• Journal of Satellite, Information and Communications
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• v.4 no.2
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• pp.5-11
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• 2009

In this paper, we propose our design of adaptive resource allocation in the cognitive radio network assisted by satellite to improve the performance of Cognitive Radio user. Most of today’s telecommunication network operates in a fixed, licensed frequency band using a specific spectrum access network. However, the spectrum is not always used all the time, all the band. It causes the inefficiency in the spectrum usage. Thus, cognitive radio network is proposed to solve these spectrum inefficiency problems. The cognitive radio users (secondary users) are coexistent with primary users (PUs) who are licensed. That cognitive radio network is considered as lower priority comparing with primary user. So, the operation of the cognitive radio network is limited to interference constraints. Especially, when the number of secondary users increases, CCI among SUs will increase as well as interference to PU. That motivates our objective to improve the performance even if cognitive radio users increase. To solve this problem, we suggest an adaptive resource allocation scheme to improve the performance of cognitive radio network assisted by satellite. Through this algorithm, we can improve the cognitive radio network performance. And the simulation results confirm the effectiveness of our proposed algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.11-18
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• 2012

Smart Dynamic Pricing has been introduced to address the under-utilised network resources problem in mobile telecommunications systems. In this paper, we investigate the applicability of Smart Dynamic Pricing and its signalling models into Cognitive Radio Systems. Cognitive Radio System is defined as one in which cognitive radios are employed to access shared spectrum and/or dynamically allocated spectrum. Network elements, protocols, traffic and control channels, and system architecture are proposed for the implementation of Smart Dynamic Pricing in Cognitive Radio System. It is found that Smart Dynamic Pricing and its signalling models can be applied to Cognitive Radio Systems.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2128-2147
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• 2021

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.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.201-207
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• 2009

Recently effective spectrum resource technologies have been studied using a game theorectical approach for cognitive radio networks. Radio resource management is required an effective scheme because the performance of a radio communication system much depends on it's effectiveness. In this paper, we suggest a game theoretical algorithm for adaptive power control which is required an effect scheme in cognitive radio networks. It will be a distributed network. In the network distributed cognitive radio secondary users require an adaptive power control. There are many results which are suggested some possibility of game theoretical approaches for communication resource sharing. However, we suggest a practical game algorithm to achieve Nash equilibrium of all secondary users using a Nash equilibrium theorem in this paper. Particularly, a game model was analyzed for adaptive power control of a cognitive radio network, which is involved in DSSS (Direct Sequence Spread Spectrum) techniques. In case of K=63 and N=12 in the DSSS network, the number of iteration was less than maximum 200 using the suggested algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.206-209
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• 2014

Control message exchange is major job for cognitive radio to exist and use spectrum opportunistically. For this control message exchange they need a common control channel (CCC). Once this channel is affected by a primary user, communication stops until new CCC is setup. This takes substantial time and if they could not get free channel, this halt continues for long time. To prevent such cease of communication, we propose a combination of two networks, namely WLAN and UWB, to let the communication continue. In our proposed idea if the CCC of a certain CR in WLAN is affected, the CR changes its network from WLAN to UWB and keeps the communication because UWB cannot be affected by PU. In the proposed idea every cognitive radio has two transceivers; one for the overlay network (WLAN) and another UWB network. If a primary user is detected in the spectrum of a cognitive radio, it continues exchanging control messages under the UWB network and in parallel negotiates for a new CCC using the WLAN network. This idea solves the communication interruption until new CCC is setup.

• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.221-227
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• 2015

Spectrum sensing plays an essential role in a cognitive radio network, which enables opportunistic access to an underutilized licensed spectrum. In conventional cooperative spectrum sensing (CSS), all cognitive users (CUs) in the network spend the same amount of time on spectrum sensing and waste time in remaining silent when other CUs report their sensing results to the fusion center. This problem is solved by the superposition cooperative spectrum sensing (SPCSS) scheme, where the sensing time of a CU is extended to the reporting time of the other CUs. Subsequently, SPCSS assigns the CUs different sensing times and thus affects both the sensing performance and the throughput of the system. In this paper, we propose an algorithm to determine the optimal sensing time of each CU for SPCSS that maximizes the achieved system throughput. The simulation results prove that the proposed scheme can significantly improve the throughput of the cognitive radio network compared with the conventional CSS.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1767-1769
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• 2011

In a CR (cognitive radio) network, channel selection is one of the important issues for the efficient channel utilization. When the CR user exploits the spectrum of primary network, the interference to the primary network should be minimized. In this paper, we propose a spectrum hole prediction based channel selection scheme to minimize the interference to the primary network. To predict spectrum hole, statistic properties of primary user's traffic is used. By using the predicted spectrum hole, channel is selected and it can reduce the possibility of interference to the primary user and increase the efficiency of spectrum utilization. The performance of proposed channel selection scheme is evaluated by the computer simulation.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.297-299
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• 2012

In this paper, we introduce a joint flow control and scheduling algorithm for multi-hop cognitive radio networks with spectrum underlay. Our proposed algorithm maximizes the total utility of secondary users while stabilizing the cognitive radio network and still satisfies the total interference from secondary users to primary network is less than an accepted level. Based on Lyapunov optimization technique, we show that our scheme is arbitrarily close to the optimal.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.13-26
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• 2023

Recently, the development of wireless network technologies has been advancing in several directions: increasing data transmission speed, enhancing user mobility, expanding the range of services offered, improving the utilization of the radio frequency spectrum, and enhancing the intelligence of network and subscriber equipment. In this research, a series of contradictions has emerged in the field of wireless network technologies, with the most acute being the contradiction between the growing demand for wireless communication services (on operational frequencies) and natural limitations of frequency resources, in addition to the contradiction between the expansions of the spectrum of services offered by wireless networks, increased quality requirements, and the use of traditional (outdated) management technologies. One effective method for resolving these contradictions is the application of artificial intelligence elements in wireless telecommunication systems. Thus, the development of technologies for building intelligent (cognitive) radio and cognitive wireless networks is a technological imperative of our time. The functions of artificial intelligence in prospective wireless systems and networks can be implemented in various ways. One of the modern approaches to implementing artificial intelligence functions in cognitive wireless network systems is the application of fuzzy logic and fuzzy processors. In this regard, the work focused on exploring the application of fuzzy logic in prospective cognitive wireless systems is considered relevant.