CoPD: a conjugate prior based detection scheme to countermeasure spectrum sensing data falsification attacks in cognitive radio networks

Cognitive radio networks are a promising solution to the spectrum scarcity issue. In cognitive radio networks, cooperative spectrum sensing is critical to accurately detect the existence of a primary user (PU) signal, because the local spectrum sensing by a single secondary user (SU) has low reliability. Unfortunately, cooperative spectrum sensing is vulnerable to the spectrum sensing data falsification (SSDF) attack. Specifically, a malicious user can send a falsified sensing report to mislead other (benign) SUs to make an incorrect decision on the PU activity, to cause either denial of service to benign SUs or harmful interference to PUs. Therefore, detecting the SSDF attack is extremely important for robust cooperative spectrum sensing. This paper proposes a distributed defense scheme, termed conjugate prior based SSDF detection (CoPD), to countermeasure the SSDF attack. CoPD can effectively exclude the malicious sensing reports from SSDF attackers, so that benign SUs can effectively detect the PU activity. Furthermore, CoPD can also exclude abnormal sensing reports from ill-functioned SUs. Simulation results indicate that CoPD achieves very good performance to accomplish robust cooperative spectrum sensing.     

A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters.     

基于稳定匹配的认知无线网络协作物理层安全机制

在Underlay认知无线网络中,次用户被允许在主用户进行数据发送时接入主用户的频谱.此时,主用户将对次用户和窃听者造成干扰.利用协作干扰技术,主用户产生的干扰可以被用来改善次用户的物理层安全.基于此,本文针对包含多个主次用户的Underlay认知无线网络,提出了一种新的协作物理层安全机制.为了在保证主用户通信质量的前提下,最大化网络中次用户的总的安全容量,该机制将对次用户进行合理的频谱接入选择和功率控制.另外,考虑到个体理性和自私性对于频谱接入稳定性的影响,该机制利用稳定匹配理论将频谱接入选择问题建模为一对一的双边匹配问题,通过构建主次用户之间的稳定匹配来保证频谱接入的稳定性.仿真结果表明,使用本文所提安全机制,可以在保证主用户通信质量的前提下,稳定而又有效地改善网络中次用户获得的总的安全容量.     

Spectrum leasing based on Nash Bargaining Solution in cognitive radio networks

Cognitive radio is becoming an emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum resource. In this paper, we focus on the dynamic spectrum access of cognitive radio networks, in which the primary user (PU) and secondary users (SUs) coexist. In property-rights model, the PU has property of the bandwidth and may decide to lease it to secondary network for a fraction of time in exchange for appropriate remuneration. We propose a cooperative communication-aware spectrum leasing framework, in which, PU selects SUs as cooperative relays to help transmit information, while the selected SUs have the right to decide their payment made for PU in order to obtain a proportional access time to the spectrum. Then, the spectrum leasing scheme is cast into a Nash Bargaining Problem, and the Nash Bargaining Solution (NBS) can be used to fairly and efficiently address the resource allocation between PU and secondary network, enhancing both the utility of PU and secondary network. Numerical results show that spectrum leasing based on NBS is an effective method to improve performance for cognitive radio networks.     

Optimal Energy Harvesting-based Weighed Cooperative Spectrum Sensing in Cognitive Radio Network

In cognitive radio (CR) network, to improve spectrum sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cooperative spectrum sensing, an energy harvesting-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal and then converts the RF energy into the electric energy to supply the power used for energy detection and cooperation. The time switching model and power splitting model are developed to realize the notion. In the time switching model, the SU performs either spectrum sensing or energy harvesting at any time, while in the power splitting model, the received PU signal is split into two signal streams, one for spectrum sensing and the other one for energy harvesting. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time, number of cooperative SUs and splitting factor. The simulation results have shown that compared to the traditional cooperative spectrum sensing, the proposed energy harvesting-based weighed cooperative spectrum sensing can decrease the energy wastage obviously while guaranteeing the maximum spectrum access probability.     

Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.

