Scheme For Cognitive Radio Networks Research Articles

Random Relay Selection based Heuristic Optimization Model for the Scheduling and Effective Resource Allocation in the Cognitive Radio Network

Cognitive Radio Network (CRN) provides effective capabilities for resource allocation with the valuable spectrum resources in the network. It provides the effective allocation of resources to the unlicensed users or Secondary Users (SUs) to access the spectrum those are unused by the licensed users or Primary Users (Pus). This paper develops an Optimal Relay Selection scheme with the spectrum-sharing scheme in CRN. The proposed Cross-Layer Spider Swarm Shiftingis implemented in CRN for the optimal relay selection with Spider Swarm Optimization (SSO). The shortest path is estimated with the data shifting model for the data transmission path in the CRN. This study examines a cognitive relay network (CRN) with interference restrictions imposed by a mobile end user (MU). Half-duplex communication is used in the proposed system model between a single primary user (PU) and a single secondary user (SU). Between the SU source and SU destination, an amplify and forward (AF) relaying mechanism is also used. While other nodes (SU Source, SU relays, and PU) are supposed to be immobile in this scenario, the mobile end user (SU destination) is assumed to travel at high vehicle speeds. The suggested method achieves variety by placing a selection combiner at the SU destination and dynamically selecting the optimal relay for transmission based on the greatest signal-to-noise (SNR) ratio. The performance of the proposed CrossLayer Spider Swarm Shifting model is compared with the Spectrum Sharing Optimization with QoS Guarantee (SSO-QG). The comparative analysis expressed that the proposed Cross-Layer Spider Swarm Shifting model delay is reduced by 15% compared with SSO-QG. Additionally, the proposed Cross-Layer Spider Swarm Shiftingexhibits the improved network performance of ~25% higher throughput compared with SSO-QG.

Multi-objective distributed cooperative spectrum sensing for cognitive radio networks using greedy-based coalitional game

In this work, we propose a distributed cooperative spectrum sensing (CSS) scheme for cognitive radio networks applying a greedy-based coalitional game. We formulate the cooperative spectrum sensing problem as a multi-objective optimization problem using the weighted global criteria method. The objective of the formulated problem is to jointly consider the relative impacts of the three key performance metrics in CSS: throughput gain, penalty cost, and energy overhead. By integrating these three distinct metrics into a global optimization problem, we aimed to achieve a well-balanced trade-off, essential for deploying the CSS scheme across diverse network and application environments. We prove that the formulated CSS problem is non-deterministic polynomially hard (NP-hard). The computational complexity of the formulated CSS problem is decreased by proposing a heuristic scheme that produces a sub-optimal solution in polynomial time. We develop the heuristic scheme by putting forward a greedy-based coalitional game theoretic model. The proposed scheme exploits the spatial diversity of secondary users (SUs) in forming distributed coalitions to minimize the effects of attenuation and distortion on the transmitted signal. Further sensing energy overhead is reduced by dynamically deciding the sensing duration for the SUs based on their received signal strength. To establish the stability of the coalitional game model, we carry out proof which shows that the proposed heuristic algorithm converges to a stable coalition structure. Simulation-based results show the effectiveness of the proposed scheme in terms of average detection accuracy, utility, and energy overhead compared to conventional schemes.

A Lightweight Secure Throughput Optimization Scheme in Cognitive Radio Networks

A Lightweight Secure Throughput Optimization Scheme in Cognitive Radio Networks

Research on User Pairing Techniques Based on NOMA in Cognitive Radio Networks

This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the traditional far-near pairing algorithm, and the low transmission rate of the traditional Orthogonal Multiple Access (OMA) transmission, a joint pairing algorithm was proposed, which provided multiple pairing schemes according to the actual scene. Firstly, the secondary users were sorted according to their channel gain, and then different secondary user groups were divided, and the far-near pairing combined with (Uniform Channel Gain Difference (UCGD) algorithm was used to group the secondary users. After completing the user pairing, the power allocation problem was solved. Finally, the simulation data results showed that the proposed algorithm can effectively improve the system transmission rate.

