Survey on Optimization Methods For Spectrum Sensing in Cognitive Radio Network

A cognitive radio is a capable Technology, which has provided a great innovation in wireless communication system as to improve the efficiency of the electromagnetic spectrum utilization in wireless network. The technology allows unlicensed user or secondary user to use the vacant spectrum of licensed user through dynamic channel assignment strategies to improve the spectral utilization and hence cognitive radio avoids spectrum shortage. Cooperative sensing is one of the fastest growing areas of research and it is likely to be a key enabling technology, for efficiently spectrum sensing in future. For this several spectrum sensing are available, which can detect the white spaces or spectrum holes and share them to the secondary user without interfering with the movement of licensed user. In order to reliably and swiftly detect spectrum holes in cognitive radios, optimization must be used. In this paper we study different optimization for spectrum searching and sharing and also compare this optimization on the basis of probability of total error on fading channel

Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications

In recent years, the networks of low-power devices have gained popularity. Typically these devices are wireless and interact to form large networks such as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable Computing, and Wireless Sensor Networks. The collaboration among these devices is a key to achieving the full potential of these networks. A major problem in this field is to guarantee robust communication between elements while keeping the whole network energy efficient. In this paper, we introduce an extended and improved emergent broadcast slot (EBS) scheme, which facilitates collaboration for robust communication and is energy efficient. In the EBS, nodes communication unit remains in sleeping mode and are awake just to communicate. The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up window in partially overlapped manner within each duty-cycle to avoid message collisions. We show the theoretical convergence behavior of the scheme, which is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

Primary User Emulation Attacks: A Detection Technique Based on Kalman Filter

Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users to use the vacant spectrum bands without causing interference to the primary users. However, several attacks could disturb the normal functioning of the cognitive radio network. Primary user emulation attacks are one of the most severe attacks in which a malicious user emulates the primary user signal characteristics to either prevent other legitimate secondary users from accessing the idle channels or causing harmful interference to the primary users. There are several proposed approaches to detect the primary user emulation attackers. However, most of these techniques assume that the primary user location is fixed, which does not make them valid when the primary user is mobile. In this paper, we propose a new approach based on the Kalman filter framework for detecting the primary user emulation attacks with a non-stationary primary user. Several experiments have been conducted and the advantages of the proposed approach are demonstrated through the simulation results.Comment: 14 pages, 9 figure

Ant-colony and nature-inspired heuristic models for NOMA systems: a review

The increasing computational complexity in scheduling the large number of users for non-orthogonal multiple access (NOMA) system and future cellular networks lead to the need for scheduling models with relatively lower computational complexity such as heuristic models. The main objective of this paper is to conduct a concise study on ant-colony optimization (ACO) methods and potential nature-inspired heuristic models for NOMA implementation in future high-speed networks. The issues, challenges and future work of ACO and other related heuristic models in NOMA are concisely reviewed. The throughput result of the proposed ACO method is observed to be close to the maximum theoretical value and stands 44% higher than that of the existing method. This result demonstrates the effectiveness of ACO implementation for NOMA user scheduling and grouping

Comparative study between metaheuristic algorithms for internet of things wireless nodes localization

Wireless networks are currently used in a wide range of healthcare, military, or environmental applications. Wireless networks contain many nodes and sensors that have many limitations, including limited power, limited processing, and narrow range. Therefore, determining the coordinates of the location of a node of the unknown location at a low cost and a limited treatment is one of the most important challenges facing this field. There are many meta-heuristic algorithms that help in identifying unknown nodes for some known nodes. In this manuscript, hybrid metaheuristic optimization algorithms such as grey wolf optimization and salp swarm algorithm are used to solve localization problem of internet of things (IoT) sensors. Several experiments are conducted on every meta-heuristic optimization algorithm to compare them with the proposed method. The proposed algorithm achieved high accuracy with low error rate (0.001) and low power consumption

Reliable and efficient data dissemination schemein VANET: a review

Vehicular ad-hoc network (VANET), identified as a mobile ad hoc network MANETs with several added constraints. Basically, in VANETs, the network is established on the fly based on the availability of vehicles on roads and supporting infrastructures along the roads, such as base stations. Vehicles and road-side infrastructures are required to provide communication facilities, particularly when enough vehicles are not available on the roads for effective communication. VANETs are crucial for providing a wide range of safety and non-safety applications to road users. However, the specific fundamental problem in VANET is the challenge of creating effective communication between two fast-moving vehicles. Therefore, message routing is an issue for many safety and non-safety of VANETs applications. The challenge in designing a robust but reliable message dissemination technique is primarily due to the stringent QoS requirements of the VANETs safety applications. This paper investigated various methods and conducted literature on an idea to develop a model for efficient and reliable message dissemination routing techniques in VANET