Analysis of distributed beamforming in cooperative communications network with phase shifter based smart antenna nodes

This research study investigates the application of phase shifter-based smart antenna system in distributed beamforming. It examines the way to optimise the transmit power by jointly maximising the directivity of the array antennas and the weight vector for distributed beamforming. This research study concludes that maximising directivity can lead to better transmit power minimisation compared to maximising field intensity. This study also concludes that signal to noise power ratio maximisation subject to a power constraint and power minimisation subject to a signal to noise power ratio constraint yield the same results.

Experimental evaluation of the performance of 2×2 MIMO-OFDM for vehicle-to-infrastructure communications

In this paper, a novel 2×2 multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) testbed based on an Analog Devices AD9361 highly integrated radio frequency (RF) agile transceiver was specifically implemented for the purpose of estimating and analyzing MIMO-OFDM channel capacity in vehicle-to-infrastructure (V2I) environments using the 920 MHz industrial, scientific, and medical (ISM) band. We implemented two-dimensional discrete cosine transform-based filtering to reduce the channel estimation errors and show its effectiveness on our measurement results. We have also analyzed the effects of channel estimation error on the MIMO channel capacity by simulation. Three different scenarios of subcarrier spacing were investigated which correspond to IEEE 802.11p, Long-Term Evolution (LTE), and Digital Video Broadcasting Terrestrial (DVB-T)(2k) standards. An extensive MIMO-OFDM V2I channel measurement campaign was performed in a suburban environment. Analysis of the measured MIMO channel capacity results as a function of the transmitter-to-receiver (TX-RX) separation distance up to 250 m shows that the variance of the MIMO channel capacity is larger for the near-range line-of-sight (LOS) scenarios than for the long-range non-LOS cases, using a fixed receiver signal-to-noise ratio (SNR) criterion. We observed that the largest capacity values were achieved at LOS propagation despite the common assumption of a degenerated MIMO channel in LOS. We consider that this is due to the large angular spacing between MIMO subchannels which occurs when the receiver vehicle rooftop antennas pass by the fixed transmitter antennas at close range, causing MIMO subchannels to be orthogonal. In addition, analysis on the effects of different subcarrier spacings on MIMO-OFDM channel capacity showed negligible differences in mean channel capacity for the subcarrier spacing range investigated. Measured channels described in this paper are available on request.

How does angular resolution affect diffusion imaging measures?

A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

A method for estimating intrinsic noise in electroretinographic (ERG) signals

Purpose To develop a signal processing paradigm for extracting ERG responses to temporal sinusoidal modulation with contrasts ranging from below perceptual threshold to suprathreshold contrasts. To estimate the magnitude of intrinsic noise in ERG signals at different stimulus contrasts. Methods Photopic test stimuli were generated using a 4-primary Maxwellian view optical system. The 4-primary lights were sinusoidally temporally modulated in-phase (36 Hz; 2.5 - 50% Michelson). The stimuli were presented in 1 s epochs separated by a 1 ms blank interval and repeated 160 times (160.16 s duration) during the recording of the continuous flicker ERG from the right eye using DTL fiber electrodes. After artefact rejection, the ERG signal was extracted using Fourier methods in each of the 1 s epochs where a stimulus was presented. The signal processing allows for computation of the intrinsic noise distribution in addition to the signal to noise (SNR) ratio. Results We provide the initial report that the ERG intrinsic noise distribution is independent of stimulus contrast whereas SNR decreases linearly with decreasing contrast until the noise limit at ~2.5%. The 1ms blank intervals between epochs de-correlated the ERG signal at the line frequency (50 Hz) and thus increased the SNR of the averaged response. We confirm that response amplitude increases linearly with stimulus contrast. The phase response shows a shallow positive relationship with stimulus contrast. Conclusions This new technique will enable recording of intrinsic noise in ERG signals above and below perceptual visual threshold and is suitable for measurement of continuous rod and cone ERGs across a range of temporal frequencies, and post-receptoral processing in the primary retinogeniculate pathways at low stimulus contrasts. The intrinsic noise distribution may have application as a biomarker for detecting changes in disease progression or treatment efficacy.

Cooperative diversity for performance enhancement of vehicular ad hoc networks

This project was a step forward in introducing suitable cooperative diversity transmission techniques for vehicle to vehicle communications. The contributions are intended to aid in the successful implementation of future vehicular safety and autonomous controlling systems. Several protocols were introduced for vehicles to communicate effectively without losing connectivity. This study investigated novel protocols in terms of diversity-multiplexing trade-off and outage for a range of potential vehicular safety and infotainment applications.