     

Optimal Transmission Strategies for Dynamic Spectrum Access in Cognitive Radio Networks

Cognitive radio offers a promising technology to mitigate spectrum shortage in wireless communications. It enables secondary users (SUs) to opportunistically access low-occupancy primary spectral bands as long as their negative effect on the primary user (PU) access is constrained. This PU protection requirement is particularly challenging for multiple SUs over a wide geographical area. In this paper, we study the fundamental performance limit on the throughput of cognitive radio networks under the PU packet collision constraint. With perfect sensing, we develop an optimum spectrum access strategy under generic PU traffic patterns. Without perfect sensing, we quantify the impact of missed detection and false alarm, and propose a modified threshold-based spectrum access strategy that achieves close-to-optimal performance. Moreover, we develop and evaluate a distributed access scheme that enables multiple SUs to collectively protect the PU while adapting to behavioral changes in PU usage patterns. Our results provide useful insight on the trade-off between the protection of the primary user and the throughput performance of cognitive radios.     

Cluster‐based coordination scheme for cooperative cognitive radio networks

In this paper, a cluster‐based two‐phase coordination scheme for cooperative cognitive radio networks is proposed considering both spectrum efficiency and network fairness. Specifically, candidate secondary users (SUs) are first selected by a partner selection algorithm to enter the two‐phase cooperation with primary users (PUs). In phase I, the selected SUs cooperate with PUs to acquire a fraction of time slot as a reward. In phase II, all SUs including the unselected ones share the available spectrum resources in local clusters; each of which is managed by a cluster head who participated in the cooperation in phase I. To improve the total network utility of both PUs and SUs, the maximum weighted bipartite matching is adopted in partner selection. To further improve the network performance and communication reliability, network coding is exploited during the spectrum sharing within the cluster. Simulation results demonstrate that, with the proposed cluster‐based coordination scheme, not only the PUs' transmission performance is improved, but also SUs achieve spectrum access opportunities. Copyright © 2015 John Wiley & Sons, Ltd.     

认知无线电网络中基于信誉度的分层合作频谱感知方案（英文）

Cooperative spectrum sensing in cognitive radio is investigated to improve the detection performance of Primary User(PU).Meanwhile,cluster-based hierarchical cooperation is introduced for reducing the overhead as well as maintaining a certain level of sensing performance.However,in existing hierarchically cooperative spectrum sensing algorithms,the robustness problem of the system is seldom considered.In this paper,we propose a reputation-based hierarchically cooperative spectrum sensing scheme in Cognitive Radio Networks(CRNs).Before spectrum sensing,clusters are grouped based on the location correlation coefficients of Secondary Users(SUs).In the proposed scheme,there are two levels of cooperation,the first one is perfonned within a cluster and the second one is carried out among clusters.With the reputation mechanism and modified MAJORITY rule in the second level cooperation,the proposed scheme can not only relieve the influence of the shadowing,but also eliminate the impact of the PU emulation attack on a relatively large scale.Simulation results show that,in the scenarios with deep-shadowing or multiple attacked SUs,our proposed scheme achieves a better tradeoff between the system robustness and the energy saving compared with those conventionally cooperative sensing schemes.     

A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. Copyright © 2013 John Wiley & Sons, Ltd.     

Cooperative spectrum sensing using amplify-and-forward relaying with partial relay selection in cognitive radio networks

Cooperative spectrum sensing has been shown to be an effective approach to improve the detection performance by exploiting the spatial diversity among multiple cognitive nodes. By using the amplify-and-forward relaying with partial relay selection, this paper proposes a novel cooperative spectrum sensing scheme, which provides higher detection performance and is interesting in distributed cognitive radio networks. In the proposed sensing scheme, the “best” cognitive relay by means of partial relay selection technique amplifies and forwards the signals transmitted from the primary user (PU) to the cognitive user (CU). Then the CU detects PU’s states (i.e., presence or absence) via an energy detector. Moreover, the average missed-detection probability of proposed sensing scheme is studied over Nakagami-m fading channels, where m is a positive integer. In particular, the tight closed-form lower bounds of the average missed-detection probability are presented for the convenience of performance evaluation in practice. Finally, numerical results are provided to validate the derived closed-form lower bounds and the influence of the number of cognitive relays on the detection performance is also discussed.     

A coalition formation game based relay selection scheme for cooperative cognitive radio networks

In a cognitive radio network, cooperative communications between a primary user (PU) and a second user (SU) may be able to significantly improve the spectrum utilization, and thus, the network performance. To be specific, the PU can select a number of SUs as its relays to cooperatively transmit its data. In turn, these relays can be granted access to the licensed channel of the PU to transmit their data. In this paper, an effective cooperation strategy for SUs is presented. We formulate the problem of cooperative relay selection as a coalition formation game, and develop a utility function based on the game. The utility function considers various factors such as transmission power and noise level. With the utility function, a distributed coalition formation algorithm is proposed, which can be used by SUs to decide whether to join or leave a coalition. Such a decision is based on whether it can increase the maximal coalition utility value. We rigorously prove that our proposed coalition formation algorithm can terminate and reach a stable state. Finally, this paper demonstrates that the proposed scheme is able to enhance the network throughput via a simulation study.     

