Efficient Power Allocation Schemes for Hybrid Decode-Amplify-Forward Relay Based Wireless Cooperative Network

Cooperative communication in various wireless domains, such as cellular networks, sensor networks and wireless ad hoc networks, has gained significant interest recently. In cooperative network, relays between the source and the destination, form a virtual MIMO that creates spatial diversity at the destination, which overcomes the fading effect of wireless channels. Such relay assisted schemes have potential to increase the channel capacity and network coverage. Most current research on cooperative communication are focused broadly on efficient protocol design and analysis, resource allocation, relay selection and cross layer optimization. The first part of this research aims at introducing hybrid decode-amplify-forward (HDAF) relaying in a distributed Alamouti coded cooperative network. Performance of such adaptive relaying scheme in terms of symbol error rate (SER), outage probability and average channel capacity is derived theoretically and verified through simulation based study. This work is further extended to a generalized multi HDAF relaying cooperative frame work. Various efficient power allocation schemes such as maximized channel capacity based, minimized SER based and total power minimization based are proposed and their superiority in performance over the existing equal power allocation scheme is demonstrated in the simulation results. Due to the broadcast nature of wireless transmission, information privacy in wireless networks becomes a critical issue. In the context of physical layer security, the role of multi HDAF relaying based cooperative model with control jamming and multiple eavesdroppers is explored in the second part of the research. Performance evaluation parameters such as secrecy rate, secrecy outage and intercept probability are derived theoretically. Further the importance of the proposed power allocation schemes in enhancing the secrecy performance of the network in the presence of multiple eavesdroppers is studied in detail through simulation based study and analysis. For all the proposed power allocation schemes in this research, the optimization problems are defined under total power constraint and are solved using Lagrange multiplier method and also evolutionary algorithms such as Differential evolution and Invasive Weed Optimization are employed. Monte Carlo simulation based study is adopted throughout the research. It is concluded that HDAF relaying based wireless cooperative network with optimal power allocation schemes offers improved and reliable performance compared to conventional amplify forward and decode forward relaying schemes. Above research contributions will be applicable for future generation wireless cooperative networks

Online signature verification techniques

Signature is a behavioral biometric: it is not based on the physical properties, such as fingerprint or face, of the individual, but behavioral ones. Signature verification is split into two according to the available data in the input. Offline (static) signature verification takes as input the image of a signature and is useful in automatic verification of signatures found on bank checks and documents. Online (dynamic) signature verification uses signatures that are captured by pressure-sensitive tablets that extract dynamic properties of a signature in addition to its shape. The purpose of project is to develop an authentication system based on personal signatures. Signature verification is an important research topic in the area of biometric authentication. In this project the work is done in such a way that the signatures are captured using WEBCAM. A visual-based online signature verification system in which the signer’s pen tip is tracked. The data acquisition of the system consists of only low-cost cameras (webcams) and does not need special equipment such as an electronic tablet. Online signature data is obtained from the images captured by the webcams by tracking the pen tip. The pen tip tracking is implemented by the Sequential Monte Carlo method in real time. Then, the distance between the input signature data and reference signature data enrolled in advance is computed using Dynamic Time Warping (DTW). Finally, the input signature is classified as genuine or a forgery by comparing the distance with a threshold