Spectrum Sensing Using Hybrid Gravitational Search Genetic Algorithm Based Predictor Model in Cognitive Radio Networks

2017 ◽  
Author(s):  
A Priyadharshini ◽  
M Sundarambal
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Gravitational Search ◽  
Predictor Model

scholarly journals An Optimal Bit Allocation Scheme Based on Genetic Algorithm for Cooperative Spectrum Sensing in Cognitive Radio NetworksAn Optimal Bit Allocation Scheme Based on Genetic Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

2021 ◽  
Author(s):  
Junhai Luo ◽  
Zhiyan Wang ◽  
Yuxin Tian ◽  
Yu Chen
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cognitive Radio ◽  
Objective Function ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Bit Allocation ◽  
Allocation Scheme

Abstract In cooperative spectrum sensing (CSS), there are two ways for the secondary users (SU) to deliver their sensing data or local decisions to the information fusion center (FC): hard-decision (HD) and soft-decision (SD). In HD or SD, the number of bits transmitted by the SUs is always the same and static. However, considering the differences of different SUs in the environment, remaining energy, distances to the FC, and so on, the number of bits transmitted by different SUs should be different. Besides, the reliability of transmitted data by different SUs to the FC is also different. Therefore, this paper proposes an optimized bit allocation scheme based on the genetic algorithm (GA-BAS) for CSS in cognitive radio networks (CRNs). In the proposed scheme, the number of bits transmitted by each SU is different and would be allocated by the FC according to GA-BAS algorithm, and the FC would fuse the transmitted data by each SU with an allocated weight, which could represent the reliability of the SU. Firstly, a simple quantization scheme based on the sub-partitioning of the local decision space is designed to quantify the raw sensing data. Then, the objective function of the overall detection probability and the objective function of energy consumption about the number of allocated bits and the value of the allocated weight of each SU are derived. Finally, the number of allocated bits of each SU would be optimized by an improved genetic algorithm, and an overall decision rule would be given to obtain a global decision. Simulation results show that the proposed scheme (GA-BAS) gets a tradeoff between energy consumption and detection performance. In addition, the proposed algorithm achieves better detection performance, which is close to that of the equal gain combining scheme (EGC), but consumes less energy.

Joint spectrum sensing and resource allocation optimization using genetic algorithm for frequency hopping-based cognitive radio networks

2018 ◽  
Vol 31 (13) ◽  
pp. e3733 ◽  
Author(s):  
Sang-Jo Yoo ◽  
Anish Prasad Shrestha ◽  
Myunghwan Seo ◽  
Chul-Hee Han ◽  
Minho Park ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Frequency Hopping ◽  
Radio Networks ◽  
Joint Spectrum

scholarly journals Robust Spectrum Sensing via Double-Sided Neighbor Distance Based on Genetic Algorithm in Cognitive Radio Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Noor Gul ◽  
Muhammad Sajjad Khan ◽  
Junsu Kim ◽  
Su Min Kim
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Decision Fusion ◽  
Radio Networks ◽  
Majority Voting ◽  
Soft Decision ◽  
Neighbor Distance ◽  
Hard Decision

In cognitive radio networks (CRNs), secondary users (SUs) can access vacant spectrum licensed to a primary user (PU). Therefore, accurate and timely spectrum sensing is vital for efficient utilization of available spectrum. The sensing result at each SU is unauthentic due to fading, shadowing, and receiver uncertainty problems. Cooperative spectrum sensing (CSS) provides a solution to these problems. In CSS, false sensing reports at the fusion center (FC) received from malicious users (MUs) drastically degrade the performance of cooperation in PU detection. In this paper, we propose a robust spectrum sensing scheme to minimize the effects of false sensing reports by MUs. The proposed scheme focuses on double-sided neighbor distance (DSND) based on genetic algorithm (GA) in order to filter out the MU sensing reports in CSS. The simulation results show that the sensing results are more accurate and reliable for the proposed GA majority-voting hard decision fusion (GAMV-HDF) and GA weighted soft decision fusion (GAW-SDF) compared to conventional equal gain combination soft decision fusion (EGC-SDF), maximum gain combination soft decision fusion (MGC-SDF), and majority-voting hard decision fusion (MV-HDF) schemes in the presence of MUs.

Optimization of Cooperative Spectrum Sensing in Cluster-Based Cognitive Radio Networks with Soft Data Fusion

2013 ◽  
Vol E96.B (11) ◽  
pp. 2923-2932 ◽  
Author(s):  
Ying WANG ◽  
Wenxuan LIN ◽  
Weiheng NI ◽  
Ping ZHANG
Keyword(s):  
Cognitive Radio ◽  
Data Fusion ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Soft Data

An Energy Efficient Spectrum Aware Routing for Cognitive Radio Networks (CRNs)

2020 ◽  
Vol 10 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Jijesh J J ◽  
Mahaveer Penna ◽  
Shiva Shankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Research Work ◽  
Spectrum Management ◽  
Residual Energy ◽  
Radio Networks ◽  
Traffic Load ◽  
The Impact

Back Ground/ Aims:: Now-a-days in the Wireless Communications some of the spectrum bands are underutilized or unutilized; the spectrum can be utilized properly by using the Cognitive Radio Techniques using the Spectrum Sensing mechanisms. Objectives:: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods:: The detection of the spectrum hole plays a vital role in the routing of Cognitive Radio Networks (CRNs). While detecting the spectrum holes and the routing, sensing is impacted by the hidden node issues and exposed node issues. The impact of sensing is improved by incorporating the Cooperative Spectrum Sensing (CSS) techniques. Along with these issues the spectrum resources changes time to time in the routing. Results:: All the issues are addressed with An Energy Efficient Spectrum aware Routing (EESR) protocol which improves the timeslot and the routing schemes. The overall network life time is improved with the aid of residual energy concepts and the overall network performance is improved. Conclusion:: The proposed protocol (EESR) is an integrated system with spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it improves the Network Lifetime of the Overall Network and the Individual CR user, along with this the performance of the proposed protocol outperforms the conventional state of art routing protocols.

Secure spectrum sensing in relay-based cognitive radio networks

2021 ◽  
Author(s):  
Arun Sivakumaran ◽  
B. T. Maharaj ◽  
Attahiru S. Alfa
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks

Utility driven cooperative spectrum sensing scheduling for heterogeneous multi-channel cognitive radio networks

2021 ◽  
Author(s):  
Prakash Chauhan ◽  
Sanjib K. Deka ◽  
Bijoy Chand Chatterjee ◽  
Nityananda Sarma
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks
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