Cognitive Radio Network Architecture Research Articles

Priority-based band sharing for secondary users in cognitive radio networks

To improve wireless spectrum utilization, cognitive radio networks (CRNs) allow secondary users (SUs) opportunistic access to the frequency bands owned by primary users (PUs), when such PUs are inactive. A fully distributed CRN architecture is quite favorable, as it does not require any centralized scheduling, nor does it require coordination between SUs via a common control channel. This can reduce cost and avoid single point-of-failure issues. However, uncoordinated access to the spectrum by competing SUs, if not done judiciously, can cause excessive collisions and limit performance, which can be detrimental to the usefulness of CRNs, especially if some SUs have urgent traffic to send. Hence, we present a novel protocol to support traffic with multiple classes of priority within a fully distributed CRN. In such protocol, competing SUs attempt to access the spectrum autonomously, but rationally, based on their priority level, opting to transmit their packets when it is beneficial to both the SU itself and also to the overall system performance. Simulations confirm that the proposed protocol achieves excellent overall network performance, while ensuring that higher priority packets experience higher throughput and smaller delay compared to lower priority packets.

Cognitive radio network architecture for GEO and LEO satellites shared downlink spectrum

The fixed spectrum assignment policy in the space sector and large constellations of Low Earth Orbit (LEO) satellites left little or no spectrum available for future LEO satellite communications services. Cognitive Radio (CR) technology enables spectrum sharing between primary and secondary users without limiting the transmission power, and thus is of great interest to commercial and defense entities. A number of Radio Environment Map (REM) techniques have been making Cognitive Radio Networks (CRNs) practical by constructing a comprehensive map of the CRN by utilizing multi-domain information from geolocation databases, characteristics of spectrum use, geographical terrain models, propagation environment, and regulations. In this paper, we investigate spectrum sharing for a network comprised of a Geostationary Orbit (GEO) and a LEO satellite with a multibeam antenna array. A CRN architecture of GEO and LEO satellites shared downlink spectrum is proposed and details are provided covering its architecture, REM structure and channel utilization data aggregation, as well as a frequency slot assignment mechanism.

Performance Improvement of Next-Generation Network with Cognitive Radio Network and Coordinated Multipoint Joint Transmission

Cognitive Radio Network (CRN) is a favourable technology for the future of wireless networks. It aims to seamlessly exploit spectrum resources by opportunistically using the unused or underused radio spectrum that is licensed. Cognitive Radio Network is a technology that is planned to be used in the 5th Generation of wireless communication. This technology is belied to be the answer to the unused and underused radio spectrum in the Radio environment. Whereas Coordinated Multipoint Joint Transmission (CoMP JT) is a technology that has already been used, first used in 3GPP LTE-Advanced. Coordinated Multipoint Joint Transmission aims to improve the performance of the cellular network. In this report, Cognitive Radio Network is being implemented along with Coordinated Multipoint Joint Transmission techniques. An inclusive and layered architecture of Cognitive Radio Network along with Coordinated multipoint Joint Transmission is being designed in this report, showing different technologies and different steps involved in the concept of this combination. Then the impact of CoMP JT on CRN is being studied. By implementing CoMP JT on CRN, it has been able to show how the performance of CRN is changing when implemented alone and when implemented with CoMP JT and some of the significant results are being depicted to better understand the changes in CRN with CoMP JT. Lastly, a study is performed on the combination of Cognitive Radio Network and Coordinated Multipoint Joint Transmission. As far as the investigation is being performed, two factors have been considered, which is: Signal to Interference plus Noise Ratio (SINR) and Total Average Throughput (TAT). The detailed study is being performed in this report and is being implemented in three different environments. Hence the results are being compared and a conclusion is being drawn based on these results.

SDN‐enabled Cognitive Radio Network Architecture

In this study, a new network architecture based on the software-defined networking (SDN) approach is proposed for cognitive radio networks (CRNs). The proposed network architecture [software-defined cognitive radio (SDCR)] assumes the responsibilities of network resource management for CRNs and provides a dynamic spectrum management mechanism with an SDN controller. In this way, the dependency of network users on base stations is reduced in dynamic cognitive radio environments, and network performance is improved by delegating some of the management responsibilities to the controller. The performance analysis of the SDCR is carried out through the RIVERBED MODELER simulation software. End-to-end delays and packet loss rates for the primary network are investigated by selecting different offered loads for secondary users. In addition, for the equal and different packet sizes, primary network and SDCR throughput are examined and network performance is improved by using channel bonding technique. The results indicate that the SDCR outperforms the traditional CRN architecture, in terms of the throughput, and the proposed architecture can provide effective performance. Bit error rate parameter is investigated in the study and the energy consumption parameter of the SDCR is also compared with the cognitive radio wireless network.