Centralized spectrum leasing via cooperative SU assignment in cognitive radio networks

As the increasing demand of the radio spectrum, the researchers pay more attention to the technology of cognitive radio networks to improve the use of the scarce spectrum resources. Recently, cooperative communications combining with cognitive radio have been proposed in many literatures to improve the channel capacity. The primary users with poor transmission environment transmit their packets with the assistance of the secondary users (SUs) by offering them spectrum resources. This paper first raises issues in existing works, such as non‐optimal selection, selection collision, and transmission interruption. Aiming at these issues, we design a centralized system model and a cooperative relaying protocol for multiple primary user pairs to dynamically lease spectrum in exchange for the transmission assistance of SUs. Then we define 2 problems of the cooperative SU assignment to maximize total rate and maximize number of assigned SUs. We prove they are NP‐hard and propose a local search algorithm for the objective of maximize total rate and a ‐approximation algorithm for another objective. Our simulation results show that our system and algorithms can effectively improve the performance of the wireless networks.     

Coalitional game‐based behavior analysis for spectrum access in cognitive radios

The core of cognitive radio paradigm is to introduce cognitive devices able to opportunistically access the licensed radio bands. The coexistence of licensed and unlicensed users prescribes an effective spectrum hole‐detection and a non‐interfering sharing of those frequencies. Collaborative resource allocation and spectrum information exchange are required but often costly in terms of energy and delay. In this paper, each secondary user (SU) can achieve spectrum sensing and data transmission through a coalitional game‐based mechanism. SUs are called upon to report their sensing results to the elected coalition head, which properly decides on the channel state and the transmitter in each time slot according to a proposed algorithm. The goal of this paper is to provide a more holistic view on the spectrum and enhance the cognitive system performance through SUs behavior analysis. We formulate the problem as a coalitional game in partition form with non‐transferable utility, and we investigate on the impact of both coalition formation and the combining reports costs. We discuss the Nash Equilibrium solution for our coalitional game and propose a distributed strategic learning algorithm to illustrate a concrete case of coalition formation and the SUs competitive and cooperative behaviors inter‐coalitions and intra‐coalitions. We show through simulations that cognitive network performances, the energy consumption and transmission delay, improve evidently with the proposed scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Iterative optimization of detection threshold and throughput for secondary users in multiband cognitive radio systems

In cognitive radio(CR) systems,efficient spectrum sensing ensures the secondary user(SU) to successfully access the spectrum hole.Typically,the detection problem has been considered separately from the optimization of transmission strategy.However,in practice,due to non-zero probabilities of miss detection and false alarm,the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user(PU).In this paper,using energy detection,we maximize the total throughput of SUs by ...     

Delay QoS Guaranteed Cooperative Double-Threshold Sensing Scheme in Cognitive Radio Networks

In cognitive radio networks, cooperation can greatly improve the performance of spectrum sensing. This paper proposes a delay (QoS) quality-of-service guaranteed cooperative spectrum sensing frame structure in which secondary users (SUs) conduct spectrum sensing and data transmission concurrently over two different parts of the primary user spectrum band. A double-threshold sensing scheme is employed in the local sensing step, only the SUs with reliable sensing information are allowed to transmit their “one bit” local decisions to the fusion center. The sensing performance and the SU transmission delay are analyzed in detail in this paper. Computer simulations show that the delay QoS guaranteed cooperative double-threshold sensing scheme could not only decrease the SU transmission delay but also save the reporting overhead of the SUs compared with the conventional detection method with one threshold.     

