Equity-Based free channels assignment for secondary users in a cognitive radio network

The present paper addresses the equity issue among the secondary users in a cognitive radio network. After using a multi scheduler algorithm and a fairness metric namely Jain’s Equity Index; we enhance the equity between the secondary users’ transfer rates by 0.64 in average, relative to a previous work

Decentralization of Services Through Three Tiers in Wireless Body Area Networks

The Wireless Body Area Network (WBAN) contains a set of sensors, placed in the patient’s environment, to detect the vital signs and transmit the results towards the relevant services that interact in urgent cases. The present work exposes a functional WBAN architecture formed by three layers: closest, intermediate and farthest. The closest layer senses the chemical and biological signs. If the case is normal, or it can be locally regulated, the service stops there; else the intermediate service, namely the local hospital, is consulted to make treatments. Therefore, the patient will be transported into the hospital for examinations. If this condition is established the processus stopped there, otherwise, the request of help from an outside hospital becomes necessary. This request passes through a manager that supervises a network of hospitals and looks for a free place to welcome the patient. After the localization of a hospital, its coordinates will be forwarded into the customer hospital, for transporting the patient. The simulation results show that this design increases the patient’s probability of healing and maximizes the use of the available resources, relative to the centralization of services at a single layer or at two layers

Monopoly-Market-Based Cooperation in Cognitive Radio Networks

In a cognitive radio network (CRN), the primary users (PUs) do not operate their spectra, full time. Thus, they can sell them to the secondary users (SUs), for a second use, during the free time slots. In this article, we assume that the market is perfect, monopolized by a single PU, and all players are rational. After formulating the PU’s profit, we established a necessary and sufficient condition that guarantees the introduction of the PU into the market. In addition, the expressions of the SUs’ profits, showed us that in non-cooperative form, some ones got zero profit, even after maximizing their profits. Therefore, we have considered to study the effect of cooperation on the profits of this category of SUs. By following this step, we established a cooperation strategy, to avoid zero profits for all SUs. In order to analyze the impact of this cooperation on the PU, we have expressed the profits of the PU in the cooperative and non-cooperative forms; as result, we found that the cooperation between SUs brought better than the non-cooperative form

Energy efficient power control for device to device communication in 5G networks

Next generation cellular networks require high capacity, enhanced energy efficiency and guaranteed quality of service (QoS). In order to meet these targets, device-to device (D2D) communication is being considered for future 5th generation especially for certain applications that require the proximity gain, the reuse gain, and the hop gain. In this paper, we investigate energy efficient power control for the uplink of an OFDMA (orthogonal frequency-division multiple access) single-cell communication system composed of both regular cellular users and device to device (D2D) pairs. Firstly, we analyze and mathematically model the actual requirements forD2D communications and traditional cellular links in terms of minimum rate and maximum power requirement. Secondly, we use fractional programming in order to transform the original problem into an equivalent concave one and we use the non-cooperative Game theory in order to characterize the equilibrium. Then, the solution of the game is given as a water-filling power allocation. Furthermore, we implement a distributed power allocation scheme using three ways: a) Fractional programming techniques b) Closed form expression (the novelty is the use of wright omega function). c) Inverse water filling. Finally, simulations in both static and dynamic channel setting are presented to illustrate the improved performance in term of EE, SE (spectral efficiency) and time of execution of the iterative algorithm (Dinkelbach) than the closed form algorithms

Improving the selection of MPRs in OLSR protocol: a survey of methods and techniques

Multi Point Relays (MPRs) are those nodes that are calculated and determined by the Optimized Link State Routing protocol (OLSR) in order to minimize and avoid overload inside the Mobile Ad hoc Network (MANET). In this paper, we will present a synthetic study of many techniques and methods for calculating and selecting the MPR nodes using a set of criteria namely energy, mobility, bandwidth, the quality of links, etc. The result of this study shows that most techniques consider a limited number of metrics for selecting the MPR nodes and therefore they are insufficient to allow the OLSR protocol to be quite complete and efficient because several metrics can occur at the same time in the real execution environment

Merging gradual neural networks and Genetic algorithm for Dynamic Channel Assignment Problem

Under this article, we offer a novel neural-network approach called gradual neural network (GNN) hybridized with a genetic algorithm for a class of combinatorial optimization problems of requiring the constraint satisfaction and the goal function optimization simultaneously. The hard problem of frequency assignment problem in the mobile communication system is efficiently solved by GNN as the typical problem of this class.The goal of this problem is to minimize the electromagnetic compatibility constraints between transceivers by first, rearranging the frequency assignment so that they can accommodate the increasing demands and second, using a minimum number of frequencies. An optimal solution is sought to facilitate the subsequent addition of new links. The binary neural network achieves the constraint satisfaction with the help of genetic algorithm, in order to seek the cost optimization and the network topology. The capability of the GNN algorithm is demonstrated through solving real instances in practical problem, showing that it can find far equivalent solutions than the existing algorithms, has good performance, and suggests a new interesting direction for research

Development of a hardware emulator of a nanosatellite gyroscope

The gyroscope sensor has multiple applications in consumer electronics, aircraft navigation, and control systems. Significant errors that match the corresponding data are a typical disadvantage of this sensor. This needs to be done by making error models that can be used to get the right level of measurement accuracy. For high-precision space applications, the navigation design system should take into account the angle random walk (N), bias instability error (B), and rate random walk (K) of the BMG160 gyroscope. For this reason, this paper shows how to use Allan Variance (AVAR) and Power Spectral Density (PSD) for the experimental identification and modeling of the stochastic parameters of the Bosch BMG160 gyroscope embedded in a nanosatellite in order to get an accurate gyroscope model. This work also demonstrates the principle of operation of the equivalent electronic model intended to carry out advanced simulations without recourse to the real material in order to avoid the problem of bad manipulation and availability of the material in order to reduce the time and cost of development. The interpretation of the Allan curves and the PSD obtained from the measurements collected over a long period is presented, as well as a comparison between the real raw data of the BMG160 gyroscope and the designed hardware emulator in both the time and frequency domains. This is done to evaluate the accuracy of the gyroscope model emulating the real sensor in laboratory simulations. The experimental results show that the signals from the emulator and the BMG160 gyroscope are quite close. Therefore, the proposed prototype could be an optimal solution for laboratory calculations and simulation

Software calibration for AK8963 magnetometer based on optimal ellipsoidal fitting

With the rapid development of mechatronics, systems in package (SiP), in particular the MPU-9250 inertial measurement Unit 9DOF (MPU-6050 6DOF and AK8963 3DOF), are becoming ubiquitous in applications for autonomous navigation purposes. Nevertheless, they suffer from some accuracy problems related to axis misalignment, disturbances, and deviation over time that make them unable to work autonomously for a long time. This paper will present a simple and practical calibration method using a least-squares based ellipsoid fitting method to calibrate and compensate for the error interference of the AK8963 sensor. Towards the end of this paper, a comparison between before and after the calibration is presented to study the software compensation effect and the stability of the magnetic sensor under study