To Achieve Security and High Spectrum Efficiency: A New Transmission System Based on Faster-than-Nyquist and Deep Learning

With the rapid development of various services in wireless communications, spectrum resource has become increasingly valuable. Faster-than-Nyquist (FTN) signaling, which was proposed in the 1970s, has been a promising paradigm to improve the spectrum utilization. In this paper, we try to apply FTN into secure communications and propose a secure and high-spectrum-efficiency transmission system based on FTN and deep learning (DL). In the proposed system, the hopping symbol packing ratio with random values makes it difficult for the eavesdropper to obtain the accurate symbol rate and inter-symbol interference (ISI). While the receiver can use the blind estimation to choose the true parameters with the aid of DL. The results show that without the accurate symbol packing ratio, the eavesdropper will suffer from severe performance degradation. As a result, the system can achieve a secure transmission with a higher spectrum efficiency. Also, we propose a simplified symbol packing ratio estimation which has bee employed in our proposed system. Results show that the proposed simplified estimation achieves nearly the same performance as the original structure while its complexity has been greatly reduced

Blind parameter estimation of M-FSK signals in the presence of alpha-stable noise

Blind estimation of parameters for M-ary frequency-shift-keying (M-FSK) signals is great of importance in intelligent receivers. Many existing algorithms have assumed white Gaussian noise. However, their performance severely degrades when grossly corrupted data, i.e., outliers, exist. This paper solves this issue by developing a novel approach for parameter estimation of M-FSK signals in the presence of alpha-stable noise. Specifically, the proposed method exploits the generalized first- and second-order cyclostationarity of M-FSK signals with alpha-stable noise, which results in closed-form solutions for unknown parameters in both time and frequency domains. As a merit, it is computationally efficient and thus can be used for signal preprocessing, symbol timing estimation, signal and noise power estimation. Furthermore, substantial theoretical analysis on the performance of the proposed approach is provided. Simulations demonstrate that the proposed method is robust to alpha-stable noise and that it outperforms the state-of-the-art algorithms in many challenging scenarios

Modified Cramer-Rao bound for M-FSK signal parameter estimation in Cauchy and Gaussian noise

The Cramer-Rao bound (CRB) provides an efficient standard for evaluating the quality of standard parameter estimators. In this paper, a modified Cramer-Rao bounds (MCRB) for modulation parameter estimations of frequency-shift-keying (FSK) signals is proposed under the condition of the Gaussian and non-Gaussian additive interference. We extend the MCRB to the estimation of a vector of non-random parameters in the presence of nuisance parameters. Moreover, the MCRB is applied to the joint estimation of phase offset, frequency offsets, frequency deviation, and symbol period of FSK signal with two important special cases of alpha stable distributions, namely, the Cauchy and the Gaussian. The extensive simulation studies are conducted to contrast the MCRB for the modulation parameter vector in different noise environments

Reliable detection of transmit-antenna number for MIMO systems in cognitive radio-enabled Internet of Things

Identification of transmit-antenna number is of importance in cognitive Internet of Things with multiple-input multiple-output (MIMO). Previous studies on transmit-antenna number detection only consider Gaussian noise and ignore impulsive interference. In the practical wireless communication, impulsive interference may exist due to low-frequency atmospheric noise, multiple access and electromagnetic disturbance. Such interference can usually be modeled as symmetric alpha stable (SαS), which cause the performance degradation of conventional algorithms based on Gaussian model. In this paper, we present a novel scheme to detect the transmit-antenna number for MIMO systems in cognitive Internet of Things, assuming that signals are corrupted by both SαS interference and Gaussian noise. We first introduce a new approach to characterize the generalized correlation matrix, and provide its bound with SαS interference. Then, the discriminating feature vector is constructed by utilizing the higher-order moments (HOM) of eigenvalues of the generalized correlation matrix. Finally, an advanced clustering algorithm is employed to detect the transmit-antenna number, using the cluster where the minimum eigenvalue is located. The proposed algorithm avoids the need for a priori information about the transmitted signals, such as coding mode, modulation type and pilot patterns. Simulation experiments demonstrate the feasibility of the proposed transmit-antenna number detection scheme in MIMO systems with Gaussian noise and SαS interference

Development and Validation of Early Death Risk Score Model for Emergency Status Prediction in Very Severe Aplastic Anemia

