Behavior Of Secondary Users Research Articles

Order statistics and recursive updating with aging factor for cooperative cognitive radio networks under SSDF attacks

Abstract For detecting the presence of the primary user under malicious attacks in cooperative cognitive radio networks, we propose a detection scheme based on the order statistics and recursive updating algorithm with aging factor. The aging factor not only makes the detector sensitive to the change in the behavior of secondary users but also allows reduction in the storage space. The order statistics help select secondary users with higher degree of reputation for cooperation, and consequently, reduce the influence of malicious users. Computer simulations show the proposed scheme can defend the network against malicious attacks more effectively than the conventional scheme.

Discrete-Time Analysis of Cognitive Radio Networks with Nonsaturated Source of Secondary Users

Sensing is a fundamental aspect in cognitive radio networks and one of the most complex issues. In the design of sensing strategies, a number of tradeoffs arise between throughput, interference to primary users, and energy consumption. This paper provides several Markovian models that enable the analysis and evaluation of sensing strategies under a broad range of conditions. The occupation of a channel by primary users is modeled as alternating idle and busy intervals, which are represented by a Markov phase renewal process. The behavior of secondary users is represented mainly through the duration of transmissions, sensing periods, and idle intervals between consecutive sensing periods. These durations are modeled by phase-type distributions, which endow the model with a high degree of generality. Unlike our previous work, here the source of secondary users is nonsaturated, which is a more practical assumption. The arrival of secondary users is modeled by the versatile Markovian arrival process, and models for both finite and infinite queues are built. Furthermore, the proposed models also incorporate a quite general representation of the resumption policy of an SU transmission after being interrupted by PUs activity. A comprehensive analysis of the proposed models is carried out to derive several key performance indicators in cognitive radio networks. Finally, some numerical results are presented to show that, despite the generality and versatility of the proposed models, their numerical evaluation is perfectly feasible.

A Dynamic Spectrum Allocation Algorithm for a Maritime Cognitive Radio Communication System Based on a Queuing Model

With the rapid development of maritime digital communication, the demand for spectrum resources is increasing, and building a maritime cognitive radio communication system is an effective solution. In this paper, the problem of how to effectively allocate the spectrum for secondary users (SUs) with different priorities in a maritime cognitive radio communication system is studied. According to the characteristics of a maritime cognitive radio and existing research about cognitive radio systems, this paper establishes a centralized maritime cognitive radio communication model and creates a simplified queuing model with two queues for the communication model. In the view of the behaviors of SUs and primary users (PUs), we propose a dynamic spectrum allocation (DSA) algorithm based on the system status, and analyze it with a two-dimensional Markov chain. Simulation results show that, when different types of SUs have similar arrival rates, the algorithm can vary the priority factor according to the change of users’ status in the system, so as to adjust the channel allocation, decreasing system congestion. The improvement of the algorithm is about 7–26%, and the specific improvement is negatively correlated with the SU arrival rate.

Faithworthy Collaborative Spectrum Sensing Based on Credibility and Evidence Theory for Cognitive Radio Networks

Cognitive radio (CR) has become a tempting technology that achieves significant improvement in spectrum utilization. To resolve the hidden terminal problem, collaborative spectrum sensing (CSS), which profits from spatial diversity, has been studied intensively in recent years. As CSS is vulnerable to the attacks launched by malicious secondary users (SUs), certain CSS security schemes based on the Dempster–Shafer theory of evidence have been proposed. Nevertheless, the available works only focus on the real-time difference of SUs, like the difference in similarity degree or SNR, to evaluate the credibility of each SU. Since the real-time difference is unilateral and sometimes inexact, the statistical information comprised in SUs’ historical behaviors should not be ignored. In this paper, we propose a robust CSS method based on evidence theory and credibility calculation. It is executed in four consecutive procedures, which are basic probability assignment (BPA), holistic credibility calculation, option and amelioration of BPA and evidence combination via the Dempster–Shafer rule, respectively. Our scheme evaluates the holistic credibility of SUs from both the real-time difference and statistical sensing behavior of SUs. Moreover, considering that the transmitted data increase with the number of SUs increasing, we introduce the projection approximation approach to adjust the evidence theory to the binary hypothesis test in CSS; on this account, both the data volume to be transmitted and the workload at the data fusion center have been reduced. Malicious SUs can be distinguished from genuine ones based on their historical sensing behaviors, and SUs’ real-time difference can be reserved to acquire a superior current performance. Abounding simulation results have proven that the proposed method outperforms the existing ones under the effect of different attack modes and different numbers of malicious SUs.

