An Efficient Data-aided Synchronization in L-DACS1 for Aeronautical Communications

L-band Digital Aeronautical Communication System type-1 (L-DACS1) is an emerging standard that aims at enhancing air traffic management (ATM) by transitioning the traditional analog aeronautical communication systems to the superior and highly efficient digital domain. L-DACS1 employs modern and efficient orthogonal frequency division multiplexing (OFDM) modulation technique to achieve more efficient and higher data rate in comparison to the existing aeronautical communication systems. However, the performance of OFDM systems is very sensitive to synchronization errors. L-DACS1 transmission is in the L-band aeronautical channels that suffer from large interference and large Doppler shifts, which makes the synchronization for L-DACS more challenging. This paper proposes a novel computationally efficient synchronization method for L-DACS1 systems that offers robust performance. Through simulation, the proposed method is shown to provide accurate symbol timing offset (STO) estimation as well as fractional carrier frequency offset (CFO) estimation in a range of aeronautical channels. In particular, it can yield excellent synchronization performance in the face of a large carrier frequency offset.Comment: In the proceeding of International Conference on Data Mining, Communications and Information Technology (DMCIT

Automatic modulation classification for cognitive radios using cumulants based on fractional lower order statistics

Automatic modulation classification (AMC) finds various applications in cognitive radios. This paper presents a method for the automatic classification using cumulants derived using fractional lower order statistics. The performance of the classifier is presented in the form of probability of correct classification under noisy and fading conditions. Unlike many of the conventional methods, the proposed method does not require a priori knowledge of signal parameters. The proposed method is also more robust to different noises. Simulation results show that the proposed method can achieve better classification accuracy when compared to conventional cumulant based AMC method, in various impulsive noise conditions. 1

Design and Implementation of Low Complexity Reconfigurable Filtered-OFDM based LDACS

L-band Digital Aeronautical Communication System (LDACS) aims to exploit vacant spectrum in L-band via spectrum sharing, and orthogonal frequency division multiplexing (OFDM) is the currently accepted LDACS waveform. Recently, various works dealing with improving the spectrum utilization of LDACS via filtering/windowing are being explored. In this direction, we propose an improved and low complexity reconfigurable filtered OFDM (LRef-OFDM) based LDACS using novel interpolation and masking based multi-stage digital filter. The proposed filter is designed to meet the stringent non-uniform spectral attenuation requirements of LDACS standard. It offers significantly lower complexity as well as higher transmission bandwidth than state-of-the-art approaches. We also integrate the proposed filter in our end-to-end LDACS testbed realized using Zynq System on Chip and analyze the performance in the presence of $L$-band legacy user interference as well as LDACS specific wireless channels. Via extensive experimental results, we demonstrate the superiority of the proposed LRef-OFDM over OFDM and Filtered-OFDM based LDACS in terms of power spectral density, bit error rate, implementation complexity, and group delay parameters.Comment: Paper with Appendi

Association of proinflammatory cytokines and chemotherapy-associated cognitive impairment in breast cancer patients: a multi-centered, prospective, cohort study.

BackgroundExisting evidence suggests that proinflammatory cytokines play an intermediary role in postchemotherapy cognitive impairment. This is one of the largest multicentered, cohort studies conducted in Singapore to evaluate the prevalence and proinflammatory biomarkers associated with cognitive impairment in breast cancer patients.Patients and methodsChemotherapy-receiving breast cancer patients (stages I-III) were recruited. Proinflammatory plasma cytokines concentrations [interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, IL-10, granulocyte-macrophage colony-stimulating factor, interferon-γ and tumor necrosis factor-α] were evaluated at 3 time points (before chemotherapy, 6 and 12 weeks after chemotherapy initiation). The FACT-Cog (version 3) was utilized to evaluate patients' self-perceived cognitive disturbances and a computerized neuropsychological assessment (Headminder) was administered to evaluate patients' memory, attention, response speed and processing speed. Changes of cognition throughout chemotherapy treatment were compared against the baseline. Linear mixed-effects models were applied to test the relationships of clinical variables and cytokine concentrations on self-perceived cognitive disturbances and each objective cognitive domain.ResultsNinety-nine patients were included (age 50.5 ± 8.4 years; 81.8% Chinese; mean duration of education = 10.8 ± 3.3 years). Higher plasma IL-1β was associated with poorer response speed performance (estimate: -0.78; 95% confidence interval (CI) -1.34 to -0.03; P = 0.023), and a higher concentration of IL-4 was associated with better response speed performance (P = 0.022). Higher concentrations of IL-1β and IL-6 were associated with more severe self-perceived cognitive disturbances (P = 0.018 and 0.001, respectively). Patients with higher concentrations of IL-4 also reported less severe cognitive disturbances (P = 0.022).ConclusionsWhile elevated concentrations of IL-6 and IL-1β were observed in patients with poorer response speed performance and perceived cognitive disturbances, IL-4 may be protective against chemotherapy-associated cognitive impairment. This study is important because cytokines would potentially be mechanistic mediators of chemotherapy-associated cognitive changes

