (PMM) estimator already designed for general quadrature amplitude constellations. This unbiased estimator is seen here as a fourth order PMM then generalized to Mth order (Mth PMM) in such manner that it covers general 2{\Pi}/M-rotationally symmetric constellations such as PAM, QAM, PSK. Simulation results demonstrate the good performance of this Mth PMM estimation algorithm against competitive blind phase estimators already published for various modulation systems of practical interest.Comment: 14 pages, 12 figures, International Journal of Wireless & Mobile Networks (IJWMN

A Simple Improvement to the Viterbi and Viterbi Monomial-Based Phase Estimators

It is well known that the Viterbi and Viterbi Monomial- Based Phase Estimator, which includes the Mth Power Estimator, performs poorly for cross QAM signals. However, it is shown here that by allowing the power of the monomial to be negative, much improved performance can be realized at medium to high signalto- noise ratios (SNR). Monte Carlo simulations are used to demonstrate the efficacy of this novel simple extension, for 32- and 128-QAM systems. In principle, this extension can also be applied to other constellations, e.g., (4,12)-PSK

Blind Phase Recovery in Cross QAM Communication Systems with the Reduced Constellation Eigth-Order Estimator (RCEOE)

The eighth-order (EOE) phase estimator [4] is modified to work for an eight-symbol symmetrical constellation, so that the large signal-to-noise (SNR) performance is not limited by self-noise. By using only the eight highest energy points of cross- QAM constellations, a reduced constellation eighth-order estimator (RCEOE) is proposed. Computer simulations for 128-QAM show that this new method performs substantially better than the recently introduced APP phase estimator of Wang et al. [8]. However, simulations with 32-QAM show little performance advantage of the RCEOE over the APP estimator, for SNR values normally of interest, whereas for low SNR, the improvement is significant. Application to any constellation which can be reduced to an 8-symbol quadrant symmetrical sub-constellation is straightforward

Joint data detection and channel estimation for OFDM systems

We develop new blind and semi-blind data detectors and channel estimators for orthogonal frequency-division multiplexing (OFDM) systems. Our data detectors require minimizing a complex, integer quadratic form in the data vector. The semi-blind detector uses both channel correlation and noise variance. The quadratic for the blind detector suffers from rank deficiency; for this, we give a low-complexity solution. Avoiding a computationally prohibitive exhaustive search, we solve our data detectors using sphere decoding (SD) and V-BLAST and provide simple adaptations of the SD algorithm. We consider how the blind detector performs under mismatch, generalize the basic data detectors to nonunitary constellations, and extend them to systems with pilots and virtual carriers. Simulations show that our data detectors perform well

Advanced methods in automatic modulation classification for emerging technologies

Modulation classification (MC) is of large importance in both military and commercial communication applications. It is a challenging problem, especially in non-cooperative wireless environments, where channel fading and no prior knowledge on the incoming signal are major factors that deteriorate the reception performance. Although the average likelihood ratio test method can provide an optimal solution to the MC problem with unknown parameters, it suffers from high computational complexity and in some cases mathematical intractability. Instead, in this research, an array-based quasi-hybrid likelihood ratio test (qHLRT) algorithm is proposed, which depicts two major advantages. First, it is simple yet accurate enough parameter estimation with reduced complexity. Second the incorporation of antenna arrays offers an effective ability to combat fading. Furthermore, a practical array-based qHLRT classifier scheme is implemented, which applies maximal ratio combining (MRC) to increase the accuracy of both carrier frequency offset (CFO) estimation and likelihood function calculation in channel fading. In fact, double CFO estimations are executed in this classifier. With the first the unknown CFO, phase offsets and amplitudes are estimated as prerequisite for MRC operation. Then, MRC is performed using these estimates, followed by a second CFO estimator. Since the input of the second CFO estimator is the output of the MRC, fading effects on the incoming signals are removed significantly and signal-to-noise ratio (SNR) is augmented. As a result, a more accurate CFO estimate is obtained. Consequently, the overall classification performance is improved, especially in low SNR environment. Recently, many state-of-the-arts communication technologies, such as orthogonal frequency division multiplexing (OFDM) modulations, have been emerging. The need for distinguishing OFDM signal from single carrier has become obvious. Besides, some vital parameters of OFDM signals should be extracted for further processing. In comparison to the research on MC for single carrier single antenna transmission, much less attention has been paid to the MC for emerging modulation methods. A comprehensive classification system is proposed for recognizing the OFDM signal and extracting its parameters. An automatic OFDM modulation classifier is proposed, which is based on the goodness-of-fittest. Since OFDM signal is Gaussian, Cramer-von Mises technique, working on the empirical distribution function, has been applied to test the presence of the normality. Numerical results show that such approach can successfully identify OFDM signals from single carrier modulations over a wide SNR range. Moreover, the proposed scheme can provide the acceptable performance when frequency-selective fading is present. Correlation test is then applied to estimate OFDM cyclic prefix duration. A two-phase searching scheme, which is based on Fast Fourier Transform (FFT) as well as Gaussianity test, is devised to detect the number of subcarriers. In the first phase, a coarse search is carried out iteratively. The exact number of subcarriers is determined by the fine tune in the second phase. Both analytical work and numerical results are presented to verify the efficiency of the proposed scheme

Asymptotic Performance of the Pth Power-Law Phase Estimator

An expression for the true variance of the Pth powerlaw phase estimator, as the number of samples approaches infinity, is given. This expression is an extension to the linear approximation of Moeneclaey and de Jonghe [1] which is known to be inadequate in some practical systems. Our new expression covers general 2π/P-rotationally symmetric constellations that include those of PAM, QAM, PSK, Star M-QAM, MR-DPSK, and others. This expression also generalizes the known expressions for QAM and PSK. Additionally, our expression reduces to the Cramer-Rao bound given by Steendam and Moeneclaey [9], as SNR goes to zero. Monte Carlo simulations provide experimental verification of the theoretical expression for various constellations