Broadcasting in Cognitive Radio Networks: A Fountain Codes Approach

The present paper addresses the performance of the broadcasting scheme in cognitive radio networks (CRNs) under a fountain codes (FC) approach. Particularly, closed-form expressions are derived for the cumulative distribution function (CDF) and the expectation of the number of FC clock cycles required for broadcasting packets to all secondary receivers. The energy efficiency (EE) of the secondary networks (SN) is also provided. Moreover, a simple transmit power scheme is proposed to enhance the performance of the SN and guarantee the quality-of-service (QoS) of the primary network (PN). The trends of the introduced closed-form performance metrics are then examined versus important network parameters allowing for the optimization of those parameters. Finally, numerical results are provided to confirm the accuracy of the derived mathematical framework and the superior performance of the introduced FC scheme over uncoded broadcasting protocols.

Rate Splitting Multiple Access Scheme for Cognitive Radio Network

Rate Splitting Multiple Access Scheme for Cognitive Radio Network

Comparison of a Probabilistic Returning Scheme for Preemptive and Non-Preemptive Schemes in Cognitive Radio Networks with Two Classes of Secondary Users

Comparison of a Probabilistic Returning Scheme for Preemptive and Non-Preemptive Schemes in Cognitive Radio Networks with Two Classes of Secondary Users

Performance analysis of the cooperative uplink-downlink NOMA and OMA scheme in cognitive radio network with max-min relay selection strategy

In this paper, we study the application of the non orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) scheme to cooperative cognitive radio network. We investigate a two phase cooperative NOMA where a secondary transmitter can transmit simultaneously with a primary transmitter via the uplink NOMA. We assign a larger power factor to the primary user (PU) to satisfy the quality of service (QoS) of the PU in overlay cognitive radio network. We purpose the cooperative NOMA scheme in which the one relay is selected between K relays, based on max–min relay selection strategy, to improve the performance of the PU and the secondary users (SUs). We investigate the outage probabilities of PU and the SUs with residual interference due to the imperfect successive interference cancelation (SIC). Then, the outage probabilities and diversity orders with perfect SIC for fixed power allocation and cognitive radio power allocation are derived in the closed form. We also calculate the outage probability and diversity order for the OMA scheme, as a benchmark. Finally, the simulation results are presented to confirm the accuracy of the theoretical results.

Hybrid Common Control Channel Based MAC Protocol with Proactive Handoff Scheme in Cognitive Radio Network

Hybrid Common Control Channel Based MAC Protocol with Proactive Handoff Scheme in Cognitive Radio Network

A Novel Weighted Cluster Based Co-operative Spectrum Sensing Scheme for Cognitive Radio Network

Background: Cognitive radio can be described as a radio system where it familiarizes to the situations of the environs by some procedure like analyzing, observing and learning. Cognitive radio can basically recycle the unused white space in the license spectrum through sensing the network thus the method can achieve the maximum implementation of the radio bandwidth. Objective: The motivation of this research is to improve the performance of spectrum sensing of a group of users in every cluster where various channel environment will be presented in comparison with the conventional weighted sensing. Methods: With the intention of lessening the fading and shadowing, co-operative detection is favored over independent detection. Clustered based cooperation has been employed to expand the sensing enactment moderately. Sensing of co-operative spectrum which is weighted has been used to boost the cluster cooperation scheme. To crack the critical problem this research proposed a weighted cluster based co-operative sensing in which the weight calculation is performed at FC reducing all available redundancies. Results: From the simulation it is found that our proposed algorithm has better probability of detection (i.e, at -6 dB of SNR, clustered, Weighted Clustered and Novel Weighted Clustered probability of detections are 67%,84% and 95% respectively). Even if Novel Weighted Clustered has the lower False Alarm probability. Conclusion: Proposed novel weighted co-operative spectrum sensing algorithm for cognitive radio network spectrum sensing scheme can attain better performance under different fading environments.

A novel fast and fair asynchronous channel hopping rendezvous scheme in cognitive radio networks for internet of things

Recent years have witnessed significant growth in the area of Internet of things (IoT) and is further expected to increase manifolds in the foreseeable future. Such a massive usage of IoT comes with spectrum scarcity issues. In the last few years, Cognitive Radio Network (CRN) has been widely researched because of its potential to be an effective solution to the problem of spectrum scarcity. The unlicensed users in CRN need to rendezvous on a commonly available channel for the purpose of necessary information exchange. Channel hopping (CH) is one of the representative technique to achieve rendezvous in CRNs in which users hop among available channels according to a pre-defined sequence. Providing guaranteed rendezvous which is fair and having full rendezvous diversity in minimum possible time is a challenging issue in CRN. In this paper, we propose an asymmetric asynchronous CH algorithm that provides guaranteed, fair and full rendezvous diversity among the users. The idea is to construct sender and receiver matrices to generate CH sequences based on the number of available channels of sender and receiver. Analytical and simulation results verify that the proposed algorithm outperform some existing state of the art rendezvous algorithms in terms of maximum time to rendezvous (MTTR), provide full rendezvous diversity and rendezvous fairness among the users.

