Number Of Cognitive Radio Users Research Articles

Wireless Communication Network Security System Based on Big Data Information Transmission Technology

This paper establishes a unified perception information transmission model for the difference in the number of cognitive radio users in wireless communication network systems. The model can effectively improve the utilization of spectrum resources. At the same time, this paper introduces a cyclic delay full diversity sensing information coding transmission scheme for the security risks of wireless communication networks. We established a system simulation model to compare performance under different correlation coefficients. The study found that the total interference intensity in the cyclic delay diversity system is lower than that of the frequency division duplex and time division duplex. Its antijamming attack capability also becomes stronger accordingly.

Bilişsel Radyolarda Beklenti Maksimizasyonu ile Gauss Karışım Modelleri Kestirimi

Nowadays, it is known that there is a constantly increasing demand for the radio frequency spectrum. The biggest reason for this situation is the constantly increasing data sizes in wireless communication systems. Therefore, Cognitive Radio (BR) systems are potential technologies that can be a solution to future spectrum shortage problems. In the BR systems, the probability distribution function of the signal to be detected is utilized at the basis of spectrum detection. The probability distribution functions of the signals perceived by BR users according to their spatial location, which will perform spectrum detection in wireless communication systems, vary. The purpose of this study is to predict the common Gaussian mix model of signals perceived by different BR users using the expectation maximization algorithm. In the study, simulation results were performed according to different noise levels and different number of cognitive radio users in terms of spatial differences of different BR users. Thus, the estimated Gaussian mix models can be used to predict different spectrum sensing models.

Optimized cooperative spectrum sensing network analysis in nonfading and fading environments

SummaryThe proposed cooperative spectrum sensing (CSS) network is equipped with multiple antennas and an improved energy detector (IED) scheme at each cognitive radio (CR). Each CR in the network receives the information about the primary user (PU) in the form of binary decisions at multiple antennas. Diversity technique called selection combining (SC) scheme is used at multiple antennas to select the maximum value of sensing information present at multiple antennas. Finally, sensing information will be passed to the fusion center (FC) through reporting channel, and the final decision about PU is made at FC using fusion rules. Initially, we have derived the novel missed detection probability expressions for AWGN channel, Rayleigh, and Rician fading environments. Later, the closed form of optimized expressions for proposed CSS network parameters are derived to achieve an optimal performance. The closed form of optimized expressions such as number of CR users (Nopt), normalize threshold value (λn,opt), and an arbitrary power of the received signal (popt) are derived under various fading environments. The performance is evaluated using complementary receiver operating characteristics (CROC) and total error rate curves. The MATLAB‐based simulations are evaluated with the strong support of theoretical expressions. Finally, various simulation parameters such as sensing channel SNR, the error rate in reporting channel, threshold value, and number of antennas at each CR are considered in the simulation to show the effect on the performance of proposed CSS network.

Optimised fusion rule in cluster-based energy-efficient CSS for cognitive radio networks

ABSTRACTCooperative spectrum sensing (CSS) can solve the problem of the hidden terminal in cognitive radio (CR). Energy consumption and sensing time are high in CSS due to a large number of users. In CSS, the parameters that affect the energy efficiency (EE) of the system are fusion rule, sensing time, transmission power and number of users. In this paper, four fusion rules OR-OR, AND-OR, OR-AND and AND-AND are proposed for cluster-based CSS and optimum fusion rule is determined. It is found that in terms of EE metric, AND-OR rule outperforms the other fusion rules. An iterative algorithm has been proposed which finds the optimum number of CR users in a cluster and total number of clusters that maximises the EE. Quantitatively at SNR = −20 dB, EE is maximum when number of clusters equals to 4 and number of users in the cluster equals to 3 for 12 fixed number of users. The maximum EE is 3.69 Mbits/Hz/joule at sensing time 1.5 ms.

Spectrum Mapping in Large-Scale Cognitive Radio Networks With Historical Spectrum Decision Results Learning

To mitigate the contradiction between scarcity spectrum resources and heavily wireless services, cognitive radio (CR) has been proposed to improve spectrum utilization through allowing CR users to access licensed channels opportunistically. In large-scale networks, spectrum status is not the same at different locations due to the heterogeneity of CR network (CRN). To cope with such heterogeneity, some noncooperative spectrum sensing and distributed cooperative sensing algorithms were proposed. Such spectrum decision results will be exploited in this paper, in order to draw the spectrum map of the entire large-scale CRN. The proposed spectrum mapping scheme contains three processing steps, and a boundary CR users searching algorithm using kennel function based supportive vector machine is adopted to improve the performance of the proposed scheme. The simulation results show that radial basis function kennel performs the best in the proposed scheme, and when accuracy threshold ${\theta _{a}} = 0.95$ and filtration threshold ${\theta _{f}} = 0.02$ , the proposed scheme can draw a spectrum map with the accuracy 99.3% using only about 28% CR users performing spectrum sensing. Furthermore, the number of CR users and energy detection threshold have little effects on the performance of the proposed scheme.

