While addressing cellular network performance issues, resolving problems with coverage and capacity is critical. The coexistence of cellular networks and smaller femtocells working within the macrocell area is among the alternative solutions. The simultaneous functioning of macrocells and femtocells, however, introduces new technical challenges that pose serious concerns about the efficiency of cellular networks. Therefore, this work proposes a hybrid approach based on variant advanced antenna technologies including MIMO methods and antenna systems for the deployment of femtocells and macrocells. To accomplish this, three distinct LTE-A network models with and without femtocells are set up with different architectures for high-density areas. The models further cover tri-sector and omnidirectional antenna systems to analyze the relevant effects on the performance of the LTE-A macrocells as well as femtocells. Also, to extend the analysis, integration of different MIMO methods for the models is provided. The networks are implemented and the link performance evaluation is carried out with regard to spectral and energy efficiency, cell and user throughputs, fairness, and SINR. The results contribute to determining the performance gains and energy saving of the LTE-A femtocells as well as macrocells by employing different advanced antenna technologies.

The prototype development of Rescue Robot can help search and rescue teams with their difficult and life-saving tasks. Unmanned Aerial vehicles (UAVs) and Unmanned Ground vehicles (UGVs) are viewed as two separate entities. However, upon closer examination, we can classify them into a closely-coupled system where both are just seen as separable parts of the body of one robotic entity, whose body parts can separate temporarily and acquire together again later.  In this prototype, a mobile robot UGV can be used as transport and landing station for a light-weight quadcopter UAV. UAV has separable long-range vision system which provides the top view of environment for the UGV, separable images are stitched and transformed into maps and utilized for rescue operations. This rescue robot contains a combination of UGV and UAV. It is equipped with a strong manipulator arm, used for debris removal, shoring operations, and delivering medicines/ food on very rough terrain. It has light detection and ranging (lidar) sensors, cameras, enabling it to look for victims and for mapping semi-destroyed buildings. The UGV can send visual feedback to the operator at a remote location. The UAV drone has a camera for an aerial view and mapping of the place. Working in conjunction with one another and thus the human search and rescue workers, these robotic assets form a strong team, increasing the effectiveness of search and rescue operations. This project aims at the realization of a new generation of search and rescue robot which can work in semi-autonomous and wireless modes and can be used in harsh physical environments of disaster regions to hold out the given tasks more effectively by the utilization of advanced and economic sensors. the problem domain of earthquake disasters and search and rescue processes is clarified with introducing an overview of this project. Disasters unsettle the economic and social stability of society. Shortage of skilled rescue work forces, also because the risks involved in search and rescue operations, are getting foremost problems during an emergency situation. In this paper rescue robot were designed, implemented in a real time environment and analyzed the result.

One of the key issues of wireless communication networks is the spectrum crisis, and studies noted that static licensed bands are in the under-utilization stage. Recently Cognitive Radio Network facilitates a solution to minimize the spectrum crisis in which unlicensed users can utilize the licensed spectrum without transmission interference. To achieve this task we used Machine Learning techniques for analyzing spectrum occupancy which is an efficient method to analyze spectrum occupancy and provides high accuracy. Supervised machine learning algorithms namely Logistic regression, K nearest neighbor, and Naive Bayes are used to classify a given frequency band. In this paper we collect spectrum samples of GSM 900, 1800, and 2100 bands using Rohde & Schwarz FSH6 Handheld Spectrum Analyzer for developing a dataset, using that dataset we trained the classifiers and analyze their classification performance accuracy. Results have shown the best performance on the validation and testing partition for various Unweighted Average Recall (UAR) of each classifier. Here the Logistic Regression classifier learns the best representation from their feature vector. This research is helpful to measure the spectrum occupancy of different static allocated licensed bands for 24/7. This will give better ideas about spectrum utilization, future spectrum allocation and comfort to serve more users in the limited spectrum. The occupancy measurements of current allocated spectrums can not only provide a convincing basis for making future spectrum allocation policies, but also provide technical support for the development of new communication technologies.

In this paper, a fan-shaped ultra- wideband (UWB) microstrip patch antenna is re- ported. The antenna is designed, simulated, fab- ricated, and tested. The antenna operates over a 3.1 GHz – 6 GHz for Wireless Capsule Endoscopy (WCE) applications with VSWR less than 2 and return loss is lower than -10 dB. The antenna is a monopole circular structure with radius of 10.2 mm and ground plane dimension 24 x 16 mm (“Lg x Wg”) is designed on substrate FR4. The impedance matching and radiation characteristics of the designed structure are investigated. The pro- posed antenna with small size and different ground structure is considered to reduce the surface wave and to achieves high impedance bandwidth and good gain performance for ultra-wide band (UWB) range with specific absorption rate (SAR) 1.126 W/kg for 10 g of tissue.

Contamination and degradation in the quality of the fresh water under the ground is one of the major problems of our world. Water quality on the other hand, determined by the physical, chemical and biological compounds in the water. TDS (Total Dissolved Solid), salinity, dissolved oxygen, temperature, metabolic wastes, toxic compounds and conductivity are some of the major indicators of the water quality. These items are sometimes correlated and any increase in one factor may decrease/increase other factors as well. The aim of this work is to develop an idea about the contamination due to chemicals dissolved or biological anomalies in the water. Mainly the indicator of this change has been examined by the change in the conductivity parameter, which is a major electrical property that affects the Electromagnetic reflectivity of the surface ground.