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

Modulation-Index Estimation in a Combined CPM/OFDM Receiver

In this paper we develop a blind modulation-index estimator for\ud a combined CPM/OFDMReceiver. The performance of the estimator\ud in an AWGN channel is assessed by simulation and analysis\ud and its suitability for our receiver is established

Symbol timing recovery for generalized minimum shift keying modulations in software radio receiver

A new symbol timing estimator for generalized MSK signals is proposed. It is based on the squaring algorithm and has a feedforward structure. The proposed timing estimator is fully-digital and is suitable for implementation in software radios. The performance in AWGN channel is compared with the Modified Cramer-Rao bound and that of the ML algorithm. The proposed timing estimator is found to have a performance close to that of the ML algorithm, but with a lower implementation complexity.published_or_final_versio

New implementation of a GMSK demodulator in linear software radio receiver

This paper proposes a practical linear software-radio architecture (dealing with linear modulations) that is suitable for multi-mode operation. In particular, it is shown how to integrate GMSK into the proposed architecture. Coherent and noncoherent detections of GMSK signals are detailed for the implementation of the proposed software radio.published_or_final_versio

Advanced digital modulation: Communication techniques and monolithic GaAs technology

Communications theory and practice are merged with state-of-the-art technology in IC fabrication, especially monolithic GaAs technology, to examine the general feasibility of a number of advanced technology digital transmission systems. Satellite-channel models with (1) superior throughput, perhaps 2 Gbps; (2) attractive weight and cost; and (3) high RF power and spectrum efficiency are discussed. Transmission techniques possessing reasonably simple architectures capable of monolithic fabrication at high speeds were surveyed. This included a review of amplitude/phase shift keying (APSK) techniques and the continuous-phase-modulation (CPM) methods, of which MSK represents the simplest case

Synchronization Issues for Continuous Phase Modulations

Continuous-phase modulations (CPMs) have been studied for many years. Mainly because of the attractive property of constant envelope, that make this family the most suitable modulations in the satellite field, they found their first relevant practical application in mobile communications, where they represent the standard signal format for GSM. In spite of the huge literature that is available on the subject, more elaborate CPM schemes have found no application until now because of the implementation complexity of the detector, and of synchronization problems. In the last few years several methods have been proposed to solve synchronization issues related to Continuous Phase Modulations (CPMs). Unfortunately most of these techniques are ad-hoc algorithms, developed to meet synchronization problems for a particular subclass of signals. In this thesis, we tackle the issue of both cyclostationary-based and soft-based synchronization for continuous phase modulations (CPMs), by extending to such signals (including the multi-h variant) the corresponding methods that were already proposed for linearly-modulated data signals. As first, we will examine the timing synchronization algorithm. The problem of blind timing recovery with linear modulations has several efficient solutions, irrespective of the complexity of the signal constellation. The workhorse in this respect is Gardner’s timing error detector, that is a closed loop estimator. Another approach is represented by the wellknown Oerder-Meyr’s (O&M) estimator, that is on the contrary an open loop method. Gini and Giannakis (G&G) showed that the O&M estimator is a particular sample of a larger class of estimators that exploit the cyclostationarity of a data signal. We will show in the following that the G&G approach can be extended to CPM signals, and we will perform an approximate analytical performance evaluation. The second part of this work is about another general synchronization method that can be applied to CPM signals, that exploit the trellis structure inherent in the modulator. In particular we will focus on phase estimation, being the phase the parameter that shows the lower implementation complexity. Our approach is the so-called code-aided synchronization, that take benefits from the a priori information available from the code structure applied to a linear modulation scheme. We try to extend this approach to CPMs, since this signals share with a coded system the trellis structure, due to the inherent memory of the CPM modulator. The algorithm starts with a first step, called Expectation- Maximisation. It is an iterative method which enables to solve ML optimisation problem. In the special case of the sole phase, being CPM a phase modulation, the computational complexity decreases and it is possible to find a closed form for the estimator, that is data aided and makes use of the state transition probabilities given by a symbol-based BCJR, developed in an ad-hoc way for an uncoded CPM signal

Automatic modulation classification of communication signals

The automatic modulation recognition (AMR) plays an important role in various civilian and military applications. Most of the existing AMR algorithms assume that the input signal is only of analog modulation or is only of digital modulation. In blind environments, however, it is impossible to know in advance if the received communication signal is analogue modulated or digitally modulated. Furthermore, it is noted that the applications of the currently existing AMR algorithms designed for handling both analog and digital communication signals are rather restricted in practice. Motivated by this, an AMR algorithm that is able to discriminate between analog communication signals and digital communication signals is developed in this dissertation. The proposed algorithm is able to recognize the concrete modulation type if the input is an analog communication signal and to estimate the number of modulation levels and the frequency deviation if the input is an exponentially modulated digital communication signal. For linearly modulated digital communication signals, the proposed classifier will classify them into one of several nonoverlapping sets of modulation types. In addition, in M-ary FSK (MFSK) signal classification, two classifiers have also been developed. These two classifiers are also capable of providing good estimate of the frequency deviation of a received MFSK signal. For further classification of linearly modulated digital communication signals, it is often necessary to blindly equalize the received signal before performing modulation recognition. This doing generally requires knowing the carrier frequency and symbol rate of the input signal. For this purpose, a blind carrier frequency estimation algorithm and a blind symbol rate estimation algorithm have been developed. The carrier frequency estimator is based on the phases of the autocorrelation functions of the received signal. Unlike the cyclic correlation based estimators, it does not require the transmitted symbols being non-circularly distributed. The symbol rate estimator is based on digital communication signals\u27 cyclostationarity related to the symbol rate. In order to adapt to the unknown symbol rate as well as the unknown excess bandwidth, the received signal is first filtered by using a bank of filters. Symbol rate candidates and their associated confident measurements are extracted from the fourth order cyclic moments of the filtered outputs, and the final estimate of symbol rate is made based on weighted majority voting. A thorough evaluation of some well-known feature based AMR algorithms is also presented in this dissertation