ON THE LOCATION-AWARE COOPERATIVE SPECTRUM SENSING IN URBAN ENVIRONMENT

Spectrum sensing is a key enabling technology for cognitive radio networks (CRNs). The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Spectrum sensing decisions can lead to erroneous sensing with low performance due to fading, shadowing and other interferences caused by either terrain inconsistency or dense urban structure. In order to improve spectrum sensing decisions, in this paper a cooperative spectrum sensing scheme is proposed. The propagation conditions such as the variance and intensity of terrain and urban structure between two points with respect to signal propagation are taken into consideration. We have also derived the optimum fusion rule which accounts for location reliability of secondary users (SUs). The analytical results show that the proposed scheme slightly outperforms the conventional cooperative spectrum sensing approaches

Eye Gesture Analysis with Head Movement for Advanced Driver Assistance Systems

Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an onboard CCD camera to observe the driver’s face. A template matching approach is used to compare the driver’s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver’s eye-gaze pattern with templates of a driver’s eyes looking at each cell is used to determine the driver’s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard

Universal and Dynamic Clustering Scheme for Energy Constrained Cooperative Wireless Sensor Networks

Energy conservation is considered to be one of the key design challenges within resource constrained wireless sensor networks (WSNs) that leads the researchers to investigate energy efficient protocols with some application specific challenges. Dynamic clustering is generally considered as one of the energy conservation techniques; but unbalanced distribution of cluster heads, highly variable number of sensor nodes in the clusters and high number of sensor nodes involved in event reporting tend to drain out the network energy quickly resulting premature decrease in network lifetime. In this paper, a dynamic and cooperative clustering and neighborhood formation scheme is proposed that is expected to evenly distribute energy demand from the cluster heads and optimize the number of sensor nodes involved in event reporting. Assuming multiple sensors will form a cluster, while responding to an event to report to the fusion center. However, all the sensor nodes are assuming to report the sensing parameters to a cluster-head; which are to be summarized and then report it to fusion center. The transmission of the same event data from multiple sensors within the cluster at different distances with single or multiple antennas to the cluster-head with similar antenna characteristics can be realized as multiple-input multiple-output (MIMO) channel set up as found in the literature. Such realization among clusters of MIMO channel and existence of a feedback channel between the clusters and fusion center is the key of the proposed framework. The dynamic behavior has been adopted within the framework with a proposed index derived from the received measure of the channel quality, which has been attained through the feedback channel from the fusion center. The dynamic property of the proposed framework makes it robust against time-varying behavior of the propagation environment. The proposed framework is independent of the nature of the sensing application, providing with universal behavior. From simulation results, it is observed that the proposed clustering scheme enhances network lifetime by 24.5% and 36% as compared to existing schemes e.g. DDEEC and EDDEEC respectively. Furthermore, it is validated by simulation results that the proposed framework provides a trade-off model between network lifetime and transmission reliability

RF Sensing Based Target Detector for Smart Sensing Within Internet of Things in Harsh Sensing Environments

In this paper, we explore surveillance and target detection applications of Internet of Things (IoT) with radio detection as the primary means of sensing. The problem of surveillance and target detection has found its place in numerous civilian and military applications , andIoTiswellsuitedtoaddress this problem. Radio frequency (RF) sensing techniques are the next generation technologies, which offer distinct advantages over traditional means of sensing used for surveillance and target detection applications of IoT. However, RF sensing techniques have yet to be widely researched due to lack of transmission and computational resources within IoT. Recent advancements in sensing, computing, and communication technologies have made radio detection enabled sensing techniques available to IoT. However, extensive research is yet to be done in developing reliable and energy efficient target detection algorithms for resource constrained IoT. In this paper, we have proposed a multi-sensor RF sensing-based target detection architecture for IoT. The proposed target detection architecture is adaptable to interference, which is caused due to the co-existence of sensor nodes within IoT and adopts smart sensing strategies to reliably detect the presence of the targets .A wave form selection criterion has been proposed to identify the optimum choice of transmit waveforms within a given set of sensing conditions to optimize the target detection reliability and power consumption within the IoT. A dual-stage target detection strategy has been proposed to reduce the computational burden and increase the lifetime of the sensor nodes

Spectral efficient compressive transmission framework for wireless communication systems

Increasing demand of high-speed data rate is leading to a challenging task to provide services to the users within exponentially growing market for wireless multimedia services. Subsequently, the available radio resources are becoming scarce because of different factors such as spectrum segmentation and dedicated frequency allocation to existing wireless standards. Exploring new techniques for enhancing the spectral efficiency in wireless communication has been an important research challenge. In this study, the enhancement of spectral efficiency of wireless communication systems is considered. A framework is proposed to implement the concept of compressive sampling (CS) for compressing the natural random signals. The performance of proposed framework is evaluated in the context of multiple input multiple output orthogonal frequency division multiplexing system. Simulation-based results show that 25% of resources can be saved by marginal trade-off with the quality of service (QoS) requirement applying CS to the natural random signals. Furthermore, it can be claimed that this QoS trade-off can be optimised with dynamic selection of random measurement matrices

Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper

Fraudulence Risk Strategic Assessment of Processed Meat Products

 A total of 450 samples of different meat products (luncheon chicken, luncheon meat, sausage, beef burger, minced meat, and kofta) were examined. Fifty samples of each type of product were collected from different supermarkets in Assiut City. All of the samples were analysed by different microscopy techniques (light, fluorescence, histochemical microscopy, and scanning electron microscopy (SEM)) for the detection of meat adulteration. Haematoxylin-eosin (HE) staining was used for general histological examinations. Different histochemical techniques were used to stain paraffinised sections. The adulterated tissues detected were the nuchal ligament, large elastic blood vessels, muscular artery, elastic fibers, lung, cardiac muscle fibers, tendon, spongy bone, bone of immature animals, adipose tissue, cartilage (hyaline and white fibrocartilage), and smooth muscle of visceral organs. SEM detected contamination of the minced meat by bacteria and yeast. Fluorescence microscopy was used as an effective method for the detection of bone and cartilage. Interestingly, the stained acidophilic cytoplasm of skeletal muscle changed to basophilic, and the skeletal muscle was suspected to be diseased. The findings of the present work provide qualitative evaluations of the detection of unauthorised tissues in different meat products using different effective histological techniques

Universal Intelligent Small Cell (UnISCell) for Next Generation Cellular Networks

Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell) for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations