Spectral Sensing for Cognitive Radio: Estimation of Adaptive Frequency Hopping Signal

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Method for obtaining minimum noise in a general purpose hot wire amplifier

It has been shown that the conventional practice of designing a compensated hot wire amplifier with a fixed ceiling to floor ratio results in considerable and unnecessary increase in noise level at compensation settings other than optimum (which is at the maximum compensation at the highest frequency of interest). The optimum ceiling to floor ratio has been estimated to be between 1.5-2.0 ωmaxM. Application of the above considerations to an amplifier in which the ceiling to floor ratio is optimized at each compensation setting (for a given amplifier band-width), shows the usefulness of the method in improving the signal to noise ratio.

Spectral Sensing of Adaptive Frequency Hopping Signal for Cognitive Radio

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Antenna Selection Training in MIMO-OFDM/OFDMA Cellular Systems

Antenna selection allows multiple-antenna systems to achieve most of their promised diversity gain, while keeping the number of RF chains and, thus, cost/complexity low. In this paper we investigate antenna selection for fourth-generation OFDMA- based cellular communications systems, in particular, 3GPP LTE (long-term evolution) systems. We propose a training method for antenna selection that is especially suitable for OFDMA. By means of simulation, we evaluate the SNR-gain that can be achieved with our design. We find that the performance depends on the bandwidth assigned to each user, the scheduling method (round-robin or frequency-domain scheduling), and the Doppler spread. Furthermore, the signal-to-noise ratio of the training sequence plays a critical role. Typical SNR gains are around 2 dB, with larger values obtainable in certain circumstances.

A Huber-loss-driven clustering technique and its application to robust cell detection in confocal microscopy images

We address the problem of detecting cells in biological images. The problem is important in many automated image analysis applications. We identify the problem as one of clustering and formulate it within the framework of robust estimation using loss functions. We show how suitable loss functions may be chosen based on a priori knowledge of the noise distribution. Specifically, in the context of biological images, since the measurement noise is not Gaussian, quadratic loss functions yield suboptimal results. We show that by incorporating the Huber loss function, cells can be detected robustly and accurately. To initialize the algorithm, we also propose a seed selection approach. Simulation results show that Huber loss exhibits better performance compared with some standard loss functions. We also provide experimental results on confocal images of yeast cells. The proposed technique exhibits good detection performance even when the signal-to-noise ratio is low.

Gradient echo single scan inversion recovery: application to proton and fluorine relaxation studies

Single scan longitudinal relaxation measurement experiments enable rapid estimation of the spin-lattice relaxation time (T-1) as the time series of spin relaxation is encoded spatially in the sample at different slices resulting in an order of magnitude saving in time. We consider here a single scan inversion recovery pulse sequence that incorporates a gradient echo sequence. The proposed pulse sequence provides spectra with significantly enhanced signal to noise ratio leading to an accurate estimation of T-1 values. The method is applicable for measuring a range of T-1 values, thus indicating the possibility of routine use of the method for several systems. A comparative study of different single scan methods currently available is presented, and the advantage of the proposed sequence is highlighted. The possibility of the use of the method for the study of cross-correlation effects for the case of fluorine in a single shot is also demonstrated. Copyright (C) 2015 John Wiley & Sons, Ltd.

Gradient echo single scan inversion recovery: application to proton and fluorine relaxation studies

Single scan longitudinal relaxation measurement experiments enable rapid estimation of the spin-lattice relaxation time (T-1) as the time series of spin relaxation is encoded spatially in the sample at different slices resulting in an order of magnitude saving in time. We consider here a single scan inversion recovery pulse sequence that incorporates a gradient echo sequence. The proposed pulse sequence provides spectra with significantly enhanced signal to noise ratio leading to an accurate estimation of T-1 values. The method is applicable for measuring a range of T-1 values, thus indicating the possibility of routine use of the method for several systems. A comparative study of different single scan methods currently available is presented, and the advantage of the proposed sequence is highlighted. The possibility of the use of the method for the study of cross-correlation effects for the case of fluorine in a single shot is also demonstrated. Copyright (C) 2015 John Wiley & Sons, Ltd.

