We analyze the effect of the propagation of route request packets in ad hoc network routing protocols such as DSR and AODV. So far it has not been clear how the number density of route request packets depends on propagation and hop counts. By stochastic analysis, it is found that the collisions of route request packets can be avoided efficiently by adjusting the number of the relevant nodes in the early stages of propagation.

This paper derives the balanced realizations of second-order analog filters directly from the transfer function. Second-order analog filters are categorized into the following three cases: complex conjugate poles, distinct real poles, and multiple real poles. For each case, simple formulas are derived for the synthesis of the balanced realizations of second-order analog filters. As a result, we obtain closed form expressions of the balanced realizations of second-order analog filters.

Observed samples in wideband radar are always represented as nonlinear points in high dimensional space. In this paper, we consider the feature selection problem in the scenario of wideband radar target clustering. Inspired by manifold learning, we propose a novel feature selection algorithm, called Local Reconstruction Error Alignment (LREA), to select the features that can best preserve the underlying manifold structure. We first select the features that minimize the reconstruction error in every neighborhood. Then, we apply the alignment technique to extend the local optimal feature sequence to a global unique feature sequence. Experiments demonstrate the effectiveness of our proposed method.

Lane detection plays an important role in Driver Assistance Systems and Autonomous Vehicle System. In this paper, we propose a parallel-snake model combined with balloon force for lane detection. Parallel-snake is defined as two open active contours with parallel constrain. The lane boundaries on the left and right sides are assumed as parallel curves, parallel-snake is deformed to estimate these two boundaries. As lane regions between left and right boundaries usually have low gradient, snake will lose external force on these regions. Furthermore, inspired by balloon active contour model, the balloon force is introduced into parallel-snake to expand two parallel curves from center of road to the left and right lane boundaries. Different from closed active contour, stretching force is adopted to prevent the head and tail of snake from converging together. The experimental results on three different datasets show that parallel-snake model can work well on images with shadows and handle the lane with broken boundaries as the parallel property.

Spectrum sensing is one of the methods to identify available white spaces for secondary usage which was specified by the regulators. However, signal quality to be sensed can plunge to a very low signal-to-noise-ratio due to signal propagation and hence readings from individual sensors will be unreliable. Distributed sensing by the cooperation of multiple sensors is one way to cope with this problem because the diversity gain due to the combining effect of data captured at different position will assist in detecting signals that might otherwise not be detected by a single sensor. In effect, the probability of detection can be improved. We have implemented a distributed sensing system to evaluate the performance of different cooperative sensing algorithms. In this paper we describe our implementation and measurement experience which include the system design, specification of the system, measurement method, the issues and solutions. This paper also confirms the performance enhancement offered by distributed sensing algorithms, and describes several ideas for further enhancement of the sensing quality.

This paper reports the use of haptic augmented reality in breast tumor palpation. In general, lumps in the breast are stiffer than surrounding tissues, allowing us to haptically detect them through self-palpation. The goal of the study is to assist self-palpation of lumps by haptically augmenting stiffness around lumps. The key steps are to estimate non-linear stiffness of normal tissues in the offline preprocessing step, detect areas that show abnormally stiffer responses, and amplify the difference in stiffness through a haptic augmented reality interface. The performance of the system was evaluated in a user-study, demonstrating the potential of the system.

This paper presents a novel acoustic modeling technique of large vocabulary automatic speech recognition for under-resourced languages by leveraging well-trained acoustic models of other languages (called source languages). The idea is to use source language acoustic model to score the acoustic features of the target language, and then map these scores to the posteriors of the target phones using a classifier. The target phone posteriors are then used for decoding in the usual way of hybrid acoustic modeling. The motivation of such a strategy is that human languages usually share similar phone sets and hence it may be easier to predict the target phone posteriors from the scores generated by source language acoustic models than to train from scratch an under-resourced language acoustic model. The proposed method is evaluated using on the Aurora-4 task with less than 1 hour of training data. Two types of source language acoustic models are considered, i.e. hybrid HMM/MLP and conventional HMM/GMM models. In addition, we also use triphone tied states in the mapping. Our experimental results show that by leveraging well trained Malay and Hungarian acoustic models, we achieved 9.0% word error rate (WER) given 55 minutes of English training data. This is close to the WER of 7.9% obtained by using the full 15 hours of training data and much better than the WER of 14.4% obtained by conventional acoustic modeling techniques with the same 55 minutes of training data.