Energy aware resource allocation and complexity reduction approach for cognitive radio networks using game theory

Nowadays, the demand for mobile wireless communication systems has increased drastically due to its significant use for various real-time applications. This increased demand for communication causes heavy utilization of the radio spectrum to improve ubiquitous computing services. However, systems providing high-speed communication fail to achieve the desired performance due to unsystematic spectrum utilization and resources. The problem addressed by Cognitive Radio Network (CRN) architecture has attracted research and industrial community to enhance the real-time communication systems. Although CRN based real-time communication systems suffer from resource allocation, spectrum sensing, and power consumption issues. In this paper, we introduce a novel approach for resource allocation and sharing based on cooperative game theory, and cooperative node selection ensures maximized payoff. The proposed method optimizes the overhead, energy consumption, and resource utilization. Further, energy consumption and resource allocation issues transformed into an optimization problem. A backtracking search algorithm is applied to reduce the computation complexity and to find the optimal solution for resource utilization. The simulation result obtained achieves better performance compared to the existing energy-aware scheduling approach in CRN.

A Software Defined Radio Cross-Layer Resource Allocation Approach for Cognitive Radio Networks: From Theory to Practice

Software Defined Radio (SDR)-enabled cognitive radio network architectures are expected to play an important role in the future 5G networks. Despite the increased research interest, the current implementations are of small-scale and provide limited functionality. In this paper, we contribute towards the alleviation of the limitations in SDR deployments by developing and evaluating a resource allocation approach for cognitive radios implemented with SDR technology over two testbeds of the ORCA federation. Resource allocation is based on a Markov Random Field (MRF) framework realizing a distributed cross-layer computation for the secondary nodes of the cognitive radio network. The proposed framework implementation consists of self-contained modules developed in GNU Radio realizing cognitive functionalities, such as spectrum sensing, collision detection, etc. We demonstrate the feasibility of the MRF based resource allocation approach and provide extensive results and performance analysis that highlight its key features. The latter provide useful insights about the advantages of our framework, while allowing to pinpoint current technological barriers of broader interest.

Dynamic Interference Optimization in Cognitive Radio Networks for Rural and Suburban Areas

In this paper, we investigate the coexistence of cognitive radio networks on TV white spaces for rural and suburban connectivity. Although experimental models and laboratory measurements defined the maximum interference threshold for TV white space technologies for general use cases, our research found that in real wireless rural and suburban scenarios, severe interference to the broadcasting services might occur. This is particularly relevant when the traffic load of the telecom base stations (BSs) exceeds 80% of their maximum capacity. We propose a dynamic management algorithm for minimizing the interference, based on a centralized access control architecture for cognitive radio wireless networks. In an experimental emulation for assessing the impact of cognitive radio interference on the broadcasting service’s QoE, our method reduced the perceived video distortion by the broadcasting users by at least 50% and 27.5% in a rural and suburban scenario, respectively, while the spectrum usage is increased by just 8%.

Review on cross‐layer design for cognitive ad‐hoc and sensor network

Most of the ad-hoc networks including wireless sensor network operates in unlicensed spectrum bands (e.g. 2.4 GHz ISM band), which is shared by other wireless technologies. This leads to coexistent interference and degrades the performance of ad-hoc sensor network (AHSN). Introducing cognitive radio (CR) concept in AHSN, the unutilised licensed spectrum (white spaces) can be used opportunistically without disturbing licensed holders. Conventional TCP/IP layered architecture for CR network lacks in mobility, data transfer performance, energy efficiency, quality of service and so on. Coupling of some of the layers allows coordination, interaction and joint optimisation of protocols to achieve significant performance improvements for CR-AHSN. Of late, many researches are going on different approaches of using CR for reusing unused spectrum and enhancing total system capacity. This study presents a comprehensive review of various cross-layer design approaches in CR sensor network.

