scholarly journals Low Energy Consumption Compressed Spectrum Sensing Based on Channel Energy Reconstruction in Cognitive Radio Network

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1264 ◽  
Author(s):  
Yuan Fang ◽  
Lixiang Li ◽  
Yixiao Li ◽  
Haipeng Peng ◽  
Yixian Yang
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Compressed Sensing ◽  
Tensor Product ◽  
Communication Networks ◽  
Spectrum Sensing ◽  
Vital Role ◽  
Sensor Nodes ◽  
Sensing Matrix ◽  
Low Dimensional

For wireless communication networks, cognitive radio (CR) can be used to obtain the available spectrum, and wideband compressed sensing plays a vital role in cognitive radio networks (CRNs). Using compressed sensing (CS), sampling and compression of the spectrum signal can be simultaneously achieved, and the original signal can be accurately recovered from the sampling data under sub-Nyquist rate. Using a set of wideband random filters to measure the channel energy, only the recovery of the channel energy is necessary, rather than that of all the original channel signals. Based on the semi-tensor product, this paper proposes a new model to achieve the energy compression and reconstruction of spectral signals, called semi-tensor product compressed spectrum sensing (STP-CSS), which is a generalization of traditional spectrum sensing. The experimental results show that STP-CSS can flexibly generate a low-dimensional sensing matrix for energy compression and parallel reconstruction of the signal. Compared with the existing methods, STP-CSS is proved to effectively reduce the calculation complexity of sensor nodes. Hence, the proposed model markedly improves the spectrum sensing speed of network nodes and saves storage space and energy consumption.

Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks

2015 ◽  
pp. 100-121
Author(s):  
Saud Althunibat ◽  
Sandeep Narayanan ◽  
Marco Di Renzo ◽  
Fabrizio Granelli
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
High Energy ◽  
Radio Networks ◽  
Participation Decision ◽  
Consumption Energy ◽  
Fusion Centre

One of the main problems of Cooperative Spectrum Sensing (CSS) in cognitive radio networks is the high energy consumption. Energy is consumed while sensing the spectrum and reporting the results to the fusion centre. In this chapter, a novel partial CSS is proposed. The main concern is to reduce the energy consumption by limiting the number of participating users in CSS. Particularly, each user individually makes the participation decision. The energy consumption in a CSS round is expected by the user itself and compared to a predefined threshold. The corresponding user will participate only if the expected amount of energy consumed is less than the participation threshold. The chapter includes optimizing the participation threshold for energy efficiency maximization. The simulation results show a significant reduction in the energy consumed compared to the conventional CSS approach.

Stackelberg Game Theoretic Framework in Cognitive Green Heterogeneous Networks

2017 ◽  
pp. 269-286
Author(s):  
Chungang Yang ◽  
Pengyu Huang ◽  
Jia Xiao ◽  
Lingxia Wang ◽  
Jiandong Li
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Cellular Networks ◽  
Communication Networks ◽  
Cognitive Radio Networks ◽  
Stackelberg Game ◽  
Radio Networks ◽  
Heterogeneous Cellular Networks ◽  
Game Theoretic

Game theory has found an extensive application in wireless communication networks including cognitive radio networks, heterogeneous cellular networks, cooperative relay networks. Also, cognitive radio networks, green communications and heterogeneous cellular networks have attracted a wide attention on improve the spectrum efficiency and energy efficiency; therefore, the capacity, the coverage and the energy consumption. However, interference problem and energy consumption are critical for these networks. Introducing hierarchy among different decision-making players in cognitive, heterogeneous, green, cooperative cellular networks can both save energy and mitigate interference, thus enhance throughput. Stackelberg game suits to model, analyze and design the distributed algorithms in these hierarchical decision-making networking scenarios. In this chapter, we introduce basics of Stackelberg game and survey the extensive applications of Stackelberg game in cognitive, heterogeneous, cooperative cellular networks with the emphasis on resource management, green commutations design and interference management. This chapter highlights the potentials and applications with the promising vision of Stackelberg game theoretic framework for future cognitive green heterogeneous cellular networks.

scholarly journals An Unequal Cluster-based Routing Protocol Based on Data Controlling for Wireless Sensor Network

2016 ◽  
Vol 6 (5) ◽  
pp. 2403
Author(s):  
Slaheddine Chelbi ◽  
Majed Abdouli ◽  
Mourad Kaddes ◽  
Claude Duvallet ◽  
Rafik Bouaziz
Keyword(s):  
Energy Consumption ◽  
Communication Networks ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Link Cost ◽  
Data Controller ◽  
Routing Tree ◽  
Multiple Metrics

<p>Wireless Sensor Networks (WSN) differ from traditional wireless communication networks in several characteristics. One of these characteristics is power awarness, due to the fact that the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed to minimize energy consumption and preserve the longevity of the network. In this paper, we propose (i) to fairly balance the load among nodes. For this, we generate an unequal clusters size where the cluster heads (CH) election is based on energy availability, (ii) to reduce the energy consumption due to the transmission by using multiple metrics in the CH jointure process and taking into account the link cost, residual energy and number of cluster members to construct the routing tree and (iii) to minimize the number of transmissions by avoiding the unnecessary updates using sensitive data controller. Simulation results show that our Advanced Energy-Efficient Unequal Clustering (AEEUC) mechanism improves the fairness energy consumption among all sensor nodes and achieves an obvious improvement on the network lifetime.</p>

scholarly journals A Survey on Comparisons of Cryptographic Algorithms Using Certain Parameters in WSN

2017 ◽  
Vol 7 (4) ◽  
pp. 2232 ◽  
Author(s):  
Pooja Singh ◽  
R.K. Chauhan
Keyword(s):  
Energy Consumption ◽  
Processing Speed ◽  
Energy Efficient ◽  
Resource Constraints ◽  
Vital Role ◽  
Sensor Nodes ◽  
Diffie Hellman ◽  
Dna Cryptography ◽  
Cryptographic Algorithms ◽  
Encryption Algorithms

The Wireless Sensor Networks (WSNs) have spread its roots in almost every application. Owing to their scattered nature of sensor nodes, they are more prone to attacks. There are certain applications e.g. military, where sensor data’s confidentiality requirement during transmission is essential. Cryptography has a vital role for achieving security in WSNs.WSN has resource constraints like memory size, processing speed and energy consumption which bounds the applicability of existing cryptographic algorithms for WSN. Any good security algorithms has higher energy consumption by the nodes, so it’s a need to choose most energy-efficient cryptographic encryption algorithms for WSNs. This paper surveys different asymmetric algorithms such as RSA, Diffie-Hellman, DSA, ECC, hybrid and DNA cryptography. These algorithms are compared based on their key size, strength, weakness, attacks and possible countermeasures in the form of table.

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