Performance evaluation of distributed CSS with clustering of secondary users over fading channels

ABSTRACTSpectrum sensing is the important aspect of cognitive radio (CR). A non-cooperative spectrum sensing faces the problem of shadowing and hidden terminal due to which the CR user fails to monitor the vacant spectrum. To solve the problem of hidden terminal and shadowing in non-cooperative spectrum sensing, cooperative spectrum sensing (CSS) is used. CSS can be divided into two categories, centralised and distributed. In this paper, a distributed CSS is proposed with clustering of secondary users for different fading channel with four fusion rules and effect of number of CR users and number of clusters on the performance has been investigated. It is investigated that if number of users and number of cluster increases, user cooperation increases and chances of detection of empty spectrum increases. For false alarm probability 0.001, detection probability increases by 25% when total number of CR users increases from 4 to 9 and it increases to 32% when total number of CR users increases from 4 to 16.

A Lightweight Spectrum Occupancy and Service Time Model for Centralized Cognitive Radio Networks

In cognitive radio networks (CRNs), secondary users (SUs) exploit the unused or sparsely used spectrum by primary users (PUs) without causing any harmful interference. Consequently, spectrum occupancy modeling appears as an essential task for CRN operations. In this paper, spectrum occupancy has been modeled using a queueing theory based approach in order to analyze the performance of CRNs in terms of network capacity, number of cognitive radio users waiting for service, and average waiting time. A compact model is presented for a CRN, where the queue adopted has variable service capacity and can be considered as a multi-service queue with server failure where each channel acts as a server. When a channel is occupied by a PU, it is regarded as a server failure for SUs. Using the probability generating function, the closed-form expressions of various performance parameters for different arrival distributions are derived. Numerical results for the remaining services for SUs, the expected number of SUs, and average waiting time as the CRN capacity, average service demands and average arrival rate vary, are illustrated.

Designing an Optimal Energy Efficient Cluster-Based Spectrum Sensing for Cognitive Radio Networks

An approach for joint optimal design system parameters is considered for energy efficient cluster-based spectrum sensing in cognitive radio (CR) networks. The design problem is formulated and subjected to primary user protection constraints and spectrum utilization requirements. An iterative algorithm with low computational complexity is proposed to determine joint optimal sensing time, data transmission time, and the number of CR users that maximize energy efficiency of the system. The design criterion combines two design parameters, namely, sensing time and data transmission time, into one parameter in order to reduce the complexity. The key idea of the proposed algorithm is to employ the impact of transmission power variation on both the optimal sensing time and the corresponding probability of false alarm. The performance of the proposed algorithm is presented and evaluated through simulation results.

A Cluster-Based Cooperative Spectrum Sensing in Cognitive Radio Network Using Eigenvalue Detection Technique with Superposition Approach

Cognitive radio (CR) networks have been active area of research because of its ability to opportunistically share the spectrum. A cluster-based cooperative spectrum sensing (CCSS) has a tremendous impact on sensing reliability compared with cooperative spectrum sensing. The energy detection (ED) technique requires perfect knowledge of noise power. An eigenvalue-based spectrum sensing has mitigated the noise uncertainty problem. Sensing and reporting time slots are rigidly separated in the conventional ED and eigenvalue-based detection (EVD) schemes. In CCSS, more reporting time slots are required as the number of CR users (CRUs) increases. If the reporting time slots of other CRUs as sensing time slots with a superposition allocation, the more reliable channel sensing can be achieved. In this paper, we propose CCSS using EVD technique with a superposition approach scheme where the reporting time slot is properly utilized to sense the primary user's (PU's) signal more accurately by rescheduling the reporting time slot for CRUs and cluster heads (CHs). Simulation result shows that the proposed EVD scheme has better detection probability than the conventional CCSS using both ED and EVD techniques.

Performance Analysis of Hybrid Fusion in Cognitive Radio Networks

Spectrum sensing is a crucial issue in cognitive radio networks for primary user detection. Cooperative sensing based on energy detection in the cognitive radio network with multiple antennas base-station is considered in this letter. To improve the sensing performance, we investigate hybrid fusion of the observed energies from the base-station and decisions (1bit, hard information) from different cognitive radio (CR) users around the base-station. Further, we present an optimized scheme where the global detection probability can be maximized according to the Neyman-Pearson criterion. Finally the impact of the change of parameters (Signal to Noise Ratio and number of CR users) in the optimized scheme is analyzed. Numerical simulations and extensive analysis confirm that hybrid fusion base on the optimized scheme is a good choice, also, Signal to Noise Ratio (SNR) and number of CR users does not have influence on the optimized scheme

Cooperative Spectrum Sensing Based on Two-Stage Detectors With Multiple Energy Detectors and Adaptive Double Threshold in Cognitive Radio Networks