This study developed and validated the Early Death Risk Score Model for early identification of emergency patients with very severe aplastic anemia (VSAA). All 377 patients with VSAA receiving first-line immunosuppressive therapy (IST) were categorized into training (n=252) and validation (n=125) cohorts. In the training cohort, age \u3e24 years, absolute neutrophil count ≤0.015×109/L, serum ferritin \u3e900ng/mL and times of fever before IST \u3e1 time were significantly associated with early death. Covariates were assigned scores and categorized as: low (score 0-4), medium (score 5-7) and high (score ≥8) risk. Early death rate was significantly different between risk groups and the validation cohort results were consistent with those of the training cohort. The area under the receiver operating characteristic curve for the model was 0.835 (0.734,0.936) in the training cohort and 0.862 (0.730,0.994) in the validation cohort. The calibration plots showed high agreement, and decision curve analysis showed good benefit in clinical applications. The VSAA Early Death Risk Score Model can help with early identification of emergency VSAA and optimize treatment strategies. Emergency VSAA with high risk is associated with high early death rate, and alternative donor hematopoietic stem cell transplantation could be a better treatment than IST even without HLA-matching

Antihuman T Lymphocyte Porcine Immunoglobulin Combined With Cyclosporine As First-Line Immunosuppressive Therapy for Severe Aplastic Anemia in China: A Large Single-Center, 10-Year Retrospective Study

BACKGROUND: Antihuman T lymphocyte porcine immunoglobulin (p-ATG) has been the most common ATG preparation in immunosuppressive therapy (IST) in Chinese patients with severe aplastic anemia (SAA) since 2009. OBJECTIVES: This study aimed to evaluate the early hematologic response and long-term outcomes of a large cohort of patients with SAA who received p-ATG plus cyclosporine (CsA) as first-line therapy from 2010 to 2019. DESIGN: This is a single-center retrospective study of medical records. METHODS: We analyzed the data of 1023 consecutive patients with acquired aplastic anemia (AA) who underwent p-ATG combined with CsA as a first-line IST treatment from 2010 to 2019 at our department. RESULTS: The median age of the patients was 24 (4-75) years, and the median follow-up time was 57.2 months (3 days-137.5 months). There was an early mortality rate of 2.8% with a median death time of 0.9 months (3 days-2.9 months). The overall response rates were 40.6% and 56.1% at 3 and 6 months, respectively. The 5-year cumulative incidences of relapse and clonal evolution were 9.0% [95% confidence interval (CI) = 4.2-16.0%] and 4.5% (95% CI = 1.4-10.6%), respectively. The 5-year overall survival (OS) and event-free survival rates were 83.7% (95% CI = 81.1-86.0%) and 50.4% (95% CI = 47.1-53.5%), respectively. CONCLUSION: p-ATG combined with CsA for the treatment of AA is effective and safe, and p-ATG can be used as an alternative ATG preparation for the standard IST regimen in areas in which h-ATG is not available

P783 Clinical, Humanistic, and Economic Burden in Patients with PNH Receiving C5 Inhibition Treatment across UK, Germany, and France. Insights from the Commodore Burden of Illness Study

Paroxysmal nocturnal hemoglobinuria (PNH) is a rare, life-threatening blood disorder. In the UK, Germany, and France, C5 complement inhibitors, such as eculizumab and ravulizumab, both of which are intravenously (IV) infused, are the standard of care for PNH

Transmit antenna number identification for MIMO cognitive radio systems in the presence of Alpha-Stable noise

Identification of communication parameters, a major task of intelligent receivers, has important applications in intelligent systems, especially cognitive radio systems. Multiple antennas make the identification problem more challenging. In this paper, we focus on the problem of detecting the number of transmit antennas in multiple-input multiple-output (MIMO) cognitive radio systems. A novel identification algorithm is proposed to determine the number of transmit antennas for MIMO systems in the presence of alpha-stable noise. We first introduce the correlation matrix based on the fractional lower order statistics (FLOS) and provide a particular structure of FLOS-based correlation matrix. Then, the eigenvalues of the FLOS-based correlation matrix are employed to construct a test statistic and the central limit theorem is exploited to obtain the decision threshold. Finally, the transmit-antenna number is detected using a serial binary hypothesis test. Simulation results are demonstrated to evaluate the effectiveness of the proposed transmit-antenna number detection algorithm for MIMO systems in the presence of alpha-stable noise