An Efficient Spectrum Sensing Framework and Attack Detection in Cognitive Radio Networks using Hybrid ANFIS

Background: Cognitive radio is being recognized as an intelligent technology due to its ability to rapidly and autonomously adapt operating parameters to changing environments and conditions. In order to reliably and swiftly detect spectrum holes in cognitive radios, spectrum sensing must be used. Accurate spectrum sensing is important in improving the efficiency of cognitive radio networks. False sensing results in either waste of spectrum or harmful interference to primary users who may remotely or physically capture the sensors and manipulate the sensing reports. Methods: A novel framework and an innovative approach have been introduced to eliminate the malicious behaviors of secondary users. It is found that spectrum sensing alone cannot prevent the malicious behavior without any information on users’ reputation. Based on the evaluation of malicious behavior resistance methods, joint spectrum sensing and malicious nodes detection approach for optimal prevention from sensing falsification is being proposed. Findings: The proposed approach minimizes Linear Minimum Mean-Square Errors (LMMSEs) when it is compared with the existing algorithms such spectrum sensing based on HSMM and FNN based spectrum sensing are plotted versus detection probability, false alarm probability. With more malicious nodes proposed schemes are more effective to restrain the false alarms. Improvement/Application: The proposed spectrum sensesframework with attack detection which is very effective to determine the malicious users in spectrum holes.

Game-theoretic analysis of selfish secondary users in cognitive radio networks

In this paper, we study the problem of selfish behavior of secondary users (SUs) based on cognitive radio (CR) with the presence of primary users (PUs). SUs are assumed to contend on a channel using the carrier sense multiple access with collision avoidance (CSMA/CA) and PUs do not consider transmission of SUs, where CSMA/CA protocols rely on the random deference of packets. SUs are vulnerable to selfish attacks by which selfish users could pick short random deference to obtain a larger share of the available bandwidth at the expense of other SUs. In this paper, game theory is used to study the systematic cheating of SUs in the presence of PUs in multichannel CR networks. We study two cases: A single cheater and multiple cheaters acting without any restraint. We identify the Pareto-optimal point of operation of a network with multiple cheaters and also derive the Nash equilibrium of the network. We use cooperative game theory to drive the Pareto optimality of selfish SUs without interfering with the activity of PUs. We show the influence of the activity of PUs in the equilibrium of the whole network.

Spectrum handoff model based on preemptive queuing theory in cognitive radio networks

Cognitive radio can significantly improve spectrum efficiency by temporarily sharing under-utilized licensed frequency with primary users. Its spectrum management framework consists of four parts: spectrum sensing, spectrum decision, spectrum sharing and spectrum handoff. The last part is what we focus on in this paper. Spectrum handoff, which aims at guaranteeing requirement for service of secondary users and shortening time delay produced by interruption from primary users, is an important functionality of cognitive radio networks. For solving the problem of optimizing the extended data delivery time, a spectrum handoff model is proposed based on the preemptive resume priority M/G/m queuing theory. In order to minimize the extended data delivery time, the queuing method with mixed queuing and parallel service is adopted. In this model, each channel has its own high-priority queue and there is only one low-priority queue for all secondary users. The primary and secondary users respectively enter into the high-priority and low-priority queue to establish corresponding primary connections and secondary connections and execute corresponding data transmission. On the above basis, secondary users’ channel usage behaviors are thoroughly analyzed in the cases of multiple secondary users, multiple licensed channels and multiple spectrum handoffs. In this process, when multiple interruptions occur, the secondary user will stay on the current channel and suspend data transmission until primary users finish their data transmission, otherwise the secondary user will switch from the current channel to the predetermined target channel to resume his unfinished data transmission. The target channel is sequentially obtained from the target channel sequence, which is determined by channel parameter estimation algorithm. Based on the analysis of channel usage behaviors for secondary users, the total time delay caused by spectrum handoffs within the whole data transmission process is derived first. The total time delay can be deduced from two scenarios. One is that the target channel is the current channel. For this reason, the total time delay equals transmission time of primary users in high-priority queue. Obviously, the other is that the target channel is not the current channel. Thus, the total time delay equals the sum of transmission times of primary users in high-priority and secondary users ahead in low-priority. In addition, appearance of new primary users should also be considered in the data transmission process. Then, expressions of the extended data delivery time in two different cases (i. e. always-staying strategy and always-changing strategy) are respectively derived. Furthermore, the adaptive spectrum handoff strategy is finally discussed, which is to choose the optimal scheme from always-staying and always-changing strategy when a spectrum handoff happens. Simulation results verify that this model can not only describe handoff behaviors of secondary users more perfectly, but also can make the transmission time delay smaller and make the extended data delivery time shorter than the existing spectrum handoff model. Especially, with the increase of service intensity of primary users, the advantages of the proposed spectrum handoff model are more outstanding. In addition, the allowable secondary user service intensity is improved and the receptive number of secondary user is increased in cognitive radio networks. All in all, the proposed spectrum handoff model improves the performance of spectrum handoff, increases the capacity of cognitive radio networks and optimally realizes spectrum sharing between secondary users and primary users.