Energy‐efficient reporting scheme for cognitive radio networks

Cooperative spectrum sensing in cognitive radio network consumes a large amount of energy during spectrum sensing and reporting. An energy-efficient reporting scheme called the reduced energy consumption scheme for reporting has been proposed to reduce energy consumption. In this scheme, all secondary users will sense the channel and make a local decision about the spectrum. All these local decisions are forwarded to a common node known as the fusion centre. This counts the presence or absence of the primary user based on the secondary user's local decisions. Whenever the counters count is greater than or equal to the threshold then the fusion centre sends a stop reporting feedback signal to the secondary users. In this way the energy consumption is reduced by diminishing the reporting secondary users and the energy efficiency is improved. The simulation and numerical results show a notable improvement in the energy efficiency of a reduced spectrum sensing scheme compared to the conventional spectrum sensing method.

Uplink NOMA-based long-term throughput maximization scheme for cognitive radio networks: an actor–critic reinforcement learning approach

Non-orthogonal multiple access (NOMA) is one of the promising techniques for spectrum efficiency in wireless networks. In this paper, we consider an uplink NOMA cognitive system, where the secondary users (SUs) can jointly transmit data to the cognitive base station (CBS) over the same spectrum resources. Thereafter, successive interference cancellation is applied at the CBS to retrieve signals transmitted by the SUs. In addition, the energy-constrained problem in wireless networks is taken into account. Therefore, we assume that the SUs are powered by a wireless energy harvester to prolong their operations; meanwhile, the CBS is equipped with a traditional electrical supply. Herein, we propose an actor–critic reinforcement learning approach to maximize the long-term throughput of the cognitive network. In particular, by interacting and learning directly from the environment over several time slots, the CBS can optimally assign the amount of transmission energy for each SU according to the remaining energy of the SUs and the availability of the primary channel. As a consequence, the simulation results verify that the proposed scheme outperforms other conventional approaches (such as Myopic NOMA and OMA), so the system reward is always maximized in the current time slot, in terms of overall throughput and energy efficiency.

Spectrum allocation strategy with a probabilistic preemption scheme in cognitive radio networks: analysis and optimization

In this paper, we propose a probabilistic preemption scheme in cognitive radio networks that will simultaneously ensure the primary user (PU) packets’ Quality of Service (QoS) and the secondary user (SU) packets’ transmission continuity. This scheme differs from a complete preemption scheme or a complete non-preemption scheme in conventional cognitive radio networks in that a PU packet can interrupt an SU packet’s transmission and preempt the channel with a certain probability that is termed the preemptive probability. In order to decrease the possible negative influence of SU packets on PU packets’ QoS, we introduce an access threshold, i.e. a limit on the size of the SU packet buffer, which controls the access of the SU packets. As part of the mathematical analysis of the probabilistic preemption scheme, we establish a discrete-time priority queueing model and then characterize it by a two-dimensional Markov chain. Based on the steady-state solution of the system we give formulas for several performance measures of the network users. We also provide numerical results to highlight the influence of the preemptive probability and the access threshold on the system performance. Moreover, we also compare the system performance of the proposed probabilistic preemption scheme with the preemptive and non-preemptive schemes by using numerical results. Finally, we build an optimization framework by the help of properly chosen net benefit function to optimize the preemptive probability and the access threshold jointly.

Improved Channel Allocation Scheme for Cognitive Radio Networks

In recent years, wireless channel optimization technologies witnessed tremendous improvements. In this regard, research for developing wireless spectrum for accommodating a wider range of wireless devices increased. This also... | Find, read and cite all the research you need on Tech Science Press

Compressive spectrum sensing using two-stage scheme for cognitive radio networks

The modern applications of communications that use wideband signals suffer the lacking since the resources of this kind of signals are limited especially for fifth generation (5G). The Compressive Spectrum Sensing (COMPSS) techniques address such issues to reuse the detected signals in the networks and applications of 5G. However, the raw techniques of COMPSS have low compression ratio and high computational complexity rather than high level of noise variance. In this paper, a hybrid COMPSS scheme has been developed for both non-cooperative and cooperative cognitive radio networks. The proposed scheme compiles on discrete wavelet transform – single resolution (DWT-SR) cascaded with discrete cosine transform (DCT). The first is constructed according to the pyramid algorithm to achieve 50% while the second performed 30% compression ratios. The simulation and analytic results reveal the significant detection performance of the proposed technique is better than that of the raw COMPSS techniques.