This paper describes an analytical study of performance of a proposed signal detection scheme that will allow coexistence of an additional radio communication system (generally, secondary system) in the service area where the existing communication system (primary system) is operated. Its performance characteristics are derived by an analytical method based on stochastic theory, which is subsequently validated by software simulation. The main purpose of the detection scheme is to protect the primary system from the secondary system. In such a situation, the signals of the primary system and secondary system may be simultaneously received in the signal detector. One application of such a scheme is D-to-D (Device-to-Device) communication, whose system concept including the detection scheme is briefly introduced. For improved secondary signal detection, we propose the signal cancellation method of the primary system and the feature detection method of the secondary system signal. We evaluate the performance characteristics of the detection scheme in terms of “probability of correct detection”. We reveal that an undesired random component is produced in the feature detection procedure when two different signals are simultaneously received, which degrades the detection performance. Such undesired component is included in the analytical equations. We also clarify that the cancellation scheme improves the performance, when the power ratio of the primary signal to secondary signal is higher than 20-22dB.

Designing a medium access control (MAC) protocol is a key for implementing any practical wireless network. In general, a MAC protocol is responsible for coordinating users in accessing spectrum resources. Given that a user in cognitive radio(CR) networks do not have priority in accessing spectrum resources, MAC protocols have to perform dynamic spectrum access (DSA) functions, including spectrum sensing, spectrum access, spectrum allocation, spectrum sharing and spectrum mobility, beside conventional control procedure. As a result, designing MAC protocols for CR networks requires more complicated consideration than that needed for conventional/primary wireless network. In this paper, we focus on two major perspectives related to the design of a CR-MAC protocol: dynamic spectrum access functions and network infrastructure. Five DSA functions are reviewed from the point of view of MAC protocol design. In addition, some important factors related to the infrastructure of a CR network including network architecture, control channel management, the number of radios in the CR device and the number of transmission data channels are also discussed. The remaining challenges and open research issues are addressed for future research to aim at obtaining practical CR-MAC protocols.

This paper proposes an adaptive marker coding (AMC) for correction of insertion/deletion/substitution errors. Unlike the conventional marker codings which select marker-bit values deterministically, the AMC adaptively reverses the first and last bits of each marker as well as bits surrounding the marker. Decoding is based on a forward-backward algorithm which takes into account the dependency of bit-values around the marker. Evaluation shows that, for a channel with insertion/deletion error probability 1.8×10-2, the decoded BER of existing marker coding of rate 9/16 is 4.25×10-3, while that of the proposed coding with the same code rate is 1.73×10-3.

MIL-STD-188-220 standard specifies protocols for narrowband and voice-based tactical communication devices. However, the future tactical communication devices require broadband services for accurate command and control. In this letter, the enhancement for MIL-STD-188-220-based systems is proposed for use over wideband channels. Unlike the operation defined in the standard, transmissions in Bump-Slots uses P-Persistence method and give the higher p to stations experiencing longer delays. The proposed method is extensively evaluated and the performance enhancements are proved.

Multi-stage splitter configurations are often utilized in passive optical network (PON) systems to effectively accommodate widely-dispersed users. This paper introduces two types of more effective user accommodation approaches that place bidirectional optical amplifiers in several branches of the splitter inside the central office (CO); it allows a single optical line terminal (OLT) to support the coexistence of normal- and extended-distance areas and also the sharing by large numbers of optical network units (ONUs). To ease the issue of amplified spontaneous emission (ASE) noise, which is inherent in these system configurations, we propose to use a semiconductor optical amplifier (SOA)-based burst-mode optical amplifier with a fast automatic level control (ALC) circuit for upstream amplification.

