scholarly journals A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

2019 ◽  
Vol 10 (3) ◽  
pp. 18
Author(s):  
Tian Yang ◽  
Moez Esseghir ◽  
Lyes Khoukhi
Keyword(s):  
Large Scale ◽  
Optimization Methods ◽  
Primary User ◽  
System Throughput ◽  
Spectrum Access ◽  
Secondary Users ◽  
Complexity Of Algorithms ◽  
Performance Constraints ◽  
Spectrum Detection ◽  
Primary And Secondary Users

A large scale of spectrum sensing techniques are proposed to improve the use of spectrum resources. However, the EE (energy efficiency) should be guaranteed for both primary and secondary users, especially under various detection performance constraints. In this regard, the linking between activities of PU (primary user) and dynamic access behaviors of SUs (secondary users) should be considered in an integrated way. This survey has compared different existing scenarios and frameworks on EE optimizations. The principal objective is to enhance the system throughput and to coordinate on the physical layer of both PU and SUs, in order to enable a high-quality spectrum detection and a more efficient spectrum access. In the technical part, several optimization methods are introduced under PU’s constraints, and different methods based on game theory are applied to suitable cooperative sensing scenarios for SUs’ optimal access. Finally, the complexity of algorithms is compared, to further reduce the execution time and deploy real-time adaptation for users with lower delay.

scholarly journals 5G cognitive radio system design with new algorithm asynchronous spectrum sensing

2021 ◽  
Vol 10 (4) ◽  
pp. 2046-2054
Author(s):  
Mohammed Mehdi Saleh ◽  
Ahmed A. Abbas ◽  
Ahmed Hammoodi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Spectrum Access ◽  
Secondary Users ◽  
Radio System ◽  
Wireless Applications ◽  
Fifth Generation ◽  
Time Required

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

scholarly journals A Robust Cooperative Spectrum Sensing-Assisted Multiuser Resource Allocation Scheme

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Jun Du ◽  
Daoxing Guo ◽  
Bangning Zhang ◽  
Yunxia Su
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
System Throughput ◽  
Allocation Scheme ◽  
Spectrum Access ◽  
Primary User Emulation Attack ◽  
Resource Allocation Scheme

Cognitive radio (CR), which is proposed as a solution for spectrum scarcity, imposes some threats to the network. One severe attack to cognitive radio network is the primary user emulation attack (PUEA), in which an attacker may transmit its signal with high power or mimic specific features of the primary user’s signal to prevent secondary users from accessing the licensed spectrum. In this paper, we study a subcarrier and power allocation problem for orthogonal frequency division multiple access-(OFDMA-) based CR systems in the presence of PUEA. To maximize the system throughput while keeping the interference introduced to the primary user (PU) below given thresholds with a certain probability, a joint design of a robust cooperative spectrum sensing and a resource allocation scheme is proposed. In the proposed scheme, the inaccurate classification of PU signals and PUEA signals provided by robust cooperative spectrum sensing is utilized by resource scheduling module. To further exploit the underutilized spectrum bands, we also evaluate the performance of the proposed scheme in the hybrid overlay/underlay spectrum access mechanism. Numerical results demonstrate the effectiveness of the proposed scheme compared to conventional scheme regardless of the number of SUs or the kind of spectrum access mechanism being used.

scholarly journals Throughput Maximization Based on Optimal Access Probabilities in Cognitive Radio System

2021 ◽  
Author(s):  
Lian Zhao
Keyword(s):  
Cognitive Radio ◽  
Primary User ◽  
Throughput Maximization ◽  
System Throughput ◽  
Secondary System ◽  
Spectrum Utilization ◽  
Secondary Users ◽  
Radio System ◽  
Low Efficiency ◽  
Service State

Well-established fact shows that the fixed spectrum allocation policy conveys to the low spectrum utilization. The cognitive radio technique promises to improve the low efficiency. This paper proposes an optimized access strategy combining overlay scheme and underlay scheme for the cognitive radio. We model the service state of the system as a continuous-time Markov model. Based on the service state, the overlay manner or/and the underlay manner is/are used by the secondary users. When the primary user is not transmitting and only one secondary user has the requirement to transmit, the secondary system adopts the overlay scheme. When the primary user is transmitting and the secondary users want to transmit simultaneously, an underlay scheme with an access probability is adopted. We obtain the optimal access probability in a closed form which maximizes the overall system throughput

scholarly journals Throughput Maximization Based on Optimal Access Probabilities in Cognitive Radio System

