Non-data-aided frequency offset and symbol timing estimation for binary CPM: performance bounds

The use of (spectrally efficient) CPM modulations may lead to a serious performance degradation of the classical non-data-aided (NDA) frequency and timing estimators due to the presence of self noise. The actual performance of these estimators is usually much worse than that predicted by the classical modified Cramer-Rao bound. We apply some well known results in the field of signal processing to these two important problems of synchronization. In particular we propose and explain the meaning of the unconditional CRB in the synchronization task. Simulation results for MSK and GMSK, along with the performance of some classical and previously proposed synchronizers, show that the proposed bound (along with the MCRB) is useful for a better prediction of the ultimate performance of the NDA estimators.Peer ReviewedPostprint (published version

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

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

1.55 μm integrated modelocked semiconductor lasers

This thesis presents research on, and the realization of compact InP/InGaAsP integrated passively modelocked lasers (MLL) operating in the 1.55 µm wavelength range. The goal of this work was to obtain modelocked laser designs at a repetition rate of several tens of GHz that can be integrated with other devices on a single semiconductor wafer. These modelocked lasers should be usable as optical pulse sources in an all-optical clock recovery application in optical time domain multiplexing (OTDM) systems. The integration of the modelocked laser on a single chip is achieved using the active-passive integration technique. This technique allows one to integrate active components such as optical amplifiers and saturable absorbers, with passive components such as waveguides and optical power splitters. The modelocking mechanism of the integrated lasers is passive modelocking using a slow saturable absorber. The saturable absorber is a short optical amplifier section that is reversely biased. The work was largely concentrated on ring laser type cavities. Such a configuration has many advantages. Firstly it allows one to fix the repetition rate of the laser by photolithography. It also provides better performance thanks to the two counter-propagating pulses which collide in the saturable absorber. Finally the output of the laser can be directly interconnected on the same wafer with other devices such as an all-optical switch or a pulse compressor. From the first realization of integrated ring modelocked lasers (RMLLs) using active-passive integration and a demonstration of a device at 27 GHz, many issues came up and have been addressed in this thesis. First, the understanding of the modelocking mechanism and other dynamics needed to be better understood. To address this issue, a simulation tool of RMLL was developed. Simulation results showed that symmetrical cavities show a much wider operating range for stable modelocking. The transitions from a modelocked state of the laser to another operating regime have been explored with the model. The simulation tool requires parameters describing the gain properties of the material. These have been accurately measured using a new type of high resolution spectrum analyzer. Another important issue which came out from the first RMLL realization was the necessity to reduce all the reflections inside the modelocked laser cavity and in particular the reflections at the active-passive interfaces. Special efforts have therefore been made to characterize the optical losses and reflections at those interfaces and to minimize them to a sufficiently low value of less than -50 dB. To validate techniques of fabrication and materials required to achieve high repetition rate RMLL designs, the realization of more compact devices through the use of deep etching has been investigated in this thesis. Results are presented on, at that time, the world’s most compact AWG using a double-etch technique, and the world’s first InAs/InP quantum dot (QD) lasers employing narrow deeply etched ridge active waveguides in the 1.55 µm wavelength region. Before realizing a final RMLL design on an active-passive wafer, a series of allactive devices has been designed, fabricated and characterized. These all-active chips provided material for the gain measurements and allowed to look further into short pulse laser characterization techniques and to test designs for reducing reflections from other intra-cavity components. The results of the all-active MLLs have been obtained in different configurations. Firstly, 20 GHz and 40 GHz linear all active Fabry-Pérot MLL (FPMLL) lasers have been successfully fabricated. Modelocking has been achieved with these lasers in the colliding pulse modelocked (CPM) and self CPM configurations. Pulse lengths down to 1.6 ps (at 20 GHz) have been observed. A 40 GHz repetition rate was demonstrated in a CPM laser with a Saturable Absorber (SA) positioned in the center of the FP cavity. All-active 15 GHz RMLLs have also been successfully fabricated. These lasers show a relatively good timing stability due to the ring configuration. Measured output pulses are highly chirped and an FWHM bandwidth of up to 4.5 nm was obtained. Such lasers with high bandwidth pulses and compatible with active-passive integration are of great interest for optical code division multiple access applications, where information is coded in the spectrum. Finally, first results from MLLs realized on an active-passive wafer are presented. Passive modelocking has been demonstrated in these integrated Extended Cavity FPMLLs with minimized intra-cavity reflections. Pulses of 2.1 ps duration and with a small pedestal have been observed. The pulses are close to transform-limited. The longer timescale dynamics of the EC-FPMLLs are reduced compared to the all-active FPMLLs, which is understood to be due to the short amplifier section. The use of a MLL at 20 GHz for the all optical clock recovery (AOCR) application and a special RMLL design for AOCR at 40 GHz are presented in the last chapter of this thesis. Many characteristics of the AOCR at 20 GHz could be quantified. The design of the 40 GHz RMLL laser is for an active-passive wafer. The design utilizes all the minimizations of small intra-cavity reflections. For the AOCR application a novel way to couple the optical input signal into the MLL via a separate waveguide is presented. Based on the accumulated results presented in this thesis the timing jitter of the clock recovered from this laser is expected to be sufficiently low to comply with the telecom requirements at 40 GHz

Artifact Rejection Methodology Enables Continuous, Noninvasive Measurement of Gastric Myoelectric Activity in Ambulatory Subjects.

The increasing prevalence of functional and motility gastrointestinal (GI) disorders is at odds with bottlenecks in their diagnosis, treatment, and follow-up. Lack of noninvasive approaches means that only specialized centers can perform objective assessment procedures. Abnormal GI muscular activity, which is coordinated by electrical slow-waves, may play a key role in symptoms. As such, the electrogastrogram (EGG), a noninvasive means to continuously monitor gastric electrical activity, can be used to inform diagnoses over broader populations. However, it is seldom used due to technical issues: inconsistent results from single-channel measurements and signal artifacts that make interpretation difficult and limit prolonged monitoring. Here, we overcome these limitations with a wearable multi-channel system and artifact removal signal processing methods. Our approach yields an increase of 0.56 in the mean correlation coefficient between EGG and the clinical "gold standard", gastric manometry, across 11 subjects (p < 0.001). We also demonstrate this system's usage for ambulatory monitoring, which reveals myoelectric dynamics in response to meals akin to gastric emptying patterns and circadian-related oscillations. Our approach is noninvasive, easy to administer, and has promise to widen the scope of populations with GI disorders for which clinicians can screen patients, diagnose disorders, and refine treatments objectively

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