Amplitude quantization method for autonomous threshold estimation in self-reconfigurable cognitive radio systems

Onumanyi, A. J.; Abu‐Mahfouz, Adnan M.; Hancke, Gerhard P.

doi:10.1016/j.phycom.2020.101256

Cited by 10 publications

(10 citation statements)

References 39 publications

(80 reference statements)

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“…The work [14] proposed adaptive algorithms for adjusting the threshold values of parameters of radio communication systems. This research allows you to distinguish a useful signal against the background of noise, adapt to the signal environment.…”

Section: Tablementioning

confidence: 99%

Improvement of complex resource management of special-purpose communication systems

Koval

Sova

Orlov

et al. 2022

EEJET

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The object of the research is a special-purpose communication system. The relevance of the research lies in the need for complex management of resources of special-purpose communication systems. The resources of the special-purpose communication system are defined as: spatial, temporal, frequency and hardware resources. Destabilizing factors include: intentional interference; denial-of-service cyber attacks and fire damage to individual elements of the special-purpose communication system. The method of complex management of resources of special-purpose communication systems was improved. The difference between the proposed method and the known ones is that the specified method contains improved procedures: ‒ determination of the impact of destabilizing factors on the special-purpose communication system; ‒ description of special-purpose communication systems of various architectures; ‒ determination of the rational route of information transmission and operation mode of communication devices in the general special-purpose communication system; ‒ consideration of uncertainty about the state of the special-purpose communication system; ‒ determination of the number of necessary forces and means of communication, which must be increased for the full functioning of the special communication system. The improved method provides a gain of 20‒26 % compared to classical approaches to the management of resources of special-purpose communication systems. The improved method can be used at the control points of the communication system of groups of troops (forces) while planning the organization of communication and at the stage of operational management of the communication system.

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Section: Tablementioning

confidence: 99%

Improvement of complex resource management of special-purpose communication systems

Koval

Sova

Orlov

et al. 2022

EEJET

View full text Add to dashboard Cite

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“…The paper [13] proposes adaptive algorithms for adjusting the threshold values of radio communication system parameters. The specified research allows allocating a useful signal against noise, adapting to a signal situation.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…The analysis of the works [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16] allows us to state that the existing scientific achievements do not allow for a through management of channel and network resources of military radio networks, but only separate control influences at a separate level of the open systems interconnection model. All this does not allow using available radio resources of military radio networks effectively and counteracting comprehensively destabilizing factors that affect the efficiency of military radio networks.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…In addition, most users today need not only routes with the fewest hops to the destination, but also routes that can meet other important needs. Such users often need to provide support for QoS [19,20] and to be able to take into account the energy component [13,15,[21][22][23][24] due to the fact that in special-purpose networks there may be a significant number of nodes running on batteries, taking into account the speed of the communication channel, the delay time between the sender of the packet and its recipient, the number of available routes and the reliability of packet delivery by the appropriate route.…”

Section: Development Of An Algorithm For Adaptive Control Of Militarymentioning

confidence: 99%

“…According to [13][14][15][16]21], the importance of REE indicators can be considered as a non-metric criterion of usefulness (NCU).…”

mentioning

confidence: 99%

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Development of a method of adaptive control of military radio network parameters

Nalapko

Shyshatskyi

Ostapchuk

et al. 2021

EEJET

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A method of adaptive control of military radio network parameters has been developed. This method allows predicting suppressed frequencies by electronic warfare devices, determining the topology of the military radio network. Also, this method allows determining rational routes of information transmission and operating mode of radio communications. Forecasting of the electronic environment is characterized by recirculation of input data for one count, resampling on a logarithmic time scale, finding a forecast for the maximum value of entropy and resampling the forecast on the exponential time scale. The developed method allows choosing a rational network topology. The choice of topology of the military radio communication system is based on the method of ant multi-colony system. The main idea of the new option of ant colony optimization is that instead of one colony of the traditional ant algorithm several colonies are used that work together in a common search space. However, this procedure additionally takes into account the type of a priori uncertainty and the evaporation coefficient of the pheromone level. The proposed method allows choosing a rational route for information transmission. The proposed procedure is based on an improved DSR algorithm. This method uses several operating modes of radio communications, namely the technology of multi-antenna systems with noise-like signals, with pseudo-random adjustment of the operating frequency and with orthogonal frequency multiplexing. The developed method provides a gain of 10‒16 % compared to conventional management approaches

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Arithmetic Optimization Algorithm Quantization Optimized With Energy Detection Using Nonparametric Amplitude

T M

et al. 2024

Int J Communication

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The spectrum sensing is a major significant task in cognitive radio networks (CRNs) to avoid the unacceptable interference to primary users (PUs). Here, the threshold value determines the effectiveness of spectrum sensing and regarded as a sensing system. The fixed threshold used by the current energy detection‐based spectrum sensing (SS) techniques does not provide sufficient safety for the main users. The threshold is determined by lowering the complete probability of decision error in addition to these guidelines. Therefore, an energy detection using nonparametric amplitude quantization optimized with arithmetic optimization algorithm for enhanced spectrum sensing in CRNs (ED‐NAQ‐AOA‐SS CRN) is proposed in this paper to acquire the ideal threshold for decreasing the total error probability. The proposed method achieves greater probability of detection of 99.67%, 98.38%, 92.34%, and 97.45%, lower settling time of 98.33%, 89.34%, 83.12%, and 88.96%, and lower error rate of 93.15%, 91.25%, 79.90%, and 92.88% compared with existing techniques, like intelligent spectrum sharing and sensing in CRN with adaptive rider optimization algorithm (AROA), a novel technique for spectrum sensing in CRN utilizing fractional gray wolf optimization with the cuckoo search optimization (GWOCS), and adaptive neuro‐fuzzy inference scheme depending on cooperative spectrum sensing optimization in CRNs (ANFIS).

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Amplitude quantization method for autonomous threshold estimation in self-reconfigurable cognitive radio systems

Cited by 10 publications

References 39 publications

Improvement of complex resource management of special-purpose communication systems

Improvement of complex resource management of special-purpose communication systems

Development of a method of adaptive control of military radio network parameters

Arithmetic Optimization Algorithm Quantization Optimized With Energy Detection Using Nonparametric Amplitude

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