An Energy-Efficient Unselfish Spectrum Leasing Scheme for Cognitive Radio Networks.

Cooperative Communications in Cognitive Radio (CR) have been introduced as an essential and efficient technique to improve the transmission performance of primary users and offer transmission opportunities for secondary users. In a typical multiuser Cooperative Communication in CR, each primary user can choose one secondary user as a relay node. To encourage the cooperative behavior of the secondary users, primary users lease a fraction of their allocated spectrum to the relay secondary users to transmit their data packets. In this work, a novel unselfish spectrum leasing scheme in CR networks is proposed that offers an energy-efficient solution minimizing the environmental impact of our network. A network management architecture is introduced, and resource allocation is proposed as a constrained sum energy efficiency maximization problem. The optimization problem is formulated and solved using non-linear programming methods and based on a modified Kuhn-Munkres bipartite matching algorithm. System simulations demonstrate an increment in the energy efficiency of the primary users’ network compared with previously proposed algorithms.

Outage Analysis of Relay-Assisted NOMA in Cooperative Cognitive Radio Networks with SWIPT

In this paper, we investigate a relay-assisted cooperative spectrum sharing for the considered non-orthogonal multiple access (NOMA) scheme in cognitive radio networks, where the relay node assists the base station (BS) to transmit the superimposed composite signal to two receivers by utilizing an amplified-and-forward (AF) technique with simultaneous wireless information and power transfer (SWIPT). The exact expressions for outage probabilities of two receivers are derived in closed forms. Moreover, a joint optimization of power allocation and the proportion of information splitting for energy harvesting is proposed in terms of energy efficiency (EE) maximization under required data reliability. Simulation results validate the analytical results since the analytical results match well with simulation results and demonstrate the performance advantages of the proposed scheme over other schemes and direct transmission.

Energy Efficiency Analysis of Collaborative Compressive Sensing Scheme in Cognitive Radio Networks

In this paper, we investigate the energy efficiency of conventional collaborative compressive sensing (CCCS) scheme, focusing on balancing the tradeoff between energy efficiency and detection accuracy in cognitive radio environment. In particular, we derive the achievable throughput, energy consumption and energy efficiency of the CCCS scheme, and then formulate an optimization problem to determine the optimal values of parameters which maximize the energy efficiency of the CCCS scheme. The maximization of energy efficiency is proposed as a multi-variable, non-convex optimization problem, and we provide approximations to reduce it to a convex optimization problem. We highlight that errors due to these approximations are negligible. Subsequently, we analytically characterize the tradeoff between dimensionality reduction and collaborative sensing performance of the CCCS scheme, i.e., the implicit tradeoff between energy saving and detection accuracy. It is shown that the resulting loss due to compression can be recovered through collaboration, which improves the overall energy efficiency of the system.

A Practical Spectrum Sharing Scheme for Cognitive Radio Networks: Design and Experiments

Spectrum shortage is a fundamental problem in wireless networks and this problem becomes increasingly acute with the rapid proliferation of wireless devices. To address this problem, spectrum sharing in the context of cognitive radio networks (CRNs) has been considered a promising solution. In this paper, we propose a practical spectrum sharing scheme for a small CRN that comprises a pair of primary users and a pair of secondary users by leveraging the multiple-input and multiple-output (MIMO) technology. In our scheme, we assume that the secondary users take full responsibility for cross-network interference cancellation (IC). We also assume that the secondary users have no knowledge about the primary network, including its signal waveform, frame structure, and network protocol. The key components of our proposed scheme are two MIMO-based interference management techniques: blind beamforming (BBF) and blind interference cancellation (BIC). We have built a prototype of our scheme on a wireless testbed and demonstrated that the prototyped secondary network can coexist with commercial Wi-Fi devices (primary users). Experimental results further show that, for a secondary device with two or three antennas, BBF and BIC achieve an average of 25dB and 33dB IC capability in an office environment, respectively.