2021 ◽  
Author(s):  
Lian Zhao
Keyword(s):  
Cognitive Radio ◽  
Primary User ◽  
Throughput Maximization ◽  
System Throughput ◽  
Secondary System ◽  
Spectrum Utilization ◽  
Secondary Users ◽  
Radio System ◽  
Low Efficiency ◽  
Service State

Well-established fact shows that the fixed spectrum allocation policy conveys to the low spectrum utilization. The cognitive radio technique promises to improve the low efficiency. This paper proposes an optimized access strategy combining overlay scheme and underlay scheme for the cognitive radio. We model the service state of the system as a continuous-time Markov model. Based on the service state, the overlay manner or/and the underlay manner is/are used by the secondary users. When the primary user is not transmitting and only one secondary user has the requirement to transmit, the secondary system adopts the overlay scheme. When the primary user is transmitting and the secondary users want to transmit simultaneously, an underlay scheme with an access probability is adopted. We obtain the optimal access probability in a closed form which maximizes the overall system throughput

scholarly journals Deep Learning for Spectrum Sensing in Cognitive Radio

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 147
Author(s):  
Surendra Solanki ◽  
Vasudev Dehalwar ◽  
Jaytrilok Choudhary
Keyword(s):  
Deep Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Structural Information ◽  
Primary User ◽  
Secondary Users ◽  
Spectrum Detection ◽  
Free Spectrum ◽  
Margin Of Error ◽  
Insight Into

The detection of primary user signals is essential for optimum utilization of a spectrum by secondary users in cognitive radio (CR). The conventional spectrum sensing schemes have the problem of missed detection/false alarm, which hampers the proper utilization of spectrum. Spectrum sensing through deep learning minimizes the margin of error in the detection of the free spectrum. This research provides an insight into using a deep neural network for spectrum sensing. A deep learning based model, “DLSenseNet”, is proposed, which exploits structural information of received modulated signals for spectrum sensing. The experiments were performed using RadioML2016.10b dataset and the outcome was studied. It was found that “DLSenseNet” provides better spectrum detection than other sensing models.

scholarly journals Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm

2021 ◽  
Vol 11 (10) ◽  
pp. 4438
Author(s):  
Satyendra Singh ◽  
Manoj Fozdar ◽  
Hasmat Malik ◽  
Maria del Valle Fernández Moreno ◽  
Fausto Pedro García Márquez
Keyword(s):  
Wind Power ◽  
Electricity Market ◽  
Large Scale ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimization Methods ◽  
Bidding Strategy ◽  
Wind Speed Profile ◽  
Gravitational Search ◽  
Modified Gravitational Search Algorithm

It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.

scholarly journals On the Throughput Optimization in Large-Scale Batch-Processing Systems

2021 ◽  
Vol 48 (3) ◽  
pp. 128-129
Author(s):  
Sounak Kar ◽  
Robin Rehrmann ◽  
Arpan Mukhopadhyay ◽  
Bastian Alt ◽  
Florin Ciucu ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Field ◽  
Queueing Network ◽  
Processing System ◽  
Batch Size ◽  
System Throughput ◽  
Throughput Optimization ◽  
Mean Field Model ◽  
Optimal Batch Size ◽  
Globally Attractive

We analyze a data-processing system with n clients producing jobs which are processed in batches by m parallel servers; the system throughput critically depends on the batch size and a corresponding sub-additive speedup function that arises due to overhead amortization. In practice, throughput optimization relies on numerical searches for the optimal batch size which is computationally cumbersome. In this paper, we model this system in terms of a closed queueing network assuming certain forms of service speedup; a standard Markovian analysis yields the optimal throughput in w n4 time. Our main contribution is a mean-field model that has a unique, globally attractive stationary point, derivable in closed form. This point characterizes the asymptotic throughput as a function of the batch size that can be calculated in O(1) time. Numerical settings from a large commercial system reveal that this asymptotic optimum is accurate in practical finite regimes.

Sign in / Sign up

Export Citation Format

Share Document