Optimal Energy-Efficient Transmission for Hybrid Spectrum Sharing in Cooperative Cognitive Radio Networks

In order to improve the energy efficiency(EE)in cognitive radio(CR),this paper investigates the joint design of cooperative spectrum sensing time and the power control optimization problem for the secondary user systems to achieve the maximum energy efficiency in a cognitive network based on hybrid spectrum sharing,meanwhile considering the maximum transmit power,user quality of service(QoS)requirements,interference limitations,and primary user protection.The optimization of energy efficient sensing time and power allocation is formulated as a non-convex optimization problem.The Dinkelbach’s method is adopted to solve this problem and to transform the non-convex optimization problem in fractional form into an equivalent optimization problem in the form of subtraction.Then,an iterative power allocation algorithm is proposed to solve the optimization problem.The simulation results show the effectiveness of the proposed algorithms for energy-efficient resource allocation in the cognitive network.

Optimal Energy Efficiency Resource Allocation Strategy for Cognitive Clustering Network under PUEA Attack

5G has pushed the use of radio spectrum to a new level,and cognitive clustering network can effectively improve the utilization of radio spectrum,which is a feasible way to solve the growing demand for wireless communications.However,cognitive clustering network is vulnerable to PUEA attack,which will lead to the degradation of system detection performance,thereby reducing the energy efficiency.Aiming at these problems,this paper investigates the optimal energy efficiency resource allocation scheme for cognitive clustering network under PUEA attack.A cooperative user selection algorithm based on selection factor is proposed to effectively resist PUEA user attack and improve detection performance.We construct the energy efficiency optimization problem under multi-constraint conditions and transform the nonlinear programming problem into parametric programming problem,which is solved by Lagrangian function and Karush-Kuhn-Tucker condition.Then the sub-gradient iterative algorithm based on optimal energy efficiency under PUEA attack is proposed and its complexity is analyzed.Simulation results indicate that proposed method is effective when subjected to PUEA attacks,and the impact of different parameters on energy efficiency is analyzed.

A Reversible Data Hiding Algorithm Based on Image Camouflage and Bit-Plane Compression

Reversible data hiding in encrypted image(RDHEI)is a widely used technique for privacy protection,which has been developed in many applications that require high confidentiality,authentication and integrity.Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image.Moreover,the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers.This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression.A camouflage encryption algorithm is used to transform a secret image into another meaningful target image,which can cover both secret image and encryption behavior based on“plaintext to plaintext”transformation.An edge optimization method based on prediction algorithm is designed to improve the image camouflage encryption quality.The reversible data hiding based bit-plane level compression,which can improve the redundancy of the bit plane by Gray coding,is used to embed watermark in the camouflage image.The experimental results also show the superior performance of the method in terms of embedding capacity and image quality.