scholarly journals Rate Request Sequenced Bit Loading Secondary User Reallocation Algorithm for DMT Systems in Cognitive Radio

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
S. Chris Prema ◽  
Dara Sudha Rani
Keyword(s):  
Cognitive Radio ◽  
Signal To Noise Ratio ◽  
Secondary User ◽  
Modulation Scheme ◽  
Channel State ◽  
Secondary Users ◽  
State Information ◽  
Discrete Multitone ◽  
Bit Loading ◽  
User Rate

A rate request sequenced bit loading reallocation algorithm is proposed. The spectral holes detected by spectrum sensing (SS) in cognitive radio (CR) are used by secondary users. This algorithm is applicable to Discrete Multitone (DMT) systems for secondary user reallocation. DMT systems support different modulation on different subchannels according to Signal-to-Noise Ratio (SNR). The maximum bits and power that can be allocated to each subband is determined depending on the channel state information (CSI) and secondary user modulation scheme. The spectral holes or free subbands are allocated to secondary users depending on the user rate request and subchannel capacity. A comparison is done between random rate request and sequenced rate request of secondary user for subchannel allocation. Through simulations it is observed that with sequenced rate request higher spectral efficiency is achieved with reduced complexity.

scholarly journals Spectrum Sensing in Cognitive Radio using Frequency Domain

2019 ◽  
Vol 9 (2) ◽  
pp. 3475-3477
Keyword(s):  
Cognitive Radio ◽  
Frequency Domain ◽  
Spectrum Sensing ◽  
Bandwidth Allocation ◽  
Dynamic Spectrum Access ◽  
Signal To Noise Ratio ◽  
Wide Band ◽  
Energy Detection ◽  
Secondary Users ◽  
Sensing Applications

An efficient bandwidth allocation and dynamic bandwidth access away from its previous limits is referred as cognitive radio (CR).The limited spectrum with inefficient usage requires the advances of dynamic spectrum access approach, where the secondary users are authorized to utilize the unused temporary licensed spectrum. For this reason it is essential to analyze the absence/presence of primary users for spectrum usage. So spectrum sensing is the main requirement and developed to sense the absence/ presence of a licensed user. This paper shows the design model of energy detection based spectrum sensing in frequency domain utilizing Binary Symmetric Channel (BSC) ,Additive white real Gaussian channel (AWGN), Rayleigh fading channel users for 16-Quadrature Amplitude Modulation(QAM) which is utilized for the wide band sensing applications at low Signal to noise Ratio(SNR) level to reduce the false error identification. The spectrum sensing techniques has least computational complexity. Simulink model for the energy detection based spectrum sensing using frequency domain in MATLAB 2014a.

scholarly journals Cooperative Spectrum Sensing Based on Multi-Features Combination Network in Cognitive Radio Network

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 129
Author(s):  
Mingdong Xu ◽  
Zhendong Yin ◽  
Yanlong Zhao ◽  
Zhilu Wu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Primary User ◽  
Radio Spectrum ◽  
Local Information ◽  
Channel State ◽  
Single Node

cognitive radio, as a key technology to improve the utilization of radio spectrum, acquired much attention. Moreover, spectrum sensing has an irreplaceable position in the field of cognitive radio and was widely studied. The convolutional neural networks (CNNs) and the gate recurrent unit (GRU) are complementary in their modelling capabilities. In this paper, we introduce a CNN-GRU network to obtain the local information for single-node spectrum sensing, in which CNN is used to extract spatial feature and GRU is used to extract the temporal feature. Then, the combination network receives the features extracted by the CNN-GRU network to achieve multifeatures combination and obtains the final cooperation result. The cooperative spectrum sensing scheme based on Multifeatures Combination Network enhances the sensing reliability by fusing the local information from different sensing nodes. To accommodate the detection of multiple types of signals, we generated 8 kinds of modulation types to train the model. Theoretical analysis and simulation results show that the cooperative spectrum sensing algorithm proposed in this paper improved detection performance with no prior knowledge about the information of primary user or channel state. Our proposed method achieved competitive performance under the condition of large dynamic signal-to-noise ratio.

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