Consecutive Symbols Research Articles

Re2Pair: Increasing the Scalability of RePair by Decreasing Memory Usage.

The RePair compression algorithm produces a context-free grammar by iteratively substituting the most frequently occurring pair of consecutive symbols with a new symbol until all consecutive pairs of symbols appear only once in the compressed text. It is widely used in the settings of bioinformatics, machine learning, and information retrieval where random access to the original input text is needed. For example, in pangenomics, RePair is used for random access to a population of genomes. BigRePair improves the scalability of the original RePair algorithm by using Prefix-Free Parsing (PFP) to preprocess the text prior to building the RePair grammar. Despite the efficiency of PFP on repetitive text, there is a scalability issue with the size of the parse which causes a memory bottleneck in BigRePair. In this paper, we design and implement recursive RePair (denoted as ), which builds the RePair grammar using recursive PFP. Our novel algorithm faces the challenge of constructing the RePair grammar without direct access to the parse of text, relying solely on the dictionary of the text and the parse and dictionary of the parse of the text. We compare to BigRePair using SARS-CoV-2 haplotypes and haplotypes from the 1000 Genomes Project. We show that our method achieves over a 40% peak memory reduction and a speed up ranging between 12% to 79% compared to BigRePair when compressing the largest input texts in all experiments. is made publicly available under the GNU public license here: https://github.com/jkim210/Recursive-RePair.

Optically biased and controlled signal processing in silicon photonics.

Optically biased and controlled signal processing is demonstrated in a commercial foundry silicon photonics integrated circuit process. Data and control signals are carried by different wavelengths in a WDM format. Optical signals on bias and control channels are converted to electrical voltages using series stacked photodiodes operating in photoconductive mode. Two examples of this scheme, namely, an amplitude modulator and a two-tap sequence detector capable of supporting different modulation formats, are experimentally demonstrated. The amplitude modulator requires 0.25 mW of optical control signal power to tune its optical output power by 15 dB. The two-tap sequence detector maps the consecutive symbols of a modulated signal such as OOK, PAM-3, and PAM-4, to distinct levels. A maximum control signal power of 5 mW is needed to calibrate and bias the sequence detector. This latter scheme may be extended to detect longer sequences and other modulation formats.

Lattice-Based Analog Mappings for Low-Latency Wireless Sensor Networks

We consider the transmission of spatially correlated analog information in a WSN through fading SIMO MAC with low latency requirements. A lattice-based analog JSCC approach is considered where vectors of consecutive source symbols are encoded at each sensor using an n-dimensional lattice and then transmitted to a multi-antenna central node. We derive a MMSE decoder that accounts for both the multi-dimensional structure of the encoding lattices and the spatial correlation. In addition, a sphere decoder is considered to simplify the required searches over the multi-dimensional lattices. Different lattice-based mappings are approached and the impact of their size and density on performance and latency is analyzed. Results show that, while meeting low-latency constraints, lattice-based analog JSCC provides performance gains and higher reliability with respect to the state-of-the-art JSCC schemes.

Multiple Signal Classification Based Joint Communication and Sensing System

Joint communication and sensing (JCS) has become a promising technology for mobile networks because of its higher spectrum and energy efficiency. Up to now, the prevalent fast Fourier transform (FFT)-based sensing method for mobile JCS networks is on-grid based, and the grid interval determines the resolution. Because the mobile network usually has limited consecutive OFDM symbols in a downlink (DL) time slot, the sensing accuracy is restricted by the limited resolution, especially for velocity estimation. In this paper, we propose a multiple signal classification (MUSIC)-based JCS system that can achieve higher sensing accuracy for the angle of arrival, range, and velocity estimation, compared with the traditional FFT-based JCS method. We further propose a JCS channel state information (CSI) enhancement method by leveraging the JCS sensing results. Finally, we derive a theoretical lower bound for sensing mean square error (MSE) by using perturbation analysis. Simulation results show that in terms of the sensing MSE performance, the proposed MUSIC-based JCS outperforms the FFT-based one by more than 20 dB. Moreover, the bit error rate (BER) of communication demodulation using the proposed JCS CSI enhancement method is significantly reduced compared with communication using the originally estimated CSI.

