Transmission protocols in Cognitive Radio Mesh Networks

A Cognitive Radio (CR) is a radio that can adjust its transmission limit based on available spectrum in its operational surroundings. Cognitive Radio Network (CRN) is made up of both the licensed users and unlicensed users with CR enable and disabled radios. CR’S supports to access dynamic spectrum and supports secondary user to access underutilized spectrum efficiently, which was allocated to primary users. In CRN’S most of the research was done on spectrum allocation, spectrum sensing and spectrum sharing. In this literature, we present various Medium Access (MAC) protocols of CRN’S. This study would provide an excellent study of MAC strategies

Software Defined Radio, a perspective from education

The evolution of communication systems has brought about a paradigm shift, particularly in radiocommunications, where software has increasingly taken precedence over hardware. This transition has not only reduced implementation costs but has also significantly enhanced the flexibility of equipment architecture. A prime example of this trend is the emergence and consolidation of software-defined radio (SDR) technology in recent decades. This study provides a comprehensive contextualization of SDR technology, offering insights into its current state in terms of development tools and market equipment. Additionally, two learning scenarios are presented that employ different teaching methodologies. In one of these scenarios, communication theory is exclusively approached from a theoretical perspective. In the second scenario, knowledge acquisition is encouraged through the implementation of low-cost laboratories that incorporate SDR technology. The study indicates that implementing SDR technology boosts student motivation and learning, with 73.13% believing it enhances engineering education and 96% showing increased motivation. Those using SDR in practical laboratories perform better on knowledge tests, but statistical analysis shows that the difference is not statistically significant

Spectrum and transmission range aware clustering for cognitive radio ad hoc networks

Cognitive radio network (CRN) is a promising technology to overcome the problem of spectrum shortage by enabling the unlicensed users to access the underutilization spectrum bands in an opportunistic manner. On the other hand, the hardness of establishing a fixed infrastructure in specific situations such as disaster recovery, and battlefield communication imposes the network to have an ad hoc structure. Thus, the emerging of Cognitive Radio Ad Hoc Network (CRAHN) has accordingly become imperative. However, the practical implementation of CRAHN faced many challenges such as control channel establishment and the scalability problems. Clustering that divides the network into virtual groups is a reliable solution to handle these issues. However, previous clustering methods for CRAHNs seem to be impractical due to issues regarding the high number of constructed clusters and unfair load distribution among the clusters. Additionally, the homogeneous channel model was considered in the previous work despite channel heterogeneity is the CRN features. This thesis addressed these issues by proposing two clustering schemes, where the heterogeneous channel is considered in the clustering process. First, a distributed clustering algorithm called Spectrum and Transmission Range Aware Clustering (STRAC) which exploits the heterogeneous channel concept is proposed. Here, a novel cluster head selection function is formulated. An analytical model is derived to validate the STRAC outcomes. Second, in order to improve the bandwidth utilization, a Load Balanced Spectrum and Transmission Range Aware Clustering (LB-STRAC) is proposed. This algorithm jointly considers the channel heterogeneity and load balancing concepts. Simulation results show that on average, STRAC reduces the number of constructed clusters up to 51% compared to conventional clustering technique, Spectrum Opportunity based Clustering (SOC). In addition, STRAC significantly reduces the one-member cluster ratio and re-affiliation ratio in comparison to non-heterogeneity channel consideration schemes. LB-STRAC further improved the clustering performance by outperforming STRAC in terms of uniformity and equality of the traffic load distribution among all clusters with fair spectrum allocation. Moreover, LB-STRAC has been shown to be very effective in improving the bandwidth utilization. For equal traffic load scenario, LB-STRAC on average improves the bandwidth utilization by 24.3% compared to STRAC. Additionally, for varied traffic load scenario, LB-STRAC improves the bandwidth utilization by 31.9% and 25.4% on average compared with STRAC for non-uniform slot allocation and for uniform slot allocation respectively. Thus, LB-STRAC is highly recommended for multi-source scenarios such as continuous monitoring applications or situation awareness applications

Radio cognitiva – Estado del arte

The wireless technology is growing very quickly, in the actuality the new technologies applied to the radius link appear with a multiplicity of names that change as the application and the use that do of them: Bluetooth, GSM, Microwaves, Links Satellites, Wi-Fi, WiMax, ZigBee, etc. Each system uses a hardware and devoted software and exclusive chord to his functionalities to send and receive the waves of radio. Some of these bands of the spectrum can justify by the fact that some applications work better in determinate spaces inside the spectrum electric radio. This exponential growth of wireless applications creates an every time main demand of spectrum electric radio what has motivated the research of technologies of radio that can scalar to satisfy the future demands, so much in terms of efficiency of spectrum and performance of the applications.El crecimiento de la tecnología radio en los últimos años ha sido muy grande y presenta retos importantes para el uso adecuado del espectro. Es bien conocido que el uso actual del espectro radio no es el más eficiente, por lo que se han planteado tecnologías que permitan usar de manera más eficiente este espectro. Los desarrollos en tecnologías de Radio Software en los años noventa y en la primera década del 2000, han permitido que la tecnología de Radio Cognitivo empiece a tomar fuerza en diversos ámbitos de los sistemas de radio. En este artículo se hace una revisión detallada de esta tecnología y los avances recientes, así como algunos de los retos por superar

A Survey on the Communication Protocols and Security in Cognitive Radio Networks

A cognitive radio (CR) is a radio that can change its transmission parameters based on the perceived availability of the spectrum bands in its operating environment. CRs support dynamic spectrum access and can facilitate a secondary unlicensed user to efficiently utilize the available underutilized spectrum allocated to the primary licensed users. A cognitive radio network (CRN) is composed of both the secondary users with CR-enabled radios and the primary users whose radios need not be CR-enabled. Most of the active research conducted in the area of CRNs has been so far focused on spectrum sensing, allocation and sharing. There is no comprehensive review paper available on the strategies for medium access control (MAC), routing and transport layer protocols, and the appropriate representative solutions for CRNs. In this paper, we provide an exhaustive analysis of the various techniques/mechanisms that have been proposed in the literature for communication protocols (at the MAC, routing and transport layers), in the context of a CRN, as well as discuss in detail several security attacks that could be launched on CRNs and the countermeasure solutions that have been proposed to avoid or mitigate them. This paper would serve as a good comprehensive review and analysis of the strategies for MAC, routing and transport protocols and security issues for CRNs as well as would lay a strong foundation for someone to further delve onto any particular aspect in greater depth

Performance analysis of channel assignment schemes for coordinated cognitive WLAN networks

Nowadays local wireless networks are very used by an elevated number of people and its use continues rising. This provokes an increase of the interference and as consequence, congestion in the non-licensed band of 2.4GHz, caused by the increase of users in a given zone and thus, the limitation of channels offered by this band. As a solution to this problem, in this project it is studied the possibility of using additional channels from licensed bands used for other radio-communications services. The use of these channels in the local network (named in this context as secondary user of this spectrum) is done in an opportunistic manner, when ever it does not provoke any interference to the users of the service which have the rights to use this spectrum (named primary users in this context), since these ones have priority to access these bands of the spectrum. As a first approximation to the solution of the assignment problem, it is studied the behaviour of a random channel assignment in a scenario with a certain density of local networks that can generate interference between them and where the availability of the primary channel for opportunistic use is not homogeneous. Later, stated the possibility of improving the level of interference even with a random channel assignment, there are proposed two channel assignment methods designed to have in concern the availability of primary channels. The first method is set out through the formulation of an Integer Linear Programming (ILP) problem, which allows obtaining an optimal solution but with an elevated execution time. The other method is an heuristic one based on obtaining a Minimum Spanning Tree (MST) on interference terms, which allows to obtain near-optimal solutions in less time of execution. In the project it is done a detailed comparison of these two methods to contrast the advantages of each one. Finally, there are identified some aspects of the implementation of these methods in a real scenario

Spectrum sharing through distributed coordination in dynamic spectrum access networks

Spectrum sharing in Open Spectrum systems is a challenging problem, particularly since users experience dynamic spectrum availabilities that vary over time and location. In the absence of any centralized infrastructure, users coordinate their spectrum usage to support fair access of spectrum and avoid interference. One critical challenge is to construct an efficient signaling path in the presence of spectrum dynamics, where users exchange control and negotiation information reliably. In this paper, we propose a distributed coordination protocol (HD-MAC) to construct an in-band control path, without relying on the existence of a pre-assigned out-of-band control channel. In particular, we propose a distributed group formation to construct coordination path using local common channels, and a heterogeneity-aware ranking scheme to select channels for data transmissions. Extensive experimental results demonstrate the efficiency and reliability of the proposed approach. Copyright © 2007 John Wiley & Sons, Ltd.link_to_subscribed_fulltex

Spectrum Sharing through Distributed Coordination in Dynamic Spectrum Access Networks

Abstract — Spectrum sharing in open spectrum systems is a challenging problem, particularly since users experience dynamic spectrum availabilities that vary over time and location. In the absence of any centralize infrastructure, users coordinate their spectrum usage to support fair access of spectrum and avoid interference. One critical challenge is to construct an efficient signalling path in the presence of spectrum dynamics, where users exchange control and negotiation information reliably. In this paper we propose a distributed coordination protocol (HD-MAC) to construct an in-band control path without relying on the existence of a pre-assigned out-of-band control channel. In particular, we propose a distributed group formation to construct coordination path using local common channels, and a heterogeneity-aware ranking scheme to select channels for data transmissions. Extensive experimental results demonstrate the efficiency and reliability of the proposed approach. I

Machine Learning Approach for Spectrum Sharing in the Next Generation Cognitive Mesh Network

Nowadays, there is an unexpected explosion in the demand for wireless network resources. This is due to the dramatic increase in the number of the emerging web-based services. For wireless computer network, limited bandwidth along with the transmission quality requirements for users, make quality of service (QoS) provisioning a very challenging problem. To overcome spectrum scarcity problem, Federal Communications Commission (FCC) has already started working on the concept of spectrum sharing where unlicensed users (secondary users, SUs) can share the spectrum with licensed users (primary users, PUs), provided they respect PUs rights to use spectrum exclusively. Cognitive technology presents a revolutionary wireless communication where users can exploit the spectrum dynamically. The integration of cognitive technology capability into the conventional wireless networks is perhaps the significant promising architectural upgrade in the next generation of wireless network that helps to solve spectrum scarcity problem. In this work, we propose integrating cognitive technology with wireless mesh network to serve the maximum number of SUs by utilizing the limited bandwidth efficiently. The architecture for this network is selected first. In particular, we introduce the cluster-based architecture, signaling protocols, spectrum management scheme and detailed algorithms for the cognitive cycle. This new architecture is shown to be promising for the cognitive network. In order to manage the transmission power for the SUs in the cognitive wireless mesh network, a dynamic power management framework is developed based on machine learning to improve spectrum utilization while satisfying users requirements. Reinforcement learning (RL) is used to extract the optimal control policy that allocates spectrum and transmission powers for the SUs dynamically. RL is used to help users to adapt their resources to the changing network conditions. RL model considers the spectrum request arrival rate of the SUs, the interference constraint for the PUs, the physical properties of the channel that is selected for the SUs, PUs activities, and the QoS for SUs. In our work, PUs trade the unused spectrum to the SUs. For this sharing paradigm, maximizing the revenue is the key objective of the PUs, while that of the SUs is to meet their requirements and obtain service from the rented spectrum. However, PUs have to maintain their QoS when trading their spectrum. These complex conflicting objectives are embedded in our machine learning model. The objective function is defined as the net revenue gained by PUs from renting some of their spectrum. We use a machine learning to help the PUs to make a decision about the optimal size and price of the offered spectrum for trading. The trading model considers the QoS for PUs and SUs, traffic load at the PUs, the changes in the network conditions, and the revenues of the PUs. Finally, we integrate all the mechanisms described above to build a new cognitive network where users can interact intelligently with network conditions

Resource Management in Cognitive Radio Networks

In the last decade, the world has witnessed rapid increasing applications of wireless networks. However, with the fixed spectrum allocation policy that has been used since the beginning of the spectrum regulation to assign different spectrum bands to different wireless applications, it has been observed that most of the allocated spectrum bands are underutilized. Therefore, if these bands can be opportunistically used by new emerging wireless networks, the spectrum scarcity can be resolved. Cognitive Radio (CR) is a revolutionary and promising technology that can identify and then exploit the spectrum opportunities. In Cognitive Radio Networks (CRNs), the spectrum can be utilized by two kinds of users: Primary Users (PUs) having exclusive licenses to use certain spectrum bands for specific wireless applications, and Secondary Users (SUs) having no spectrum licenses but seeking for any spectrum opportunities. The SUs can make use of the licensed unused spectrum if they do not make any harmful interference to the PUs. However, the variation of the spectrum availability over the time and locations, due to the coexistence with the PUs, and the spread of the spectrum opportunities over wide spectrum bands create a unique trait of the CRNs. This key trait poses great challenges in different aspects of the radio resource management in CRNs such as the spectrum sensing, spectrum access, admission control, channel allocation, Quality-of-Service (QoS) provisioning, etc. In this thesis, we study the resource management of both single-hop and multi-hop CRNs. Since most of the new challenges in CRNs can be tackled by designing an efficient Medium Access Control (MAC) framework, where the solutions of these challenges can be integrated for efficient resource management, we firstly propose a novel MAC framework that integrates a kind of cooperative spectrum sensing method at the physical layer into a cooperative MAC protocol considering the requirements of both the SUs and PUs. For spectrum identification, a computationally simple but efficient sensing algorithm is developed, based on an innovative deterministic sensing policy, to assist each sensing user for identifying the optimum number of channels to sense and the optimum sensing duration. We then develop an admission control scheme and channel allocation policy that can be integrated in the proposed MAC framework to regulate the number of sensing users and number of access users; therefore, the spectrum identification and exploitation can be efficiently balanced. Moreover, we propose a QoS-based spectrum allocation framework that jointly considers the QoS provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users with the spectrum sensing, spectrum access decision, and call admission control. We analyze the proposed QoS-based spectrum allocation framework and find the optimum numbers of the RT and NRT users that the network can support. Finally, we introduce an innovative user clustering scheme to efficiently manage the spectrum identification and exploitation in multi-hop ad hoc CRNs. We group the SUs into clusters based on their geographical locations and occurring times and use spread spectrum techniques to facilitate using one frequency for the Common Control Channels (CCCs) of the whole secondary network and to reduce the co-channel interference between adjacent clusters by assigning different spreading codes for different clusters. The research results presented in this thesis contribute to realize the concept of the CRNs by developing a practical MAC framework, spectrum sensing, spectrum allocation, user admission control, and QoS provisioning for efficient resource management in these promising networks