This letter presents a new image quality metric using low order discrete orthogonal moments. The moment features are extracted in a block manner and the relative moment differences (RMD) are computed. A new exponential function based on RMD is proposed to generate the quality score. The performance of the proposed method is evaluated on public databases. Experimental results and comparisons demonstrate the efficiency of the proposed method.

This paper presents an experimental evaluation of an ocean wave remote sensing system that uses bistatic GPS signal reflection to estimate wave characteristics. In our previous paper, a bistatic ocean wave remote sensing system by GPS was proposed to estimate the characteristics of sea swell near a harbor, and was also evaluated by numerical simulations. In the next phase, a prototype system has been developed and some basic experiments have been carried out in a coastal area in order to evaluate the system experimentally. In this paper, we will outline the prototype system. The system mainly consists of an array antenna, a front-end, and an estimator for ocean wave characteristics. Next, we explain that the estimator for ocean wave characteristics can identify each signal reflected from the ocean waves. Finally, the experiments show that the prototype system can receive the reflected signals from the sea-surface near the coast, and estimate the wave period and wavelength in the direction of the array antenna.

A ghost reduction algorithm for multiple angle sensors tracking objects under dual hypotheses is proposed. When multiple sensors and multiple objects exist on the same plane, the conventional method is unable to distinguish the real objects and ghosts from all possible pairs of measurement angle vectors. In order to resolve the issue stated above, the proposed algorithm utilizes tracking process considering dual hypotheses of real objects and ghosts behaviors. The proposed algorithm predicts dynamics of all the intersections of measurement angle vector pairs with the hypotheses of real objects and ghosts. Each hypothesis is evaluated by the residuals between prediction data and intersection. The appropriate hypothesis is extracted trough several data sampling. Representative simulation results demonstrate the effectiveness of the proposed algorithm.

The nth partial sums of a classical Fourier series have large oscillations near the jump discontinuities. This behaviour is the well-known Gibbs phenomenon. Recently, the inverse polynomial reconstruction method (IPRM) has been successfully implemented to reconstruct piecewise smooth functions by reducing the effects of the Gibbs phenomenon for Fourier series. This paper addresses the 2-D fractional Fourier series (FrFS) using the same approach used with the 1-D fractional Fourier series and finds that the Gibbs phenomenon will be observed in 1-D and 2-D fractional Fourier series expansions for functions at a jump discontinuity. The existing IPRM for resolution of the Gibbs phenomenon for 1-D and 2-D FrFS appears to be the same as that used for Fourier series. The proof of convergence provides theoretical basis for both 1-D and 2-D IPRM to remove Gibbs phenomenon. Several numerical examples are investigated. The results indicate that the IPRM method completely eliminates the Gibbs phenomenon and gives exact reconstruction results.

In this letter, we present an efficient video matching-based denoising method. Two main issues are addressed in this paper: the matched points and the denoising algorithm based on an adaptive spatial temporal filter. Unlike previous algorithms, our method adaptively selects reference pixels within spatially and temporally neighboring frames. Our method uses more information about matched pixels on neighboring frames than other methods. Therefore, the proposal enhanced the accuracy of video denoising. Simulation results show that the proposed method produces cleaner and sharper images.

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Image binarization refers to convert gray-level images into binary ones, and many binarization algorithms have been developed. The related algorithms can be classified as either high quality computation or high speed performance. This letter presents an algorithm that ensures both benefits at the same time. The proposed algorithm intelligently segments input images into several sub-image, after which the sub-image binarization is performed independently. Experimental results reveal that our algorithm provides the appropriate quality with the medium speed.

This letter deals with a new cell clustering problem subject to signal-to-interference-plus-noise-ratio (SINR) constraints in uplink network MIMO systems, where multiple base stations (BSs) cooperate for joint processing as forming a cluster. We first prove that the SINRs of users in a certain cluster always increase monotonically as the cluster size increases when the receiver filter that maximizes the SINR is used. Using this result, we propose an efficient clustering algorithm to minimize the maximum number of cooperative BSs in a cluster. Simulation results show that the maximum number of cooperative BSs minimized by the proposed method is close to that minimized by the exhaustive search and the proposed scheme outperforms the conventional one in terms of the outage probability.