An Efficient Random Access Reception Algorithm for ToA Estimation in NB-IoT

Narrowband Internet of Things (NB-IoT) aims to provide wide coverage for a massive number of low-cost devices. Therefore, an NB-IoT physical random access channel (NPRACH) preamble based on a single tone signal with frequency hopping was designed, enabling the base station to estimate the time-of-arrival (ToA) values for realizing uplink synchronization among multiple users. However, due to residual carrier frequency offset (RCFO) in the NPRACH preamble, it is crucial to keep the accuracy of the ToA estimation. Recognizing this urgency, in this paper we first judiciously investigate the effect of the hooping distance on ToA estimation. With which, we propose an efficient receiving algorithm to improve the accuracy of ToA estimation. The main aim of the algorithm is to treat two consecutive symbol groups as a whole and then carry out difference calculations on the two newly constituted symbol groups to construct a more logical frequency hopping distance. Extensive numerical results validate the superiorly of our proposed scheme compared against conventional strategies, showing that the probability of the ToA estimation obtained by this method is 99% within the acceptable error range.

Heart rate fragmentation in renovascular hypertensive rats

Although rapid oscillations of the heart rate (HR) are attributed to vagal modulation of the heart, a pattern of ultra-rapid HR variation has been named heart rate fragmentation (HRF). It is a recently proposed approach to evaluate sino-atrial instability characterized by the presence of numerous inflections points in a series of successive values of cardiac intervals. HRF is increased in aging and coronary diseases. Hypertension markedly alters HRV indices and might affect HRF as well. This study aimed to investigate the HRF in renovascular hypertension in rats. Wistar rats were anesthetized, and hypertension was surgically induced by partial constriction of the left renal artery with a silver clip with a 0.2 mm gap. In one kidney one clip (1K1C) hypertension model, the contralateral kidney was removed. In two kidneys one clip (2K1C) model, the contralateral kidney was kept intact. Sham-operated control rats underwent to same surgical procedures without receiving the clip around the renal artery. After 45 days (2K1C) or 60 days (1K1C), animals were instrumented with a catheter into the femoral artery, and on the following day, their arterial pressure (AP) was directly recorded without the effect of anesthesia. For HRF analysis, pulse interval (PI) series were generated and transformed into a sequence of symbols “-1,” “0,” or “1” when the difference between successive PI values (transitions) was negative, zero, or positive, respectively. Following, sequences of 4 consecutive symbols were classified according to the number of transitions. The total percentage of inflection points (PIP) and the percentage of sequences with zero (W0), one (W1), two (W2), or three (W3) inflection points were quantified. As expected, the arterial pressure increased in both groups of hypertension rats compared to control counterparts. All HRF indices were found similar in 1K1C hypertensive rats compared to their control counterparts. Nevertheless, in 2K1C hypertensive rats HRF was found to be lower than normotensive controls (PIP: 64±7 vs. 79±1% and W2: 30±1 vs. 39±1% in 2K1C and normotensive controls, respectively). In conclusion, high blood pressure itself does not affect HRF, although, depending on the model of hypertension used, HRF can be markedly impaired. The interpretation of these findings is challenging, and the high levels of angiotensin in the 2K1C model may affect cardiac pacemaker cells, making their action potentials more stable than unstable. However, the specific mechanisms by which this could happen still need to be studied. Funding Sources: FAPESP, CAPES and CNPq This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Spectral Efficiency of Time-Variant Massive MIMO Using Wiener Prediction