Secure Data Transmission by Detecting Different Attacks in CRN to improve the throughput

Cognitive Radio (CR) is a technology that promises to solve the data transmission problem by allowing secondary users to coexist with primary user without causing any interference to the communication. It means to improve the usage of the radio assets to improve the throughput. Despite the fact that the operational parts of CR are being investigated broadly, its security viewpoints have increased little consideration. In this work, present a CRN architecture , Different Protocol, with complete rundown of major known security dangers and assaults inside a Cognitive Radio Network (CRN). Our goal in this paper is to dissect the distinctive security issues of the primary ongoing advancements of Cognitive Radio Networks with proper resource allocation to improve the throughput.

Analysis of the On-Demand Spectrum Access Architecture for CBRS Cognitive Radio Networks

An on-demand spectrum access cognitive radio network offers spectrum services to users, so that users can dynamically set up application-oriented virtual topologies to support user applications. In this paper, we develop a mathematical model for the on-demand spectrum access architecture for cognitive radio networks based on the citizens broadband radio service (CBRS). The model can be used to estimate the blocking probability of spectrum demands from priority access license users, the network capacity, and the number of free spectrum bands available for lower priority general authorized access users. The performance evaluation indicates that the results from the mathematical model match simulation results well, which validates the accuracy of our model.

A novel cloud based self-adaptive cognitive radio network architecture

The constraints of battery, data processing and memory in mobile Secondary User (SU) in a Cognitive Radio Network (CRN) make it essential to move the spectrum sensing functionality from the SUs to the network. The cloud performing the role of the earlier defined “Spectrum Agent” or “Spectrum Monitoring Device” has a scope of taking up the computational tasks of spectrum sensing and path selection. The paper presents a novel cloud based self-adaptive network architecture for a multi-hop cognitive radio system including its communication protocol. A new method of optimal multi-hop relay selection based on Critical Path Method (CPM) is also introduced for execution in the cloud having network connectivity information. The proposed network architecture and relay selection scheme is analyzed and the performance tested with respect to the reported methods to show its strength in terms of end-to-end delay and reliability. A closed-form expression of outage probability of failed transmission for a generic multi-hop network is also analytically derived and used for testing the reliability of the proposed architecture. The results are encouraging to extend the use of CRN in dynamic environment of large deployment areas.

Adaptive resource allocation with traffic peak duration prediction and admission control for cognitive Wi-Fi networks

Cognitive radio network (CRN) architecture can be efficiently utilized to support different QoS requirements under variable traffic and channel conditions. Generally, deterministic radio resource allocation algorithms could significantly increase the channel utilization as well as the network QoS. In this paper, we propose an advanced cognitive network resource allocation algorithm for IEEE 802.11 cognitive Wi-Fi networks. By making use of the status of the transmission channels and the traffic conditions, the proposed algorithm effectively allocates secondary radio resources to improve the overall radio resource utilization and the QoS of the CSMA/CA-based networks. To improve the accuracy and efficiency of the proposed algorithm, a Markov chain model based technique that estimates the achievable network throughput is employed. Furthermore, an autoregressive moving average (ARMA) based model is used to predict the traffic peaks when allocating the channels. OMNeT++ based simulation models are then developed to analyze the performance of the proposed algorithm. It is shown that our predictive resource allocation technique offers higher throughput and QoS compared to existing resource allocation techniques.

Cognitive Capacity Harvesting Networks: Architectural Evolution Toward Future Cognitive Radio Networks

Cognitive radio technologies enable users to opportunistically access unused licensed spectrum and are viewed as a promising way to deal with the current spectrum crisis. Over the last 15 years, cognitive radio technologies have been extensively studied from algorithmic design to practical implementation. One pressing and fundamental problem is how to integrate cognitive radios into current wireless networks to enhance network capacity and improve users’ experience. Unfortunately, existing solutions to cognitive radio networks (CRNs) suffer from many practical design issues. To foster further research activities in this direction, we attempt to provide a tutorial for CRN architecture design. Noticing that an effective architecture for CRNs is still lacking, in this tutorial, we systematically summarize the principles for CRN architecture design and present a novel flexible network architecture, termed cognitive capacity harvesting network (CCHN), to elaborate on how a CRN architecture can be designed. Unlike existing architectures, we introduce a new network entity, called secondary service provider, and deploy cognitive radio capability enabled routers, called cognitive radio routers, in order to effectively and efficiently manage resource harvesting and mobile traffic while enabling users without cognitive radios to access and enjoy CCHN services. Our analysis shows that our CCHN aligns well to industrial standardization activities and hence provides a viable approach to implementing future CRNs. We hope that our proposed design approach opens a new venue to future CRN research.

