R. Aravind

Space-frequency block coding in OFDM systems

An effective technique to improve wireless communication performance is transmit diversity. In this work, transmitter diversity using a new combination of space-time block codes (STBCs) concatenated with orthogonal frequency division multiplexing (OFDM) system in high-speed wireless data communication is investigated. Simulation results demonstrate that this scheme can achieve a significant performance increase for efficient data transmission over slow and fast fading environments, compared to conventional OFDM. Performance of proposed scheme has been compared to an STBC-OFDM scheme and it is evident that SFBC is more robust than STBC-OFDM system in a fast fading environment.

A class of M-channel reduced complexity IIR cosine modulated filter banks

We describe a class of reduced complexity IIR cosine modulated filter banks satisfying the perfect reconstruction property. They are shown to be easy to implement, in terms of the number of filters, both on the analysis and on the synthesis sides. We provide closed-form expressions for the polyphase components of the synthesis prototype in terms of those of the analysis prototype. We also derive an expression for the frame ratio for this class of filter banks.

Segmentation of camera-trap tiger images based on texture and color features

In this paper we propose a method to obtain the region of interest in a camera-trap tiger image so that it can be used for identification of the tiger in later stage. We use a combination of texture and color features to discriminate the tiger from the background. Based on these features, a level set based active contour segmentation is performed. A series of morphological operation are then performed on the segmented result to obtain the desired region of interest. The experimental results show the effectiveness of the proposed algorithm.

Improved least squares channel estimation for orthogonal frequency division multiplexing

The authors consider the design of pilot sequences for channel estimation in the presence of carrier frequency offset (CFO) in systems that employ orthogonal frequency division multiplexing (OFDM). The CFO introduces intercarrier interference (ICI) which degrades the accuracy of the channel estimation. In order to minimise this effect, the authors design pilot sequence that minimises the mean square error (MSE) of the modified least squares (mLS) channel estimator. Since the identical pilot sequence, which minimises this MSE, has high peak-to-average power ratio of the OFDM signal, an alternative approach is proposed for channel estimation. The authors first introduce a new estimator as an alternative to the mLS estimator and design a low PAPR pilot sequences tailored to this new estimator. They show that the proposed procedure completely eliminates the effect of the ICI on the channel estimate. They then extend their design of pilot sequences for realistic sparse channels. Both analytical and computer simulation results presented in this study demonstrate the superiority of the proposed approach over conventional methods for channel estimation in the presence of ICI.

A Krylov subspace based low-rank channel estimation in OFDM systems

We investigate a low-rank minimum mean-square error (MMSE) channel estimator in orthogonal frequency division multiplexing (OFDM) systems. The proposed estimator is derived by using the multi-stage nested Wiener filter (MSNWF) identified in the literature as a Krylov subspace approach for rank reduction. We describe the low-rank MMSE expressions for exploiting the time correlation function (TCF) of the channel path gains. The Krylov subspace technique requires neither eigenvalue decomposition (EVD) nor the inverse of the covariance matrices for parameter estimation. We show that the Krylov channel estimator can perform as well as the EVD estimator with a much smaller rank. Simulation results obtained confirm the superiority of the proposed Krylov low-rank channel estimator in approaching near full-rank MSE performance.

Pilot sequence design for improving OFDM channel estimation in the presence of CFO

We consider the design of pilot sequences for channel estimation in the presence of carrier frequency offset (CFO) in systems that employ orthogonal frequency division multiplexing (OFDM). The CFO introduces intercarrier interference (ICI) which degrades the accuracy of the channel estimation. To minimize this effect, we solve for the pilot sequence that minimizes the mean square error of the modified least squares (mLS) channel estimator. The transmission of this sequence results in high peak-to-average power ratio (PAPR) of the OFDM signal. To solve this problem, we first introduce a new estimator as an alternative to the mLS estimator. We then design a low PAPR pilot sequence tailored to this new estimator. We show that the proposed procedure completely eliminates the effect of the ICI on the channel estimate. Both analytical and computer simulation results demonstrate the superiority of the proposed scheme over the mLS estimator.

Improved channel estimation in OFDM systems in the presence of CFO

We consider the problem of pilot-aided accurate least squares (LS) channel estimation in the presence of carrier frequency offset (CFO). We first formulate the mean square error (MSE) of the LS channel estimator in the presence of CFO and then show how to select the pilot sequence (with element values constrained to plus or minus one) that minimizes the MSE. Our main conclusion is that, in the presence of CFO accurate channel estimates can be obtained by transmitting identical pilot symbol on all subcarriers. We demonstrate our results via computer simulations.

Measurement of asymmetry of stripe patterns in animals

The deviation from perfect symmetry of the left and right sides of a bilateral animal is known to indicate the developmental stress of the animal. It has also been used to study the general health of a population. For animals like tigers and zebras which have natural stripes on their bodies, the asymmetry between the two sides can be measured by analysing the stripe patterns taken from images of these animals. In this paper we propose an algorithm for measuring this asymmetry. We use a Short-Time Fourier Transform based approach to measure the local frequencies at different locations and compare the resulting frequency maps. The mean absolute error between the left and right frequency maps yields a measure of the asymmetry. Our results show a surprising level of asymmetry in tiger stripes compared to zebras.