The Optimal Spectrum Sensing Time for Maximizing Throughput of 802.11-Based MAC Protocol for Cognitive Radio Networks Under Unsaturated Traffic Conditions

Cognitive radio has attracted considerable attention as an enabling technology for addressing the problem of radio frequency shortages. In cognitive radio networks (CRNs), secondary users (SUs) are allowed to opportunistically utilize the licensed spectrum bands of primary users (PUs) when these bands are temporarily unused. Thus, SUs should monitor the licensed spectrum bands to detect any PU signal. According to the sensing outcomes, SUs should vacate the spectrum bands or may use them. Generally, the spectrum sensing accuracy depends on the sensing time which influences the overall throughput of SUs. That is, there is a fundamental tradeoff between the spectrum sensing time and the achievable throughput of SUs. To determine the optimal sensing time and improve the throughput of SUs, considerable efforts have been expended under the saturated traffic and ideal channel assumptions. However, these assumptions are hardly valid in practical CRNs. In this paper, we provide the framework of an 802.11-based medium access control for CRNs, and we analyze this framework to find the optimal spectrum sensing time under the saturated and unsaturated traffic condition. Through simulation, the proposed analytic model is verified and the fundamental problem of the sensing-throughput tradeoff for CRNs is investigated.     

A prediction and scheduling framework in centralized cognitive radio network for energy efficient non‐real time communication

Advent of Internet of Things led to an exponential rise in battery‐operated sensors transmitting small non‐real time (NRT) data regularly. To this end, this work proposes a framework for centralized cognitive radio network (CRN) that facilitates better spectrum utilization and low‐cost opportunistic NRT data transfer with high energy efficiency. The novelty of this framework is to incorporate Hidden Markov Model–based prediction within the traditional cognitive radio sensing‐transmission cycle. To minimize the prediction time, we design a Hardware‐based Hidden Markov Model engine (H2M2) to be used by the cognitive base station (CBS). CBS exploits the H2M2 engine over high primary user (PU) activity channels to minimize the collisions between PUs and NRT secondary users, thereby reducing the SU energy consumption. However, this is at the cost of reduced throughput. Taking this into account, we propose an Intersensing‐Prediction Time Optimization algorithm that identifies the predictable PU activity channels and maximizes the throughput within a PU interference threshold. Furthermore, to minimize the total battery consumption of all the SUs within CRN, a Battery Consumption Minimizing Scheduler is designed at the CBS that efficiently allocates the predictable PU channels to the NRT SUs. By exploiting the unutilized high PU activity channels, the proposed Centralized Scheduling, Sensing and Prediction (CSSP) framework improves the spectral efficiency of the CRN. Exhaustive performance studies show that CSSP outperforms traditional nonpredictive sensing techniques in terms of energy efficiency and interference management. Finally, through a proof of concept, we validate the ability of CSSP framework in enabling NRT communication.     

Sensing-Throughput Tradeoff in Cluster-Based Cooperative Cognitive Radio Networks with A TDMA Reporting Frame Structure

This paper proposes clustering schemes to solve the sensing throughput tradeoff problem in cooperative cognitive radio networks (CCRNs). The throughput of CCRNs extremely depends on the spectrum sensing performance and data transmission time. In CCRNs, the more secondary users (SUs) for cooperation, the better performance of spectrum sensing. However, the overhead consumption increases as the quantity of cooperative SUs becomes huge, which will lead to less time for data transmission. In this paper, we propose a frame structure that takes the sensing results reporting time into consideration. In order to reduce the reporting time consumption, a centralized cluster-based cooperative cognitive radio system model is created based on the frame structure. The sensing-throughput tradeoff problem under both the perfect reporting channel and imperfect reporting channel scenarios are formulated. The proposed clustering schemes reduce the reporting time consumption and ensure the maximum transmission time of each SU. Numerical results show that the proposed clustering schemes achieve satisfying performance.     

基于可靠次用户信息的协作频谱感知算法研究

对认知无线电系统最基本要求之一就是次用户必须有能力以高的精确率来确定主用户是否存在。而以前对认知无线电频谱感知的研究表明：在实际认知网络中次用户之间的相互协作可以提高其频谱检测性能。然而,对于协作频谱感知而言,随着协作次用户数目的增加,势必会增大用于传输本地检测结果到融合中心的专用控制信道带宽,从而增加系统开销。该文在控制信道带宽有限的约束条件下,提出一种通过考虑可靠次用户信息的协作频谱感知算法来进一步改善频谱检测的性能。该算法的基本思想：只有具有可靠的本地检测结果的次用户才发送自己的检测结果到融合中心,否则,该次用户不发送任何信息。同时,对提出的该算法在理论上进行了推导,通过仿真结果表明：在控制信道带宽受限的约束下,相比于传统的或门协作频谱感知算法,提出的算法能够大大改善对主用户的检测性能。