User sensing based on MIMO cognitive radio sensor networks

Ma, Wei; Wu, Mu Qing; Liu, Dong; Wang, Meng Ling

doi:10.1109/iccsit.2009.5234387

Cited by 9 publications

(8 citation statements)

References 9 publications

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“…Furthermore, higher detection probabilities of a PU signal can be accomplished by cooperative spectrum sensing (CSS) and SLC, as shown in [9,39,43]. In CSS, the information from different CR users is combined to make a decision.…”

Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

“…In CSS, the information from different CR users is combined to make a decision. CSS together with multiple antenna techniques (such as SLC) results in the better detection performance of OFDM signals at low values of SNR [43]. The author in [9] showed that diversity combining schemes can help to reduce the impact of multipath fading.…”

Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

“…The previous research showed that the implementation of MIMO transmissions has an impact on the ED process [9,27,[36][37][38][39][40][41][42][43]. Although a number of issues has been considered in related works, a comprehensive analysis dedicated to the ED performance based on SLC technique in MIMO-OFDM systems is still missing.…”

Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

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Performance Analyses of Energy Detection Based on Square-Law Combining in MIMO-OFDM Cognitive Radio Networks

Lörincz

Ramljak²,

Begušić

2021

Sensors

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Cognitive radio (CR) technology has the potential to detect and share the unutilized spectrum by enabling dynamic spectrum access. To detect the primary users’ (PUs) activity, energy detection (ED) is widely exploited due to its applicability when it comes to sensing a large range of PU signals, low computation complexity, and implementation costs. As orthogonal frequency-division multiplexing (OFDM) transmission has been proven to have a high resistance to interference, the ED of OFDM signals has become an important local spectrum-sensing (SS) concept in cognitive radio networks (CRNs). In combination with multiple-input multiple-output (MIMO) transmissions, MIMO-OFDM-based transmissions have started to become a widely accepted air interface, which ensures a significant improvement in spectral efficiency. Taking into account the future massive implementation of MIMO-OFDM systems in the fifth and sixth generation of mobile networks, this work introduces a mathematical formulation of expressions that enable the analysis of ED performance based on the square-law combining (SLC) method in MIMO-OFDM systems. The analysis of the ED performance was done through simulations performed using the developed algorithms that enable the performance analysis of the ED process based on the SLC in the MIMO-OFDM systems having a different number of transmit (Tx) and receive (Rx) communication branches. The impact of the distinct factors including the PU Tx power, the false alarm probability, the number of Tx and Rx MIMO branches, the number of samples in the ED process, and the different modulation techniques on the ED performance in environments with different levels of signal-to-noise ratios are presented. A comprehensive analysis of the obtained results indicated how the appropriate selection of the analyzed factors can be used to enhance the ED performance of MIMO-OFDM-based CRNs.

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Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

Section: Related Work On the Spectrum Sensing Of Ofdm Signals Based On The Ed Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Performance Analyses of Energy Detection Based on Square-Law Combining in MIMO-OFDM Cognitive Radio Networks

Lörincz

Ramljak²,

Begušić

2021

Sensors

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“…OFDM based MIMO cognitive radio network recognizes the OFDM signal with multiple antenna detector of the CR receiver. It resulted in the critical development of primary user identification of the square law combining with energy detection of a MIMO cognitive radio sensor networks [46]. Machine learning techniques are adopted in several works [32][13] to allow CR users to be trained about the nature of the system.…”

Section: Background Methodologymentioning

confidence: 99%

Improved Convolutional Neural Network Based Cooperative Spectrum Sensing For Cognitive Radio

2021

KSII TIIS

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Cognitive radio systems are being implemented recently to tackle spectrum underutilization problems and aid efficient data traffic. Spectrum sensing is the crucial step in cognitive applications in which cognitive user detects the presence of primary user (PU) in a particular channel thereby switching to another channel for continuous transmission. In cognitive radio systems, the capacity to precisely identify the primary user's signal is essential to secondary user so as to use idle licensed spectrum. Based on the inherent capability, a new spectrum sensing technique is proposed in this paper to identify all types of primary user signals in a cognitive radio condition. Hence, a spectrum sensing algorithm using improved convolutional neural network and long short-term memory (CNN-LSTM) is presented. The principle used in our approach is simulated annealing that discovers reasonable number of neurons for each layer of a completely associated deep neural network to tackle the streamlining issue. The probability of detection is considered as the determining parameter to find the efficiency of the proposed algorithm. Experiments are carried under different signal to noise ratio to indicate better performance of the proposed algorithm. The PU signal will have an associated modulation format and hence identifying the presence of a modulation format itself establishes the presence of PU signal.

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“…The following is an explanation of what is meant by the term "cognitive radio": "A 'cognitive radio' is a radio that is capable of changing its transmitter parameters depending on involvement with the environment within which it operates(M. Awasthi, 2017) [11]. By the method of sensing under the spectrums by utilization, also known as the gap spectrums or white spaces, the CR method, a revolutionary paradigm, enables the SU to employ the spectrums are in an opportunistic manner (Huazi Zhang, 2011) [16][17][18]. As a result, the SU is able to utilize the spectrum effectively.…”

Section: Introductionmentioning

confidence: 99%

Cooperative Spectrum Sensing with Amplify and Forward Scheme in CRNs

Sharma,

Awasthi

2023

J. Phys.: Conf. Ser.

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Recent research has identified cognitive radio (CR) as a possible solution for increasing spectrum usage by allowing secondary access to unlicensed bands. Having no interference with the primary system is a need for this secondary access. Due to this requirement, spectrum sensing becomes a crucial component of cognitive radio systems. The ease and effectiveness of energy detection make it an appealing technique among popular spectrum sensing techniques. The uses of the available radio network spectrum, finite and important resources, have been severely constrained by the rising demand for wireless applications. It is essential to develop a successful cooperative spectrum sensing (CSS) system for cognitive radio (CR), whose are seen to be a promising solution for improving spectrum usage. A clusters-based optimal selective CSS system is suggested in this paper to shorten reporting times for the bandwidth whiles preserving a given performance by the sensing mode. The clusters have a dynamic head in each selected cluster in accordance with data sensing qualities for CR users in the cognitive radio. Clusters have been arranged based on identifying the major signals to the noise ratio value. Making a decision to use cluster sensing is based on a chosen CSS threshold that minimizes the likelihood of sensing inaccuracy. It takes less time to make the report for the decision of the clusters’ fusion centre is significantly reduced by the Amplify and Forward-based CSS approach that is proposed. The optimal Chair-Varshney rule is applied to the fusion centre for achieving a high sensing performance is depending on the information that is currently available about the cluster. Based on the results availability of simulation, it is clear to propose a way to supersede the other existing methods.

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User sensing based on MIMO cognitive radio sensor networks

Cited by 9 publications

References 9 publications

Performance Analyses of Energy Detection Based on Square-Law Combining in MIMO-OFDM Cognitive Radio Networks

Performance Analyses of Energy Detection Based on Square-Law Combining in MIMO-OFDM Cognitive Radio Networks

Improved Convolutional Neural Network Based Cooperative Spectrum Sensing For Cognitive Radio

Cooperative Spectrum Sensing with Amplify and Forward Scheme in CRNs

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