2010/4

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Electronically Tunable Current-Mode Quadrature Oscillator Using Single MCDTA
(Společnost pro radioelektronické inženýrství, 2010-12) Li, Yongan
This paper presents a modified current differencing transconductance amlpifier (MCDTA) and the MCDTA based quadrature oscillator. The oscillator is current-mode and provides current output from high output impedance terminals. The circuit uses only one MCDTA and two grounded capacitors, and is easy to be integrated. Its oscillation frequency can be tuned electronically by tuning bias currents of MCDTA. Finally, frequency error is analyzed. The results of circuit simulations are in agreement with theory.
On the Effect of Channel Impairments on VANETs Performance
(Společnost pro radioelektronické inženýrství, 2010-12) Baltzis, Konstantinos B.
The primary means of studying the performance of vehicular ad hoc networks (VANETs) are computer simulations. Nowadays, the development of analytical models and the use of hybrid simulations that combine analytical modeling with discrete-event simulation are of great interest due to the significant reduction in computational cost. In this paper, we extend previous work in the area by suggesting an analytical model that includes distance-dependent losses, shadowing and small-scale fading. Closed-form expressions for the packet reception probability and the packet forwarding distance in the absence of simultaneous transmissions are presented. Numerical simulations validate the proposed formulation. The impact of path loss and fading on network throughput is explored. Interesting results that shows the efficacy of the approach are provided. The derived formulation is a useful tool for the modeling and analysis of vehicular communication systems.
LMS Based Adaptive Channel Estimation for LTE Uplink
(Společnost pro radioelektronické inženýrství, 2010-12) Rana, Md Masud; Kim, Jinsang; Cho, Won-Kyung
In this paper, a variable step size based least mean squares (LMS) channel estimation (CE) algorithm is presented for a single carrier frequency division multiple access(SC-FDMA) system under the umbrella of the long term evolution (LTE). This unbiased CE method can automatically adapts the weighting coefficients on the channel condition. Therefore, it does not require knowledge of channel,and noise statistics. Furthermore, it uses a phase weighting scheme to eliminate the signal fluctuations due to noise and decision errors. Such approaches can guarantee the convergence towards the true channel coefficient. The mean and mean square behaviors of the proposed CE algorithm are also analyzed. With the help of theoretical analysis and simulation results, we prove that the proposed algorithm outperforms the existing algorithms in terms of mean square error (MSE) and bit error rate (BER) by more than around 2.5dB.
Key Information Retrieval in Hyperspectral Imagery through Spatial-Spectral Data Fusion
(Společnost pro radioelektronické inženýrství, 2010-12) Mianji, Fereidoun A.; Zhang, Ye; Babakhani, Asad
Hyperspectral (HS) imaging is measuring the radiance of materials within each pixel area at a large number of contiguous spectral wavelength bands. The key spatial information such as small targets and border lines are hard to be precisely detected from HS data due to the technological constraints. Therefore, the need for image processing techniques is an important field of research in HS remote sensing. A novel semisupervised spatial-spectral data fusion method for resolution enhancement of HS images through maximizing the spatial correlation of the endmembers (signature of pure or purest materials in the scene) using a superresolution mapping (SRM) technique is proposed in this paper. The method adopts a linear mixture model and a fully constrained least squares spectral unmixing algorithm to obtain the endmember abundances (fractional images) of HS images. Then, the extracted endmember distribution maps are fused with the spatial information using a spatial-spectral correlation maximizing model and a learning-based SRM technique to exploit the subpixel level data. The obtained results validate the reliability of the technique for key information retrieval. The proposed method is very efficient and is low in terms of computational cost which makes it favorable for real-time applications.
Investigating the Behavior of Compact Composite Descriptors in Early Fusion, Late Fusion and Distributed Image Retrieval
(Společnost pro radioelektronické inženýrství, 2010-12) Chatzichristofis, Savvas A.; Arampatzis, Avi; Boutalis, Yiannis S.
In Content-Based Image Retrieval (CBIR) systems, the visual content of the images is mapped into a new space named the feature space. The features that are chosen must be discriminative and sufficient for the description of the objects. The key to attaining a successful retrieval system is to choose the right features that represent the images as unique as possible. A feature is a set of characteristics of the image, such as color, texture, and shape. In addition, a feature can be enriched with information about the spatial distribution of the characteristic that it describes. Evaluation of the performance of low-level features is usually done on homogenous benchmarking databases with a limited number of images. In real-world image retrieval systems, databases have a much larger scale and may be heterogeneous. This paper investigates the behavior of Compact Composite Descriptors (CCDs) on heterogeneous databases of a larger scale. Early and late fusion techniques are tested and their performance in distributed image retrieval is calculated. This study demonstrates that, even if it is not possible to overcome the semantic gap in image retrieval by feature similarity, it is still possible to increase the retrieval effectiveness.

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