Defect-selective photothermal imaging: a sensitive tool for damage mapping in optical coatings

A defect-selective photothermal imaging system for the diagnostics of optical coatings is demonstrated. The instrument has been optimized for pump and probe parameters, detector performance, and signal processing algorithm. The imager is capable of mapping purely optical or thermal defects efficiently in coatings of low damage threshold and low absorbance. Detailed mapping of minor inhomogeneities at low pump power has been achieved through the simultaneous action of a low-noise fiber optic photothermal beam defection sensor and a common-mode-rejection demodulation (CMRD) technique. The linearity and sensitivity of the sensor have been examined theoretically and experimentally, and the signal to noise ratio improvement factor is found to be about 110 compared to a conventional bicell photodiode. The scanner is so designed that mapping of static or shock sensitive samples is possible. In the case of a sample with absolute absorptance of 3.8 x 10(-4), a change in absorptance of about 0.005 x 10(-4) has been detected without ambiguity, ensuring a contrast parameter of 760. This is about 1085% improvement over the conventional approach containing a bicell photodiode, at the same pump power. The merits of the system have been demonstrated by mapping two intentionally created damage sites in a MgF2 coating on fused silica at different excitation powers. Amplitude and phase maps were recorded for thermally thin and thick cases, and the results are compared to demonstrate a case which, in conventional imaging, would lead to a deceptive conclusion regarding the type and location of the damage. Also, a residual damage profile created by long term irradiation with high pump power density has been depicted.

Two Methods of Ambiguity Resolution in Pulse Doppler Weather Radars

A comparison is made of the performance of a weather Doppler radar with a staggered pulse repetition time and a radar with a random (but known) phase. As a standard for this comparison, the specifications of the forthcoming next generation weather radar (NEXRAD) are used. A statistical analysis of the spectral momentestimates for the staggered scheme is developed, and a theoretical expression for the signal-to-noise ratio due to recohering-filteringrecohering for the random phase radar is obtained. Algorithms for assignment of correct ranges to pertinent spectral moments for both techniques are presented.

Implementation of a modified CVSD coder

This paper describes the implementation of the modified continuously variable slope delta modulator (MCVSD), in which the basic step size δ0 is made to vary as a function of input signal level. The information needed to carry out this is extracted at the local decoder output so that the coder and the decoder track each other. The result is a significant improvement in the dynamic range (about 15dB) as compared to CVSD coder without degrading the peak signal to noise ratio.

A solid state pulsed NMR spectrometer

A 10 MHz pulsed NMR spectrometer, built using mostly solid state devices, is described. The pulse programmer provides 2-pulse, 3-pulse, saturation burst and Carr-Purcell sequences both in repetitive and manual modes of operation. The transmitter has a maximum power output of ∼ 2 kW with a 75 Ω output impedance termination. The total gain of the receiver system is around 120 dB with a minimum band width of 2 MHz. The recovery time of the receiver is ∼ 7 µsec. A two-channel boxcar integrator capable of working in the single channel, differential and double boxcar modes provides signal to noise ratio improvement. The sensitivity and the linearity of the boxcar integrator are ∼ 2 mV and ∼ 0.1% respectively.

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

ANC schemes for the enhancement of EEG signals in the presence of EOG artifacts

One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

Performance Analysis of Reconstruction Techniques for Frequency-Domain Optical-Coherence Tomography

We address the issue of noise robustness of reconstruction techniques for frequency-domain optical-coherence tomography (FDOCT). We consider three reconstruction techniques: Fourier, iterative phase recovery, and cepstral techniques. We characterize the reconstructions in terms of their statistical bias and variance and obtain approximate analytical expressions under the assumption of small noise. We also perform Monte Carlo analyses and show that the experimental results are in agreement with the theoretical predictions. It turns out that the iterative and cepstral techniques yield reconstructions with a smaller bias than the Fourier method. The three techniques, however, have identical variance profiles, and their consistency increases linearly as a function of the signal-to-noise ratio.