Massive multiple-input multiple-output (MIMO) serves as technological pillar in current 5G deployments. The spectral efficiency (SE) reduction due to time-variance of the wireless channel, and respective mitigation strategies, are still not sufficiently understood. In this paper, we propose a multi-step Wiener predictor with a general temporal covariance function to quantify the impact of time-variance on the SE for different numbers of consecutive pilot symbols and prediction horizons. We provide asymptotic expressions of the SE for maximum ratio combining (MRC) beam-forming that show excellent agreement to numerical simulations. We investigate the channel hardening capability of massive MIMO systems in time-variant propagation channels and show that it is largely independent of the prediction horizon. The numerical evaluations show that channel prediction allows to double SE utilizing four instead of one uplink pilot symbol for a prediction horizon of 0.3 λ for both MRC and regularized zero-forcing (RZF) beam-forming.

A 12-Gb/s Baud-Rate Clock and Data Recovery With 75% Phase-Detection Probability by Precoding and Integration-Hold-Reset Frontend

This brief describes a 12-Gb/s quarter-rate receiver with a current-integrating baud-rate clock and data recovery (CDR) technique. The proposed CDR receives a pre-encoded non-return-to-zero (NRZ) data stream and integrates with 0.5-UI phase offset to extract the phase information. By sampling three consecutive symbols with multiple thresholds in the proposed phase detector, the CDR achieves a 75% phase-detection probability, which is the highest among baud-rate CDRs and leads to a better tracking bandwidth and jitter tolerance. The 12-Gb/s baud-rate CDR prototype is implemented in a 28 nm CMOS process and consumes 77 mW from a 1.2-V supply.

Cognitive Mechanisms in Temporally Controlled Rhythm Reading

Music-reading research has not yet fully grasped the variety and roles of different cognitive mechanisms that underlie visual processing of music notation; instead, studies have often explored one factor at a time. Based on prior research, we identified three possible cognitive mechanisms regarding visual processing during music reading: symbol comprehension, visual anticipation, and symbol performance demands. We also summed up the eye-movement indicators of each mechanism. We then asked which of the three cognitive mechanisms were needed to explain how note symbols are visually processed during temporally controlled rhythm reading. In our eye-tracking study, twenty-nine participants performed simple rhythm-tapping tasks, in which the relative complexity of consecutive rhythm symbols was systematically varied. Eye-time span (i.e., “looking ahead”) and first-pass fixation time at target symbols were analyzed with linear mixed-effects modeling. As a result, the mechanisms symbol comprehension and visual anticipation found support in our empirical data, whereas evidence for symbol performance demands was more ambiguous. Future studies could continue from here by exploring the interplay of these and other possible mechanisms; in general, we argue that music-reading research should begin to emphasize the systematic creating and testing of cognitive models of eye movements in music reading.

Coordinate Interleaved Faster-Than-Nyquist Signaling

Faster-than-Nyquist (FTN) signaling is an attractive transmission technique which accelerates data symbols beyond the Nyquist rate to improve the spectral efficiency; however, at the expense of higher computational complexity to remove the introduced intersymbol interference (ISI). In this work, we introduce a novel FTN signaling transmission technique, named coordinate interleaved FTN (CI-FTN) signaling that exploits the ISI at the transmitter to generate constructive interference for every pair of the counter-clockwise rotated binary phase shift keying (BPSK) data symbols. In particular, the proposed CI-FTN signaling interleaves the in-phase (I) and the quadrature (Q) components of the counter-clockwise rotated BPSK symbols to guarantee that every pair of consecutive symbols has the same sign, and hence, has constructive ISI. At the receiver, we propose a low-complexity detector that makes use of the constructive ISI introduced at the transmitter. Simulation results show the merits of the CI-FTN signaling and the proposed low-complexity detector compared to conventional Nyquist and FTN signaling.