Modified hybrid interference cancellation algorithm for uplink cognitive radio transmission based on overloaded DS-CDMA

In this paper, cognitive radio network architecture based on overloaded direct sequence code division multiple access (O-DS-CDMA) is proposed. In this method, secondary users are enabled to share the available bandwidth with the existing primary users. Two sets of orthogonal Gold codes are used to support the primary and secondary users simultaneously. Orthogonality between the spreading codes is lost due to non-zero cross correlation between the codes and timing synchronisation error in the uplink transmission, which causes interference among primary and secondary users. In this paper, a modified hybrid parallel/successive interference cancellation algorithm is proposed for the primary and secondary user base station receivers with multiple antennas, to suppress the interference among the users. Interferences among same group users are cancelled using parallel interference cancellation and the interferences between groups are cancelled using successive interference cancellation. The simulation results show that, the proposed modified interference cancellation algorithm improves the BER performance of the system significantly.

Joint detection scheme for cooperative spectrum sensing in cognitive radio network

In this paper, a new architecture of cognitive radio network (CRN) is presented for future dynamic spectrum sharing in time-variant flat fading (TVFF) channels. We consider a practical scenario where secondary users (SUs) are able to access the idle spectrum by secondary user routers (SU_Rs). Managed by a fusion center (FC), SU_Rs can work together to capture the idle spectrum, and then assign to the SUs. Besides, it is imperative to guarantee the wireless communication quality between primary base station (P_BS) and SU_Rs. Therefore, a new cooperative spectrum sensing (CSS) algorithm is suggested to recursively estimate the channel state information (CSI) while capturing the idle licensed band. The united mathematics model relies on a dynamic state-space model (DSM) and a Bernoulli filters (BF) algorithm. TVFF channels are modeled as finite-state Markov channel (FSMC). In order to reduce complexity of CSS, the particles are manipulated and reconstructed. Experimental simulations demonstrate that, by exploiting dynamic CSI, sensing performance of the new CSS algorithm will surpass the traditional schemes and this new architecture can be used in a realistic spectrum sharing system.

Implementation of OpenFlow based cognitive radio network architecture: SDN&R

The static conventional network architecture is ill-suited to the growing management complexity and highly dynamic wireless network topologies. Software Defined Radio systems and their extension to cognitive and smart radio are characterized by distinct control loops for management which constantly increase network complexity and management inefficiencies, due to clear-cut between radio and core network management. Adding numerous devices and networks together will constantly increase the management cost, thus hinders scalability. Therefore, a holistic solution to synchronize radio and networks status has an elevated demand. To interconnect these systems and devices together, there is a need for a common management interface. OpenFlow is the first standard interface that enables Software Defined Networking (SDN). It can be rolled out in a variety of networking devices to enable improved automation and management by using common Application Program Interfaces to abstract the underlying networking details. The Software Defined Networking & Radio (SDN&R) framework proposed here has a potential combination between SDN and Radio networks to discover the underlying dynamism in cognitive access networks with integrated radio management. By isolating the control plane from the data plane, SDN&R enables a flexible management framework empowered by end-to-end goals through OpenFlow. In this article, we propose, validate, and evaluate the SDN&R architecture. In doing so, first we implement the OpenFlow enabled cognitive basestations (BSs) on Wireless Open-Access Research Platform. Furthermore, we develop software agents on BSs to provide radio status information to the cognitive control application implemented on the SDN controller. The results verify that the proposed framework in-lines with layer-2 or layer-3 forwarding performance. We claim that this work represents the first successful implementation results which synergizes SDN with Cognitive networks that motivates researchers towards SDN based radio resource management.

