SINR based algorithm for vertical handover between WiMAX and Wi-Fi networks / Ammar Bathich

The great increase in user demand to roam among various wired and wireless communications networks without affecting the signal quality has attracted many researchers to investigate about the best handover decision criteria that promote seamless handover. IEEE 802.21 Media Independent Handover (MIH) standard can be considered the best candidate for handling both horizontal and vertical handover. In this work, we propose a new decision criteria based on MIH signalling between WLAN and WiMAX networks, which depend on the received Signal to Interference and Noise Ratio (SINR) instead of the traditional Received Signal Strength (RSS) criteria. In order to provide QoS inside the integrated network environment, the proposed Vertical Handover Decision (VHD) provides the knowledge of the achievable bandwidth from both networks by using the received SINR. Simulated-based outputs along with the analytical results have confirmed that our proposal offer better performance during the handover stag

IoT based on secure personal healthcare using RFID technology and steganography

Internet of things (IoT) makes it attainable for connecting different various smart objects together with the internet. The evolutionary medical model towards medicine can be boosted by IoT with involving sensors such as environmental sensors inside the internal environment of a small room with a specific purpose of monitoring of person's health with a kind of assistance which can be remotely controlled. RF identification (RFID) technology is smart enough to provide personal healthcare providing part of the IoT physical layer through low-cost sensors. Recently researchers have shown more IoT applications in the health service department using RFID technology which also increases real-time data collection. IoT platform which is used in the following research is Blynk and RFID technology for the user's better health analyses and security purposes by developing a two-level secured platform to store the acquired data in the database using RFID and Steganography. Steganography technique is used to make the user data more secure than ever. There were certain privacy concerns which are resolved using this technique. Smart healthcare medical box is designed using SolidWorks health measuring sensors that have been used in the prototype to analyze real-time data

Q-Learning vertical handover scheme in two-tier LTE-A networks

Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers

Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks

Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased