CRB derivation and new Code-Aided timing recovery technique for QAM modulated signals

International audience— * In this paper, we propose a maximum likelihood based Code-Aided (CA) timing recovery algorithm for square-QAM modulated signals. We also theoretically derive the analytical expression of the CA Cramer-Rao Bound for time delay estimation. Our simulations show that the proposed CA approach realizes a performance equivalent to the Data-Aided (DA) approach over a large interval of signal to noise ratio (SNR) values

Performance Study of a Near Maximum Likelihood Code-Aided Timing Recovery Technique

International audienceIn this paper, we propose a new code-aided (CA) timing recovery algorithm for various linear constant modulus constellations based on the Maximum Likelihood (ML) estimator. The first contribution is the derivation of a soft estimator expression of the transmitted symbol instead of its true or hard estimated value which is fed into the timing error detector (TED) equation. The proposed expression includes the Log-Likelihood Ratios (LLRs) obtained from a turbo decoder. Our results show that the proposed CA approach achieves almost as good results as the data-aided (DA) approach over a large interval of SNR values while achieving a higher spectral efficiency. We also derive the corresponding CA Cramer Rao Bounds (CRB) for various modulation orders. Contrarily to former work, we develop here the CRB analytical expression for different M-PSK modulation orders and validate them through comparison to empirical CRB obtained by Monte Carlo iterations. The proposed CA estimator realizes an important gain over the non data-aided approach (NDA) and achieves a smaller gap when compared to its relative CA CRB, especially at moderate SNR values where modern systems are constrained to work

New advances in synchronization of digital communication receivers

Synchronization is a challenging but very important task in communications. In digital communication systems, a hierarchy of synchronization problems has to be considered: carrier synchronization, symbol timing synchronization and frame synchronization. For bandwidth efficiency and burst transmission reasons, the former two synchronization steps tend to favor non-data aided (NDA or blind) techniques, while in general, the last one is usually solved by inserting repetitively known bits or words into the data sequence, and is referred to as a data-aided (DA) approach. Over the last two decades, extensive research work has been carried out to design nondata-aided timing recovery and carrier synchronization algorithms. Despite their importance and spread use, most of the existing blind synchronization algorithms are derived in an ad-hoc manner without exploiting optimally the entire available statistical information. In most cases their performance is evaluated by computer simulations, rigorous and complete performance analysis has not been performed yet. It turns out that a theoretical oriented approach is indispensable for studying the limit or bound of algorithms and comparing different methods. The main goal of this dissertation is to develop several novel signal processing frameworks that enable to analyze and improve the performance of the existing timing recovery and carrier synchronization algorithms. As byproducts of this analysis, unified methods for designing new computationally and statistically efficient (i.e., minimum variance estimators) blind feedforward synchronizers are developed. Our work consists of three tightly coupled research directions. First, a general and unified framework is proposed to develop optimal nonlinear least-squares (NLS) carrier recovery scheme for burst transmissions. A family of blind constellation-dependent optimal "matched" NLS carrier estimators is proposed for synchronization of burst transmissions fully modulated by PSK and QAM-constellations in additive white Gaussian noise channels. Second, a cyclostationary statistics based framework is proposed for designing computationally and statistically efficient robust blind symbol timing recovery for time-selective flat-fading channels. Lastly, dealing with the problem of frame synchronization, a simple and efficient data-aided approach is proposed for jointly estimating the frame boundary, the frequency-selective channel and the carrier frequency offset

On the Cramer-Rao bound for carrier frequency estimation in the presence of phase noise

We consider the carrier frequency offset estimation in a digital burst-mode satellite transmission affected by phase noise. The corresponding Cramer-Rao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even if we resort to a Monte Carlo average, from a computational point of view the evaluation of the Cramer-Rao bound is very hard. We introduce a simple but very accurate approximation that allows to carry out this task in a very easy way. As it will be shown, the presence of the phase noise produces a remarkable performance degradation of the frequency estimation accuracy. In addition, we provide asymptotic expressions of the Cramer-Rao bound, from which the effect of the phase noise and the dependence on the system parameters of the frequency offset estimation accuracy clearly result. Finally, as a by-product of our derivations and approximations, we derive a couple of estimators specifically tailored for the phase noise channel that will be compared with the classical Rife and Boorstyn algorithm, gaining in this way some important hints on the estimators to be used in this scenario

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

The automatic classification of the modulation type of communication signals

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Local oscillator parameter estimation of collaborative beamforming nodes

Parameter estimation of complex exponential signals corrupted by additive white Gaussian noise (AWGN) is crucial in the study of distributed beamforming in a practical scenario. Near zero (0) phase offset are expected at the receiver end which rely on the smoothing and correction of the frequency and phase estimates. Neither computational complexity nor the processing latency has an effect on the expected zero phase offset but the estimation accuracy does. Thus, the maximum likelihood estimator (MLE) using Fast Fourier Transform (FFT) approach is being considered for cases with none and post processing in locating of the maximum peaks. Details on how the phase estimates are arrived at is not always covered in literatures but explained in the article. Numerical results obtained showed that global maximum peaks are arrived at by employing a fine search with higher values of FFT

Synchronization Techniques for Burst-Mode Continuous Phase Modulation

Synchronization is a critical operation in digital communication systems, which establishes and maintains an operational link between transmitter and the receiver. As the advancement of digital modulation and coding schemes continues, the synchronization task becomes more and more challenging since the new standards require high-throughput functionality at low signal-to-noise ratios (SNRs). In this work, we address feedforward synchronization of continuous phase modulations (CPMs) using data-aided (DA) methods, which are best suited for burst-mode communications. In our transmission model, a known training sequence is appended to the beginning of each burst, which is then affected by additive white Gaussian noise (AWGN), and unknown frequency, phase, and timing offsets. Based on our transmission model, we derive the Cramer-Rao bound (CRB) for DA joint estimation of synchronization parameters. Using the CRB expressions, the optimum training sequence for CPM signals is proposed. It is shown that the proposed sequence minimizes the CRB for all three synchronization parameters asymptotically, and can be applied to the entire CPM family. We take advantage of the simple structure of the optimized training sequence in order to design a practical synchronization algorithm based on the maximum likelihood (ML) principles. The proposed DA algorithm jointly estimates frequency offset, carrier phase and symbol timing in a feedforward manner. The frequency offset estimate is first found by means of maximizing a one dimensional function. It is then followed by symbol timing and carrier phase estimation, which are carried out using simple closed-form expressions. We show that the proposed algorithm attains the theoretical CRBs for all synchronization parameters for moderate training sequence lengths and all SNR regions. Moreover, a frame synchronization algorithm is developed, which detects the training sequence boundaries in burst-mode CPM signals. The proposed training sequence and synchronization algorithm are extended to shaped-offset quadrature phase-shift keying (SOQPSK) modulation, which is considered for next generation aeronautical telemetry systems. Here, it is shown that the optimized training sequence outperforms the one that is defined in the draft telemetry standard as long as estimation error variances are considered. The overall bit error rate (BER) plots suggest that the optimized preamble with a shorter length can be utilized such that the performance loss is less than 0.5 dB of an ideal synchronization scenario