An energy-aware scheme for efficient spectrum utilization in a 5G mobile cognitive radio network architecture

This paper proposes an energy-efficient delay-aware cooperative scheme, exploited for efficient resource management and maximum energy conservation in a 5G mobile cognitive radio network architecture. The proposed scheme is based on the comparison of the queuing delays of both the secondary nodes and the Radio Access Points, when delay sensitive transmission is requested, providing optimal TV White Spaces exploitation via a spectrum broker. The spectrum broker manages the process of the energy consumption of the 5G mobile communication systems, according to the proposed delay-aware cooperative scheme and the comparative evaluation of the queuing delays. The validity of the performance of the scheme is verified through extended simulation tests, carried out under controlled experimental conditions.

Cognitive Radio Ad-Hoc Network Architectures: A Survey

Combating the growing necessity of radio spectrum, which is a limited natural resource, proper utilization of the radio spectrum is a must. Cognitive radio network (CRN) plays a vibrant role to solve this spectrum scarcity problem. Cognitive radio uses an open spectrum allocation technique to make more efficient utilization of the wireless radio spectrum and reduces the bottleneck on the frequency bands. Thus, accessible spectrum information is required for communication in CRN, which can be acquired by using spectrum database or by spectrum sensing. In addition, a robust architecture with appropriate communication protocol is preconditioned in the deployment of CRN. The state of the art of cognitive radio ad-hoc network architecture is surveyed in this paper, where the paper specifies the formation mechanisms and performance evaluations of the studied architectures. The reviewed papers have addressed some vital issues for the concrete deployment of cognitive radio ad-hoc network; however, there remain some issues that need to be addressed. Thus, this paper conveys a thorough and abstract understanding of cognitive radio ad-hoc network architecture, and also points out some open research issues in this area.

Performance Analysis of Uplink Cognitive Radio Transmission based on Overloaded MC-DS-CDMA

This paper reports a cognitive radio network architecture based on overloaded multicarrier direct sequence code division multiple access (O-MC-DS-CDMA). The O-MC-DSCDMA technique combines CDMA with a multicarrier modulation technique to overcome the channel fading effects. In this technique, secondary users are enabled to share the available bandwidth with the existing primary users. Two sets of orthogonal Gold codes are used to support the primary and secondary users simultaneously. The orthogonality between the spreading codes is lost due to the non-zero cross correlation between the codes and the timing synchronization error in the uplink transmission, which causes interference between primary and secondary users. This paper proposes two modified hybrid parallel/successive interference cancellation techniques for primary and secondary user base station receivers with multiple antennas to suppress the interference among users. Interference among the same group of users is cancelled by parallel interference cancellation and the interference among groups is cancelled using successive interference cancellation. The simulation results confirmed that the proposed modified interference cancellation techniques show better BER performance over conventional interference cancellation techniques.

Cognitive radio networks

A large volume of research has been conducted in the cognitive radio (CR) area the last decade. However, the deployment of a commercial CR network is yet to emerge. A large portion of the existing literature does not build on real world scenarios, hence, neglecting various important aspects of commercial telecommunication networks. For instance, a lot of attention has been paid to spectrum sensing as the front line functionality that needs to be completed in an efficient and accurate manner to enable an opportunistic CR network architecture. While on the one hand it is necessary to detect the existence of spectrum holes, on the other hand, simply sensing (cooperatively or not) the energy emitted from a primary transmitter cannot enable correct dynamic spectrum access. For example, the presence of a primary transmitter's signal does not mean that CR network users cannot access the spectrum since there might not be any primary receiver in the vicinity. Despite the existing solutions to the DSA problem no robust, implementable scheme has emerged. The set of assumptions that these schemes are built upon do not always hold in realistic, wireless environments. Specific settings are assumed, which differ significantly from how existing telecommunication networks work. In this paper, we challenge the basic premises of the proposed schemes. We further argue that addressing the technical challenges we face in deploying robust CR networks can only be achieved if we radically change the way we design their basic functionalities. In support of our argument, we present a set of real-world scenarios, inspired by realistic settings in commercial telecommunications networks, namely TV and cellular, focusing on spectrum sensing as a basic and critical functionality in the deployment of CRs. We use these scenarios to show why existing DSA paradigms are not amenable to realistic deployment in complex wireless environments. The proposed study extends beyond cognitive radio networks, and further highlights the often existing gap between research and commercialization, paving the way to new thinking about how to accelerate commercialization and adoption of new networking technologies and services.