Cooperative Secure Resource Allocation in Cognitive Radio Networks with Guaranteed Secrecy Rate for Primary Users

Mokari, Nader; Parsaeefard, Saeedeh; Saeedi, Hamid; Azmi, Paeiz

doi:10.1109/twc.2013.010214.130929

Cited by 72 publications

(55 citation statements)

References 29 publications

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“…In fact, as will be shown later in (25) and (26), this jamming antenna selection scheme maximizes the upper and lower bounds of the secrecy capacity.…”

Section: ) Eavesdropping Capacity At Ementioning

confidence: 67%

“…Noting that the jamming antenna is selected among K 2 antennas, and from (25), the lower bound of the secrecy capacity in Case 1 is obtained as…”

Section: ) Upper Bound -Casementioning

confidence: 99%

“…In [24], transmission powers are carefully allocated between the primary and secondary users to balance the primary and secondary secrecy rates. Similarly in [25], powers are optimally allocated to maximize the secrecy rate in a MIMO cognitive network, which is achieved with distributed beamforming at the source or the relay. All of these approaches mainly focus on the physical layer secrecy in the CR network.…”

Section: Introductionmentioning

confidence: 99%

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Dual Antenna Selection in Secure Cognitive Radio Networks

Chen

Gong

Xiao

et al. 2016

IEEE Trans. Veh. Technol.

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This paper investigates data transmission and physical layer secrecy in cognitive radio network. We propose to apply full duplex transmission and dual antenna selection at secondary destination node. With the full duplex transmission, the secondary destination node can simultaneously apply the receiving and jamming antenna selection to improve the secondary data transmission and primary secrecy performance respectively. This describes an attractive scheme in practice: unlike that in most existing approaches, the secrecy performance improvement in the CR network is no longer at the price of the data transmission loss. The outage probabilities for both the data transmission and physical layer secrecy are analyzed. Numerical simulations are also included to verify the performance of the proposed scheme.

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“…In fact, as will be shown later in (25) and (26), this jamming antenna selection scheme maximizes the upper and lower bounds of the secrecy capacity.…”

Section: ) Eavesdropping Capacity At Ementioning

confidence: 67%

“…Noting that the jamming antenna is selected among K 2 antennas, and from (25), the lower bound of the secrecy capacity in Case 1 is obtained as…”

Section: ) Upper Bound -Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dual Antenna Selection in Secure Cognitive Radio Networks

Chen

Gong

Xiao

et al. 2016

IEEE Trans. Veh. Technol.

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show abstract

“…In this subsection, we aim to investigate the convex optimization function (17) and propose an optimal joint power and time slot allocation policy for each channel realization with given and . By relaxing the time slot constraint, the Lagrangian function becomes…”

Section: Joint Power and Time Slot Allocation Policy For Each Channelmentioning

confidence: 99%

“…Recently, some researchers also focused on the secure resource allocation problem of the cognitive radio networks (CRNs) [16]. In [17], instantaneous and ergodic resource allocation problems were investigated in CRNs with guaranteed secrecy rate of the primary users. Secure robust resource allocation was taken into account for the relay-assisted CRNs in [18].…”

Section: Introductionmentioning

confidence: 99%

Fair Resource Allocation with QoS Guarantee in Secure Multiuser TDMA Networks

Bai

Wang

et al. 2018

Wireless Communications and Mobile Computing

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We investigate a secure multiuser time division multiple access (TDMA) system with statistical delay quality of service (QoS) guarantee in terms of secure effective capacity. An optimal resource allocation policy is proposed to minimize the -fair cost function of the average user power under the individual QoS constraint, which also balances the energy efficiency and fairness among the users. First, convex optimization problems associated with the resource allocation policy are formulated. Then, a subgradient iteration algorithm based on the Lagrangian duality theory and the dual decomposition theory is employed to approach the global optimal solutions. Furthermore, considering the practical channel conditions, we develop a stochastic subgradient iteration algorithm which is capable of dynamically learning the intended wireless channels and acquiring the global optimal solution. It is shown that the proposed optimal resource allocation policy depends on the delay QoS requirement and the channel conditions. The optimal policy can save more power and achieve the balance of the energy efficiency and the fairness compared with the other resource allocation policies.

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A new feature extraction and attacking node classification framework using PDCFE‐HPSMM model in cognitive radio networks

Ramasamy¹

2016

Int J Communication

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SUMMARYThe increasing demand of wireless communication introduces a challenge to an effective spectrum utilization. In wireless communication systems, the Cognitive Radio (CR) has emerged as a new key technology to address this issue, which allows an opportunistic access to the spectrum. The CRs form a CRN by extending the radio link features to network layer functions. The existing CR based wireless communication techniques has some drawbacks such as, inability to differentiate interference or noise from primary signals, it does not distinguish the different types of noise, low performance, not effective in spread spectrum detection, long observation time and high computational cost. To overwhelm these disadvantages, a novel method, namely, partial distribution based cyclostationary feature extraction-hidden probability state Markov model (PDCFE-HPSMM) is proposed in this work. The main intention of this technique is to extract the node features, classify the attacker nodes and predict the licensed and unlicensed bandwidth. At first, the CRN is formed with some set of CR nodes, and the communication links between the nodes are estimated. Then, the node features are extracted by employing the PDCFE technique. After that, the attacking nodes are classified based on those features with the help of a HPSMM classification technique. If the attacker is present in the network, the link between the attacking nodes to other nodes is disconnected; otherwise, the communication link is updated. In this work, the Rayleigh channels are used to predict the licensed and unlicensed bandwidth. Again, the HPSMM model is employed to optimally select the channel, and the scheduling technique is implemented to check the status of the channel for message transmission. If the channel is not busy, the message signals are multiplexed and transmitted to the receiver via the selected channel. The novel concept of this paper is, the proposed PDCFE technique extracts the features of the nodes in CRN; based on these features, the attacker nodes in the network are classified with the help of HPSMM technique. Moreover, the HPSMM is used to select the optimal channel for message transmission. The experimental results evaluate the performance of the proposed system in terms of bit error rate (BER), error rate, relay, false detection rate (FDR) and cumulative distribution function (CDF

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Cooperative Secure Resource Allocation in Cognitive Radio Networks with Guaranteed Secrecy Rate for Primary Users

Cited by 72 publications

References 29 publications

Dual Antenna Selection in Secure Cognitive Radio Networks

Dual Antenna Selection in Secure Cognitive Radio Networks

Fair Resource Allocation with QoS Guarantee in Secure Multiuser TDMA Networks

A new feature extraction and attacking node classification framework using PDCFE‐HPSMM model in cognitive radio networks

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