A cyclic prefix assisted spectrum sensing method for aeronautical communication systems

Continuous growth of air-traffic demands new technologies for future aeronautical communication systems. L-band Digital Aeronautical Communications System (LDACS) is considered as a potential candidate for the future air-to-ground links. Spectrum utilization efficiency of LDACS can be improved by enabling dynamic spectrum access (DSA) in the system. In this context, the present paper proposes a novel cyclostationary feature detection scheme based on the periodicity of the autocorrelation of LDACS signals for spectrum sensing, which is key requirement in DSA. A wideband spectrum sensing simulation model is developed to evaluate the detection performance of the proposed scheme. To improve the adaptability of the spectrum sensing unit to variable wide bandwidth, the proposed system uses interpolation and masking based filters that can extract individual LDACS channels from the wide-band signals. Results of simulation studies show that the proposed scheme provides better detection accuracy against the conventional cyclostationary feature detection scheme and energy detection scheme, while maintaining the false alarm rates to an acceptable level which balances the overall throughput of the system.Accepted versio

Unconventional techniques of fundus imaging: A review

The methods of fundus examination include direct and indirect ophthalmoscopy and imaging with a fundus camera are an essential part of ophthalmic practice. The usage of unconventional equipment such as a hand-held video camera, smartphone, and a nasal endoscope allows one to image the fundus with advantages and some disadvantages. The advantages of these instruments are the cost-effectiveness, ultra portability and ability to obtain images in a remote setting and share the same electronically. These instruments, however, are unlikely to replace the fundus camera but then would always be an additional arsenal in an ophthalmologist's armamentarium

A power-efficient spectrum-sensing scheme using 1-bit quantizer and modified filter banks

Spectrum sensing is an efficient way to determine the spectrum availabilities over the frequency range of interest, aiding in improving the spectrum utilization in the cognitive radio (CR) systems. Conventional Nyquist multiband sensing entails higher computational capability for sampling, quantization, and subsequent processing, lending the approach infeasible for applications with limited power budgets. In this brief, a power-efficient spectrum-sensing technique is proposed, which explores an accuracy-complexity tradeoff. The presented spectrum-sensing architecture is based on 1-bit quantization at the CR receiver and implements it in hardware by a resource- and power-efficient approach, using a finite-impulse-response (FIR) filter-bank channelizer. The proposed scheme allows the complex operators like multipliers and quantizers to be replaced by the inverter logic and high-speed comparators, reducing the hardware complexity and power consumption. We validate the proposed scheme on a field-programmable gate-array (FPGA) emulator for an aeronautical L-band digital aeronautical communication system (LDACS) application, and our results show that the proposed scheme achieves substantial resource reduction with at most 5% degradation in the detection accuracy in this case.Accepted versio

An adaptive energy detection scheme with real-time noise variance estimation

Energy detection-based spectrum sensing techniques are ideally suited for power-constrained cognitive radio applications because of their lower computational complexity compared to feature detection techniques. However, their detection performance is dependent on multiple factors like accuracy of noise variance estimation and signal-to-noise ratio (SNR). Many variations of energy detection techniques have been proposed to address these challenges; however, they achieve the desired detection accuracy at the cost of increased computational complexity. This restricts the use of enhanced energy detection schemes in power-constrained applications such as aeronautical communication. In this paper, an adaptive low-complexity energy detection scheme is proposed for spectrum sensing in an L-band Digital Aeronautical Communication System (LDACS) at lower SNR levels. Our scheme uses a real-time noise variance estimation technique using autocorrelation which is induced by the cyclic prefix property in LDACS signals. The proposed technique does not incur dedicated hardware blocks for noise variance estimation, leading to an efficient hardware implementation of the scheme without significant resource overheads. The simulation studies of the proposed scheme show that the desired accuracy (90% detection accuracy with only 10% of false alarms) can be achieved even at −16.5 dB SNR, significantly lowering the SNR wall over existing energy detection schemes.Accepted versio