Nonlinear Impairment Compensation Using Transfer Learning-Assisted Convolutional Bidirectional Long Short-Term Memory Neural Network for Coherent Optical Communication Systems

By combining the nonlinear impairment features derived from the first-order perturbation theory, we propose a nonlinear impairment compensation (NLC) scheme based on the transfer learning-assisted convolutional bidirectional long short-term Memory (CNN-BiLSTM) neural network structure. When considering the correlation of nonlinear impairment between preceding and succeeding consecutive adjacent symbols on the current moment symbol and integrating the multidimensional feature extraction and time memory characteristics of CNN-BiLSTM, the nonlinear impairment information contained in the input feature can be fully utilized to accurately predict the nonlinear impairment showing significant compensation effect. Meanwhile, transfer learning (TL) is introduced to greatly reduce the complexity of the scheme on the basis of high compensation performance. To verify the effectiveness of the proposed scheme, we construct single-channel (SC) and 5-channel 28 GBaud polarization division multiplexing 16 quadrature amplitude modulation (PDM-16QAM)/85 GBaud PDM-64QAM simulation systems, and SC and 3-channel 28 GBaud PDM-16QAM experimental systems. The experimental results show that when compared with simple recurrent neural network (SRNN) NLC and DBP 20 steps per span (DBP20StPs), the Q-factor gain of our scheme is about 1 dB and 1.7 dB in the SC system, and about 1.1 dB and 1.5 dB in the 3-channel system at the optimal launch power, respectively. It is interesting to highlight that, by applying TL to the simulation and experimental systems, our scheme based on only 5% of the training samples can achieve compensation performance comparable to or higher quality than retraining at various launch powers.

Support Vector Machine-Based Soft Decision for Consecutive-Symbol-Expanded 4-Dimensional Constellation in Underwater Visible Light Communication System

Nowadays, underwater visible light communication (UVLC) has become one of the key technologies for high-speed underwater wireless communication. Because of the limited modulation bandwidth and nonlinearity of the optoelectronic devices in the UVLC system, the combination of inter-symbol interference and nonlinear impairment will inevitably degrade the transmission performance. Advanced digital signal processing methods including equalization and decoding are required. In the past few years, Support vector machine (SVM) has been widely investigated in quadrature amplitude modulation (QAM) for soft decision in the decoding process. However, previous works only consider 2-dimensional (2-D) separate symbol, ignoring the correlation between consecutive symbols. In this paper, we propose to use SVM for soft decision with a 4-dimensional (4-D) constellation by concatenating two consecutive symbols. To deal with the increasing computational complexity in the SVM training phase, bit-based binary SVM multi-class strategy and an edge-detection-based data pre-processing method are employed. In this paper, we demonstrate a carrierless amplitude and phase (CAP) 16-QAM UVLC system. Experimental results indicate that the performance is greatly improved when using consecutive-symbol-expanded 4-D constellation with SVM for soft decision.

Intertwined-pulse modulation for compressive data telemetry

This paper presents a novel approach for anisochronous pulse-based modulation. In the proposed approach, referred to as the intertwined-pulse modulation (IPM), every pair of consecutive symbols overlap in time. This allows for shortening the time allocated for the transmission of the symbols, hence achieving temporal compaction while the data goes through the line encoding step in a digital communication system. The IPM is also uniquely superior to other existing anisochronous pulse-based modulation schemes in the fact that it exhibits robust symbol error rate against unwanted variations in both rise/fall times of the pulses in the modulated waveform, and in the threshold level used for data detection on the receiver side. An experimental setup was developed to implement an IPM encoder using standard digital hardware, and an IPM decoder as a part of the receiver system in software. According to the experimental results (supported by simulation results and theoretical studies), for the data mean value of mid-full-scale range, the proposed IPM scheme exhibits a time-domain compaction rate of up to 209.2%.

Deep learning for signal clock and exposure estimation in rolling shutter optical camera communication.