This paper presents two-stage detectors for spectrum sensing in cognitive radio networks. The first stage consists of multiple energy detectors, where each energy detector (ED) has a single antenna with fixed threshold for making a local binary decision. If required, the second stage comprised of ED with adaptive double threshold is invoked. The detection performance of the proposed scheme is compared with a cyclostationary-based sensing method and adaptive spectrum sensing scheme. The numerical results show that the proposed scheme improves detection performance and outperforms the cyclostationary-based sensing method and adaptive spectrum sensing by 12.3% and 14.4% at signal-to-noise ratio (SNR) setting of as low as -8 dB, respectively. Performance was also measured in terms of sensing time and scheme has smaller sensing time than cyclostationary detection and adaptive spectrum sensing scheme in the order of 4.3 and 0.1 ms at -20-dB SNR, respectively. Furthermore, the scheme was analyzed in conjunction with cooperative spectrum sensing (CSS), where each cognitive radio (CR) user used two-stage spectrum sensing detectors for local detection and sent detection decisions to the fusion center to give the final decision based on hard decision OR rule. It is further found that the proposed two-stage spectrum sensing scheme with CSS achieves spectrum detection performance in the order of 0.9 for an SNR value of as low as -19 dB as the number of CR users (K) is 10.

Study the One-bit Hard Combination Scheme on Cognitive Radio Users

This paper describes the performance of one- bit hard combination scheme of cooperative spectrum sensing for different number of cognitive radio users. We evaluate cooperative spectrum sensing by simulating OR rule as a hard combination data fusion rule. Energy detector is used to observe the presence of primary user (PU) signal. It improves the probability of detection by collaborating to detect PUs signal in cognitive radio (CR) system. Simulation result shows that the probability of missed detection is decreasing for both conventional hard combination and 1-bit hard combination scheme with OR rule correspondingly with increasing the probability of false alarm. It is shown that 1-bit scheme has much better performance than the conventional hard combination scheme. This is also shown that the probability of missed detection is decreased even though CR user is increased. Here missed detection probability is decreased when the number of user increases.

A Novel Cooperative Spectrum Sharing Algorithm Based on Optimal Cognitive Radio User Selection

In this paper, we consider the problem of cognitive radio (CR) user selection to maximize overall CR network (CRN) throughput when the available spectrum bandwidth is less than the demand by all CR users. We formulate optimal CR user selection problem. Then, based on approximation of the average received signal to interference plus noise ratio (SINR) and adaptive modulation and coding (AMC), we estimate the required bandwidth of CR users with different required quality of services (QoSs). Using the principle of optimality, we propose a novel cooperative spectrum sharing algorithm for a CRN. The proposed algorithm not only achieves exhaustive search performance but also its complexity is in the order of N × M versus 2N for exhaustive search, where N is the number of CR users, and M is the spectrum pool size. Extensive simulation results illustrate that the proposed algorithm significantly outperforms the existing algorithms that ignore optimal CR user selection. Also, these results illustrate a better fairness criterion than those of previous works.

Throughput Maximization in Cooperation Based Symbiotic Cognitive Radio Networks

In the symbiotic cognitive radio (CR) networks, the CR users (CUs) may assist the primary transmission in a cooperation time, and obtain an incentive time for their own data transmission. In this letter, we study the throughput maximization problem in the symbiotic CR networks. Under the symbiosis and transmit power constraints, we aim to find the optimal cooperation time to assist the primary transmission and power allocations among the CUs. Given the cooperation time, the optimal power allocations can be solved by multi-level water-filling (MWF) with individual volume limits. A theoretical analysis is presented on the cooperation time and a modified bisection algorithm with low complexity is proposed to find the sub-optimal cooperation time. Simulation results show that the spectrum usage efficiency can be significantly improved as the number of CUs increases.

Opportunistic spectrum sharing in cognitive MIMO wireless networks

Cognitive radio has been recently proposed as a promising technology to improve the spectrum utilization. In this paper, we consider the spectrum sharing between a large number of cognitive radio users and a licensed user in order to enhance the spectrum efficiency. With the deployment of M antennas at the cognitive base station, an opportunistic spectrum sharing approach is proposed to maximize the downlink throughput of the cognitive radio system and limit the interference to the primary user. In the proposed approach, cognitive users whose channels are nearly orthogonal to the primary user channel are pre-selected so as to minimize the interference to the primary user. Then, M best cognitive users, whose channels are mutually near orthogonal to each other, are scheduled from the preselected cognitive users. A lower bound of the proposed cognitive system capacity is derived. It is then shown that opportunistic spectrum sharing approach can be extended to the multiple input/ multiple-output (MIMO) case, where a receive antenna selection is utilized in order to further reduce the computational and feedback complexity. Simulation results show that our proposed approach is able to achieve a high sum-rate throughput, with affordable complexity, when considering either single or multiple antennas at the cognitive mobile terminals.