• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.357-366
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• 2013

Spectrum sensing, as a fundamental functionality of Cognitive Radio (CR), enables Secondary Users (SUs) to monitor the spectrum and detect spectrum holes that could be used. Recently, the security issues of Cognitive Radio Networks (CRNs) have attracted increasing research attention. As one of the attacks against CRNs, a Primary User Emulation (PUE) attack compromises the spectrum sensing of CR, where an attacker monopolizes the spectrum holes by impersonating the Primary User (PU) to prevent SUs from accessing the idle frequency bands. Energy detection is often used to sense the spectrum in CRNs, but the presence of PUE attack has not been considered. This study examined the effect of PUE attack on the performance of energy detection-based spectrum sensing technique. In the proposed protocol, the stationary helper nodes (HNs) are deployed in multiple stages and distributed over the coverage area of the PUs to deliver spectrum status information to the next stage of HNs and to SUs. On the other hand, the first stage of HNs is also responsible for inferring the existence of the PU based on the energy detection technique. In addition, this system provides the detection threshold under the constraints imposed on the probabilities of a miss detection and false alarm.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.344-347
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• 2011

In this paper, we propose the power control problem for cognitive radio networks (CRNs) that maximizes the total utility of the secondary users (SUs). We use the interference temperature constraints to protect the primary users (PUs). The utility functions of SUs can be any increasing functions. We formulate the power control problem as monotonic optimization that can be solved in centralization to achieve the global optimum.

• ETRI Journal
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• v.44 no.3
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• pp.400-412
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• 2022

In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).

• Journal of Communications and Networks
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• v.16 no.2
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• pp.183-192
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• 2014

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4446-4462
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• 2019

In this paper, we focus on interference cancellation for three-hop cognitive radio networks (CRNs) over Rayleigh fading channels. In CRNs, secondary users (SUs) are allowed to opportunistically utilize the licensed spectrum during the idle time of primary users (PUs) to achieve spectrum sharing. However, the SUs maybe power constrained to avoid interference and cover a very short transmission range. We here propose an interference cancellation scheme (ICS) for three-hop CRNs to prolong the transmission range of SUs and improve their transmission efficiency. In the proposed scheme, a flexible transmission protocol is adopted to cancel the interference at both secondary relays and destinations at the same time. And a closed-form expression for the secondary outage probability over Rayleigh fading channels is derived to measure the system performance. Simulation results show that the proposed scheme can significantly reduce the secondary outage probability and increase the secondary diversity in comparison with the traditional cases.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.300-302
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• 2012

In this paper, we investigate the performance of multi-channel cognitive radio networks (CRNs) by taking into consideration the problem of channel assignment and link scheduling. We assume that secondary nodes are equipped with multiple radios and can switch among multiple channels. How to allocate channels to links and how much power used on each channel to avoid mutual interference among secondary links are the key problem for such CRNs. We formulate the problem of channel assignment and link scheduling as a combinatorial optimization problem. Then, we propose a the optimal solution and show that it converges to maximum optimum in some iterations by using numerical results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.353-360
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• 2014

In cognitive radio networks (CRNs), SU (secondary user)'s transmissions are frequently disrupted by PU (primary user)'s transmission. Therefore SU expereiences consecutive retransmission timeout and its exponential backoff, and subsequently, the TCP of SU does not proceed with the transmission even after the disruption is over or the SU succeeds to hold an idle channel. In order to solve this problem, we propose a cross-layer approach called TCP-Freeze-CR. Moreover we consider a practical scenario where either secondary transmitter (ST) or secondary receiver (SR) detects PU's transmission, which results in the need of spectrum synchronization mechanism. All of our proposals are implemented and verified with a real CRN testbed consisting of 6 software radios called USRP. The experimental results illustrate that standard TCP suffers from significant performance degradation and show that TCP-Freeze-CR greatly mitigates the degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3414-3434
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• 2016

Classical key generation is complicated to update and key distribution generally requires fixed infrastructures. In order to eliminate these restrictions researchers have focused much attention on physical-layer (PHY-layer) based key generation methods. In this paper, we present a PHY-layer fingerprints based fuzzy key generation scheme, which works to prevent primary user emulation (PUE) attacks and spectrum sensing data falsification (SSDF) attacks, with multi-node collaborative defense strategies. We also propose two algorithms, the EA algorithm and the TA algorithm, to defend against eavesdropping attacks and tampering attacks in mobile cognitive radio networks (CRNs). We give security analyses of these algorithms in both the spatial and temporal domains, and prove the upper bound of the entropy loss in theory. We present a simulation result based on a MIMO-OFDM communication system which shows that the channel response characteristics received by legitimates tend to be consistent and phase characteristics are much more robust for key generation in mobile CRNs. In addition, NIST statistical tests show that the generated key in our proposed approach is secure and reliable.