In rolling shutter (RS)-based optical camera communication (OCC) links, selecting the appropriate camera's exposure time is critical, as it limits the reception bandwidth. In long exposures, the pixels accumulate over time the incoming irradiance of several consecutive symbols. As a result, a harmful intersymbol interference corrupts the received signal. Consequently, reducing the exposure time is required to increase the reception bandwidth at the cost of producing dark images with impracticable light conditions for human or machine-supervised applications. Alternatively, deep learning (DL) equalizers can be trained to mitigate the exposure-related ISI. These equalizers must be trained considering the transmitter clock and the camera's exposure, which can be exceptionally challenging if those parameters are unknown in advance (e.g., if the camera does not reveal its internal settings). In those cases, the receiver must estimate those parameters directly from the images, which are severely distorted by the exposure time. This work proposes a DL estimator for this purpose, which is trained using synthetic images generated for thousands of representative cases. This estimator enables the receiver operation under multiple possible configurations, regardless of the camera used. The results obtained during the validation, using more than 7000 real images, registered relative errors lower than 1% and 2% when estimating the transmitter clock and the exposure time, respectively. The obtained errors guarantee the optimal performance of the following equalization and decoding receiver stages, keeping bit error rates below the forward error correction limit. This estimator is a central component of any OCC receiver that operates over moderate exposure conditions. It decouples the reception routines from the cameras used, ultimately enabling cloud-based receiver architectures.

Generalized Receiver Designs for OFDM Systems with Alamouti Decoding in Fast Fading Channels

In the present paper, the generalized receiver designs for orthogonal frequency-division multiplex-ing (OFDM) systems that exploit the Alamouti transmit diversity technique are addressed. In Alamouti space-time coded OFDM systems, the simple Alamouti decoding at the generalized receiver relies on the assumption that the channels do not change over an Alamouti codeword period (two consecutive OFDM symbol periods). Unfortunately, when the channel is fast fading, the assumption is not met, resulting in severe performance deg-radation. In the present paper, a sequential decision feedback sequence estimation (SDFSE) scheme based on the generalized receiver with an adaptive threshold, a traditionally single-carrier equalization technique, is used to mitigate the performance degradation. A new method to set the threshold value is proposed. For small signal constellations like binary phase-shift keying (BPSK) and quadrature phase shift-keying (QPSK), the SDFSE generalized receiver with the adaptive threshold requires much lower complexity than a previous minimum me-an square error (MMSE) approach based on the generalized receiver at the cost of small performance degradati-on. Furthermore, we show that the performance difference becomes smaller when the channel estimation error is included. Adaptive effort sequence estimation (AESE) scheme based on the generalized receiver is also pro-posed to further reduce the average complexity of the SDFSE generalized receiver scheme with the adaptive threshold. The AESE generalized receiver scheme is based on the observation that a high Doppler frequency does not necessarily mean significant instantaneous channel variations. Simulations demonstrate the efficacy of the proposed SDFSE generalized receiver with the adaptive threshold and AESE generalized receiver schemes.

Heart Rate Fragmentation in Rats with Streptozotocin‐induced Diabetes

Heart rate fragmentation (HRF) is a recently proposed approach to evaluate sino‐atrial instability characterized by the presence of numerous inflections points in a series of successive values of RR intervals (RRi). HRF has been shown to be increased in aging and coronary diseases and seems to be linked to the risk of life‐threatening cardiovascular events and death. We recently demonstrated that cardiac autonomic modulation in involved in HRF in rats. Moreover, HRF is increased in a rat model of heart failure. Diabetes mellitus (DM) markedly alters HRV indices and might affect HRF as well. Therefore, we hypothesize that HRF is altered in streptozotocin‐ (STZ) induced diabetic rats. Male Sprague‐Dawley rats were injected with STZ (50 mg/kg), or vehicle (citrate buffer) into penile vein. Development of diabetes was confirmed 72h after STZ by the presence of hyperglycemia (> 350 mg/dL). Electrocardiographic (ECG) recordings were performed in conscious rats, 7 days (acute) or 4 weeks (chronic) after STZ or vehicle administration. Series of RR intervals were generated and processed by the customized software PyBios as follows: RRi values were symbolized as “‐1”, “0,” or “1” when the differences between successive RRi were negative, null, or positive, respectively. Transitions between symbols “‐1” and “1” were labeled as “hard” (H) inflection points, while those between “‐1” (or “1”) and “0” were labeled as “soft” (S) inflection points. The percentage of inflection points (PIP) was quantified, as well as sequences of 4 consecutive symbols, so‐called “words”, computing the occurrence of words with zero (W0), one (W1), two (W2), or three (W3) inflections points. The occurrence of words with only hard (WH) or only soft transitions (WS) were also quantified. Both groups of diabetic rats were bradycardic as compared to their control counterparts. Data of HRF are shown in the table below. Occurrences (%, mean ± SEM) of PIP, words with 0 to 3 inflection points, and words with only soft or hard transitions of symbols. As hypothesized, diabetes affects HRF, increasing fragmented indices (PIP, W3 and WH) and decreasing fluent ones (W1 and WS). Moreover, our results showed that changes in HRF due to diabetes in this model is time‐dependent. In addition to traditional methods of analyzing heart rate variability, HRF is a new method that can contribute to the diagnosis and prognosis of cardiovascular diseases in diabetic patients. Further studies are necessary to understand better the mechanisms involved in our findings.

