Energy Efficient Power Allocation In Cognitive Radio Network

Energy efficient wireless cellular networks have been the subject of intense research in recent years. Green radio networks are the demand of new era of communication system. In order to improve the energy of cognitive radio network, the technique for power allocation in transmission link is proposed in this paper. Recently, many technological and network issues like interference and resource allocation or power optimization in cognitive radio network have been studied but only in terms of spectrum sensing. Different from the other work, the optimization of power in order to maximize the energy with consideration of imperfect spectrum sensing is proposed. Simulation result shows that for every value of power levels energy will be improved

Beam Selection and Discrete Power Allocation in Opportunistic Cognitive Radio Systems with Limited Feedback Using ESPAR Antennas

We consider an opportunistic cognitive radio (CR) system consisting of a primary user (PU), secondary transmitter (SUtx), and secondary receiver (SUrx), where SUtx is equipped with an electrically steerable parasitic array radiator (ESPAR) antenna with the capability of choosing one beam among M beams for sensing and communication, and there is a limited feedback channel from SUrx to SUtx. Taking a holistic approach, we develop a framework for integrated sector-based spectrum sensing and sector-based data communication. Upon sensing the channel busy, SUtx determines the beam corresponding to PU's orientation. Upon sensing the channel idle, SUtx transmits data to SUrx, using the selected beam corresponding to the strongest channel between SUtx and SUrx. We formulate a constrained optimization problem, where SUtx-SUrx link ergodic capacity is maximized, subject to average transmit and interference power constraints, and the optimization variables are sensing duration, thresholds of channel quantizer at SUrx, and transmit power levels at SUtx. Since this problem is non-convex we develop a suboptimal computationally efficient iterative algorithm to find the solution. Our results demonstrate that our CR system yields a significantly higher capacity, and lower outage and symbol error probabilities, compared with a CR system that its SUtx has an omni-directional antenna.Comment: This paper has been submitted to IEEE Transactions on Cognitive Communications and Networkin

A Hierarchical Structure towards Securing Data Transmission in Cognitive Radio Networks

Cognitive Radio (CR) technology is considered as a promising technology to overcome spectrum scarcity problem in wireless networks, by sharing the spectrum between both unlicensed users (secondary users, (SUs)) and licensed users (primary users, (PUs)), provided that the SUs respect the PUs’ rights to use the spectrum exclusively. An important technical area in cognitive radio networks (CRNs) is wireless security. A secure CRN must meet different security requirements, which are: confidentiality, integrity, availability and authentication. Data confidentiality is a mandatory requirement in cognitive radio networks, generally to maintain the privacy of the data owner (PU or SU). Integrity means that data is transmitted from the source to the destination without alteration. While availability is to release the channels assigned to one SU as soon as a PU wants to use its spectrum. Authentication in CRN means that each node has to authenticate itself before it can use the available spectrum channels. New classes of security threats and challenges in CRNs have been introduced that target the different layers of OSI model and affect the security requirements. Providing strong security may prove to be the most difficult aspect of making CR a long-term commercially-viable concept. Protection of routes used for data transmission is a critical prerequisite to ensure the robustness of iv the routing process. Therefore, route discovery must be done in such a way that lets each node find the best secure path(s) for its data transmission. In this work, network security of CRN is improved through proposing different models that are built to fulfil the security requirements mentioned above. Improving the network security enhances the network performance, taking into consideration the quality of service (QoS) desired by the different network nodes such as bandwidth and time delay. This work aims to combine the spectrum sensing phase and the spectrum management phase, as well as to detect all the adversary nodes that slow down the network performance by selectively holding and not forwarding packets to their next hop(s). We measure the network node’s reliability for using network resources through a value called belief level (BL), which is considered as the main parameter for our entire work. BL is used to monitor the nodes’ behavior during the spectrum sensing phase, and then it is used to form the best path(s) during the spectrum management phase. Particularly, this work follows a hierarchical structure that has three different layers. At the bottom layer, a novel authentication mechanism is developed to fulfil the authentication and the availability security requirements, which ends assigning a belief level (BL) to each node. At the middle layer, the nodes’ behavior during the spectrum sensing phase is monitored to detect all the adversary node(s). Finally, at the top layer, a novel routing algorithm is proposed that uses the nodes’ security (BL) as a routing metric. SUs collaborate with each other to monitor other nodes’ behavior. Users’ data confidentiality and integrity are satisfied through this hierarchical structure that uses the cluster-based, central authority, and nodes collaboration concepts. By doing so, the traffic carried in the CRN is secured and adversary nodes are detected and penalized