Joint Optimization of Spectrum Sensing and Transmit Power in Energy Harvesting Cognitive Radio Sensor Networks

2019 ◽  
Vol 62 (2) ◽  
pp. 215-230 ◽  
Author(s):  
Fan Zhang ◽  
Tao Jing ◽  
Yan Huo ◽  
Kaiwei Jiang
Author(s):  
Yi Li ◽  
◽  
Jun Peng ◽  
Fu Jiang ◽  
Kaiyang Liu ◽  
...  

To address the inherent energy constraint in cognitive radio sensor networks, a novel joint optimization method of spectrum sensing and data transmission for energy efficiency is investigated in this paper. To begin with, a cooperative spectrum sensing scheme based on dynamic censoring is employed to shorten sensing time and save unnecessary spectrum sensing energy. Then to jointly optimize the energy efficiency, the distortion constrained probabilistic transmission scheme is utilized. Afterwards the sensing threshold solving issue can be formulated as a nonlinear minmax optimization problem with the detection probability and false alarm probability constraints. Solving by the Matlab software with the free OPTI toolbox, simulation results demonstrate that significant energy can be saved via the the proposed joint optimization method in various mobile cloud scenarios.


2015 ◽  
Vol 2015 ◽  
pp. 1-14
Author(s):  
Dawei Wang ◽  
Pinyi Ren ◽  
Qinghe Du ◽  
Li Sun ◽  
Yichen Wang

Aiming at allocating more licensed spectrum to wireless sensor nodes (SNs) under the constraint of the information security requirement of the primary system, in this paper, we propose a cooperative relaying and jamming secure transmission (CRJS) scheme in which SNs will relay primary message and jam primary eavesdrop concurrently with SN’s downlink and uplink information transmission in cognitive radio sensor networks (CRSNs). In our proposed CRJS scheme, SNs take advantages of physical layer secure technologies to protect the primary transmission and acquire some interference-free licensed spectrum as a reward. In addition, both decode-and-forward (DF) and amplify-and-forward (AF) relaying protocols are investigated in our proposed CRJS scheme. Our object is to maximize the transmission rate of SNs by optimal allocating of the relaying power, jamming power, and downlink and uplink transmit power under the target secure transmission rate requirement of the primary system. Moreover, two suboptimal algorithms are proposed to deal with these optimization problems. Furthermore, we analyze the transmission rate of SNs and allocate the relaying power, jamming power, and downlink and uplink transmit power for the asymptotic scenarios. Simulation results demonstrate the performance superiority of our developed strategy over conventional jamming scheme in terms of the transmission rate of WSN.


Author(s):  
Farooq Alam ◽  
Zahooruddin ◽  
Ayaz Ahmad ◽  
Muhammad Iqbal

In this chapter, the authors provide a comprehensive review of spectrum sensing in cognitive radio sensor networks. Firstly, they focus on general techniques utilized for spectrum sensing in wireless sensor networks. To have good understanding of core issues of spectrum sensing, the authors then give a brief description of cognitive radio networks. Then they give a thorough description of the main techniques that can be helpful in doing spectrum sensing in cognitive radio sensor network. The authors conclude this chapter with open research issues and challenges that need to be addressed to provide efficient spectrum sensing in order to minimize the limitations in cognitive radio sensor networks.


2015 ◽  
Vol 11 (9) ◽  
pp. 9 ◽  
Author(s):  
Yonghua Wang ◽  
Yuehong Li ◽  
Yiquan Zheng ◽  
Ting Liang ◽  
Yuli Fu

In order to maximize throughput and minimize interference of the wideband spectrum sensing problem in OFDM cognitive radio sensor networks, a linear weighted sum multi-objective algorithm based on the Particle Swarm Optimization is proposed. The multi-objective optimization advantages of Particle Swarm Optimization are utilized to solve the optimal threshold vector of the spectrum sensing problem in OFDM cognitive radio sensor networks. So the network can get a larger throughput under the condition of small interference. The simulation results show that the proposed algorithm can make larger throughput while keeping the interference is smaller in OFDM cognitive radio sensor networks. Thus the spectrum resources are used more effectively.


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