Heart Rate Fragmentation in Patients with Type 2 Diabetes Mellitus

Heart rate fragmentation (HRF) is a recently proposed approach to evaluate ultra‐rapid variability of heart rate. HRF has been shown to be increased in the aging process and in conditions such as coronary artery disease. Moreover, it proved to be a strong biomarker of adverse cardiovascular events, mortality and was an independent predictor of atrial fibrillation. Type 2 diabetes mellitus (DM) is a disease known to affect heart rate variability (HRV) indices markedly; however, HRF in diabetic patients is to be studied. We aimed to evaluate HRF in patients with DM, without autonomic cardiovascular neuropathy, compared to their healthy counterparts. Electrocardiographic (ECG) recordings collected from patients with diabetes (n=102) and healthy subjects (n=96), aged 44 to 59 years, were retrospectively analyzed from the Cardiovascular Physical Therapy Laboratory database. ECG were recorded at rest (supine) for 10 to 15 minutes. RR interval (RRi) series were processed by the customized software PyBios. RRi values were symbolized as “‐1”, “0,” or “1” when the differences between successive RRi were negative, null, or positive, respectively. The percentage of inflection points (PI) was quantified and sequences of 4 consecutive symbols, so‐called “words”, were analyzed computing the occurrence of words with zero (W0), one (W1), two (W2), or three (W3) inflections points. The occurrence of words with only hard (‐1 to 1: WH), soft (‐1 to 0 or 0 to 1: WS), or mixed (WM) (i.e., both H and S) transitions were also quantified. Patients with diabetes presented higher PIP (58±1 vs 56±1, p=0.033), W3(17±1 vs14±1, p<0.001), WS(25±2 vs16±1, p<0.001) and WM(22±1 vs 17±1, p<0.001). On the other hand, patients with diabetes showed a lower percentage of W1 (31±1 vs 35±1, p=0.024) and WH (47±2 vs 61±2, p<0.001). The occurrence of W0 and W2 were similar between groups. In conclusion, diabetics patients without autonomic cardiovascular neuropathy have augmented fragmentation of heart rate as compared to healthy subjects. Clinical applicability: In the future, studies with this approach might be useful to assess heart rate dynamic abnormalities in order to detect cardiac risks in patients with diabetes mellitus.