Detection of anuran calling activity in long field recordings for bio-acoustic monitoring

This paper presents a system to analyze long field recordings with low signal-to-noise ratio (SNR) for bio-acoustic monitoring. A method based on spectral peak track, Shannon entropy, harmonic structure and oscillation structure is proposed to automatically detect anuran (frog) calling activity. Gaussian mixture model (GMM) is introduced for modelling those features. Four anuran species widespread in Queensland, Australia, are selected to evaluate the proposed system. A visualization method based on extracted indices is employed for detection of anuran calling activity which achieves high accuracy.

Practical Algorithms For Mean Velocity Estimation In Pulse Doppler Weather Radars Using A Small Number Of Samples

Doppler weather radars with fast scanning rates must estimate spectral moments based on a small number of echo samples. This paper concerns the estimation of mean Doppler velocity in a coherent radar using a short complex time series. Specific results are presented based on 16 samples. A wide range of signal-to-noise ratios are considered, and attention is given to ease of implementation. It is shown that FFT estimators fare poorly in low SNR and/or high spectrum-width situations. Several variants of a vector pulse-pair processor are postulated and an algorithm is developed for the resolution of phase angle ambiguity. This processor is found to be better than conventional processors at very low SNR values. A feasible approximation to the maximum entropy estimator is derived as well as a technique utilizing the maximization of the periodogram. It is found that a vector pulse-pair processor operating with four lags for clear air observation and a single lag (pulse-pair mode) for storm observation may be a good way to estimate Doppler velocities over the entire gamut of weather phenomena.

Hybrid constant factor incremental delta modulators

The paper presents a new adaptive delta modulator, called the hybrid constant factor incremental delta modulator (HCFIDM), which uses instantaneous as well as syllabic adaptation of the step size. Three instantaneous algorithms have been used: two new instantaneous algorithms (CFIDM-3 and CFIDM-2) and the third, Song's voice ADM (SVADM). The quantisers have been simulated on a digital computer and their performances studied. The figure of merit used is the SNR with correlated, /?C-shaped Gaussian signals and real speech as the input. The results indicate that the hybrid technique is superior to the nonhybrid adaptive quantisers. Also, the two new instantaneous algorithms developed have improved SNR and fast response to step inputs as compared to the earlier systems.

Multi Pattern Dynamic Time Warping For Automatic Speech Recognition

We are addressing the problem of jointly using multiple noisy speech patterns for automatic speech recognition (ASR), given that they come from the same class. If the user utters a word K times, the ASR system should try to use the information content in all the K patterns of the word simultaneously and improve its speech recognition accuracy compared to that of the single pattern based speech recognition. T address this problem, recently we proposed a Multi Pattern Dynamic Time Warping (MPDTW) algorithm to align the K patterns by finding the least distortion path between them. A Constrained Multi Pattern Viterbi algorithm was used on this aligned path for isolated word recognition (IWR). In this paper, we explore the possibility of using only the MPDTW algorithm for IWR. We also study the properties of the MPDTW algorithm. We show that using only 2 noisy test patterns (10 percent burst noise at -5 dB SNR) reduces the noisy speech recognition error rate by 37.66 percent when compared to the single pattern recognition using the Dynamic Time Warping algorithm.

Constant factor incremental delta modulator

This paper presents a new algorithm for the step-size change of instantaneous adaptive delta modulator. The present strategy is such that the step-size at any sampling instant can increase or decrease by either of the two constant factors or can remain the same, depending upon the combination of three or four most recent output bits. The quantizer has been simulated on a digital computer, and its performance compared with other quantizers. The figure of merit used is the SNR with gaussian signals as the input. The results indicate that the new design can give an improved SNR over a wider dynamic range and fast response to step inputs, as compared to the earlier systems.

Implementation of a hybrid PCM encoding scheme

An improved encoding scheme is proposed wherein the quantizer step size incorporates both instantaneous and syllabic adaptation. The information needed to carry out this adaptation is extracted at the coder after the D/A conversion of the digital output, so that the coder and the decoder track each other. A 5-bit coder has been designed and built which has a dynamic range of 38 dB with a constant SNR of 30 dB, and the quality of its output signal is found to be comparable to that of other coding schemes

Improving the dynamic range of a CVSD coder

The letter describes a method of improving the dynamic range of a continuously variable slope delta modulator (CVSD). This is achieved by modifying the basic step size delta0 Compared to the CVSD algorithm, the modified CVSD (MCVSD) algorithm yields about 15–20 dB dynamic range improvement without degrading the peak SNR and the bit error rate tolerance.

Efficient Energy Management Policies for Networks with Energy Harvesting Sensor Nodes

We study sensor networks with energy harvesting nodes. The generated energy at a node can be stored in a buffer. A sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time at the node. For such networks we develop efficient energy management policies. First, for a single node, we obtain policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable suboptimal policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay. Next using the results for a single node, we develop efficient MAC policies.

Effect of fourier domain quantization on matched filtering

It is shown that the use of a coarsely quantized binary digital hologram as a matched filter on an optical computer does not degrade signal-to-noise ratio (SNR) appreciably.