Performance Analysis of Low Power Interference Cancellation Architecture for OFDM System

Orthogonal Frequency Division Multiplexing (OFDM) is a wireless communication technology that is used for highly reliable and high data rate communication. In a multi-user OFDM system, the interference has occurred in the receiver side between the consecutive OFDM symbols. This interference reduces the performance of the OFDM system. To achieve good quality in received symbols the interference level should be minimized. The conventional cancellation system requires higher interference reduction time and power. These limitations of the conventional interference cancellation architectures for OFDM systems are overcome by proposing efficient and low power interference cancellation architecture. Hence, this paper proposes a novel and efficient architecture based on logic gates for interference cancellation in multi-user OFDM systems. The proposed design consist of multiplexers, inverters and OR gate. The heuristic parameters for the proposed cancellation architecture are computed by performing an XOR operation. Compared to existing architecture, the proposed interference cancellation architecture consumes 7 mW of power consumption in the Virtex processor, 33.59 mW of power consumption in Spartan 3E processor and 0.029 mW of power consumption in the CPLD processor. This proposed interference cancellation architecture consumes fewer hardware resources and consumes low power. The proposed system is designed using Verilog High Definition Language (HDL) and synthesized in Xilinx Project Navigator 12.1i. Further, this paper also proposes gate diffusion input (GDI) based implementation of proposed interference cancellation architecture to analyse a delay and power consumption compared to other logic style implementation.

Phase Noise Resilient Three-Level Continuous-Phase Modulation for DFT-Spread OFDM

In this paper, a novel waveform with low peak-to-average power ratio (PAPR) and high robustness against phase noise (PN) is presented. It follows the discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM) signal model. This scheme, called 3MSK, is inspired by continuous-phase frequency shift keying (CPFSK), but it uses three frequencies in the baseband model – specifically, 0 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm f_{symbol}/4$ </tex-math></inline-formula> , where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$f_{symbol}$ </tex-math></inline-formula> is the symbol rate – which effectively constrains the phase transitions between consecutive symbols to 0 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm \pi /2$ </tex-math></inline-formula> rad. Motivated by the phase controlled model of modulation, different degrees of phase continuity can be achieved, allowing to reduce the out-of-band (OOB) emissions of the transmitted signal, while supporting receiver processing with low complexity. Furthermore, the signal characteristics are improved by generating an initial time-domain constant envelope signal at higher than the symbol rate. This helps to reach smooth phase transitions between 3MSK symbols, while the information is encoded in the phase transitions. Also the possibility of using excess bandwidth is investigated by transmitting additional non-zero frequency bins outside the active frequency bins of the basic DFT-s-OFDM model, which provides the capability to greatly reduce the PAPR. The most critical tradeoffs of the oversampled schemes are that improved PAPR is achieved with the cost of somewhat reduced link performance and, in case of excess band, also the spectrum efficiency is reduced. Due to the fact that the information is encoded in the phase transitions, a receiver model that tracks the phase variations without needing reference signals is developed. To this end, it is shown that this new modulation is well-suited for non-coherent receivers, even under strong phase noise (PN) conditions, thus allowing to reduce the overhead of reference signals. Evaluations of this physical-layer modulation and waveform scheme are performed in terms of transmitter metrics such as PAPR, OOB emissions and achievable output power after the power amplifier (PA), using a practical PA model. Finally, coded radio link evaluations are also provided, demonstrating that 3MSK has a similar bit error rate (BER) performance as that of traditional quadrature phase-shift keying (QPSK), but with significantly lower PAPR, higher achievable output power, and the possibility of using non-coherent receivers.

Statistics-Based Chain Code Compression with Decreased Sensitivity to Shape Artefacts

Chain codes compactly represent raster curves, but there is still a lot of room for improvement by means of data compression. Several statistics-based chain code compression techniques assign shorter extra codes to frequent pairs of consecutive symbols. Here we systematically extend this concept to patterns of up to six symbols. A curve may be represented by any of the exponentially many overlapped chains of codes, and the dynamic programming approach is proposed to determine the optimal chain. We also propose utilization of multiple averaged hard coded pseudo-statistical models, since the exact statistical models of individual curves are often huge, and they can also significantly differ from each other. A competitive compression efficiency is assured in this manner and, as a pleasant side effect, this efficiency is less affected by the curve’s shape, rasterization algorithm, noise, and image resolution, than in other contemporary methods, which surprisingly do not pay any attention to this problem at all.