• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.415-420
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• 2014

Another crucial issue is a providing secondary user(SU) with the its guaranteed quality of service(QoS) in cognitive radio systems, from the SU view to be allowed to opportunistically utilize the primary user(PU) spectrum on non-interfering. In this paper, we propose a bandwidth reallocation scheme for reducing SU dropping rate through renegotiation of requested channel numbers when available bandwidth is not enough for accepting the spectrum handoff SUs. We categorize SU calls into two types : the first priority and the second priority SU, and the first SU' service is supported by bandwidth reservation based on ARMA prediction model for PU arrivals, while the second SU's bandwidth demands for spectrum handoff is to be reallocated through their renegotiation. Simulation results show that our scheme can improve SU dropping rate and system resource utilization efficiency by bandwidth reallocation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1333-1343
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• 2016

Spectrum sharing in centrally controlled cognitive radio (CR) networks has been widely studied, however, research on channel access for distributively controlled individual cognitive users has not been fully characterized. This paper conducts an analysis of random channel access of cognitive users controlled in a distributed manner in a CR network. Based on the proposed estimation method, each cognitive user can estimate the current channel condition by using its own Markov-chain model and can compute its own blocking probability, collision probability, and forced termination probability. Using the proposed scheme, CR with distributed control (CR-DC), CR devices can make self-controlled decisions based on the status estimations to adaptively control its system parameters to communicate better.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1324-1343
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• 2014

In recent years, the problem of spectrum mobility in Cognitive Radio (CR) Networks has been widely investigated. In order to utilize spectrum resources completely, many spectrum handoff techniques based on game theory have been proposed, but most studies only concern that users how to achieve better payoffs, without much attention to the diverse needs of users. In this paper, we propose a new channel-switching model based on game theory, using a prioritized approach to meet the diverse needs of users in two different modes (CQ and PS). At the same time, this paper proposes some acceleration techniques to reach the Nash equilibrium more efficiently. We evaluate the performance of the proposed schemes depending on priority using real channel availability measurements, and conclude that the channel quality function (CQ) mode provide better service for priority user but the plan-sorting (PS) mode can be more suitable in multiple priority users exist scene.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.364-369
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• 2009

Today, as various access technologies appear, for example WiMax, WiBro, the demand for spectrum is increasing rapidly. Spectrums are a national resource with scarcity value so that we need to a]locate them effectively for the national economy and industry. Accordingly, In the paper, we proposed several factors and new model for estimating spectrum requirements of a next generation mobile network with multimedia data services. These are self-similarity characteristics of data traffic, engineered capacity considering QoS, structure of FA increase, asymmetry of data traffic between uplink and downlink, handoff traffic, and uneven traffic pattern among base stations. It can applied mobile WiMax or other wireless broadband systems in general.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.922-929
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• 2005

This paper proposes an adaptive pilot beacon equipment for mobile communication systems based on direct spread spectrum technology which generates the pilot channel for handoff between base stations by using the information acquired from the downstream wireless signal regarding the overhead channel information. Such an adaptive pilot beacon equipment will enable low power operation since among the wireless signals, only the pilot channel will be generated and transmitted. The pilot channel in the downstream link of the CDMA receiver is used to acquire time and frequency synchronization and this is used to calibrate the offset for the beacon, which implies that time synchronization using GPS is not required and any location where forward receive signal can be received can be used as the installation site. The downstream link pilot signal searching within the CDMA receiver is performed by FPGA and DSP. The FPGA is used to perform the initial synchronization for the pilot searcher and DSP is used to perform the offset correction between beacon clock and base station clock. The CDMA transmitter the adaptive pilot beacon equipment will use the timing offset information in the pilot channel acquired from the CDMA receiver and generate the downstream link pilot signal synchronized to the base station. The intermediate frequency signal is passed through the FIR filter and subsequently upconverted and amplified before being radiated through the antenna.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.757-763
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• 2011

This paper presents a channel reservation scheme using Wiener prediction model in order to reduce the rate of forced termination of cognitive users in cognitive radio networks. The proposed method uses Wiener prediction model to predict the number of radio channel required by the reappearance of primary users, and then calculates and reserves the number of channels that cognitive users demand for their spectrum handoff. Through the simulation we investigate cognitive users' forced termination rate and blocking rate with and without channel reservation. In addition we show the bandwidth utilization efficiency for both cases. The results show that the proposed scheme can reduce the forced termination rate of cognitive users at the cost of slightly increasing in blocking rate. Also it is seen that there is little difference in bandwidth utilization efficiency for both cases.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.435-441
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• 2013

This paper proposes a neural net based-predictive connection admission control (CAC) scheme for multiclass users in wireless cognitive radio networks. We classifies cognitive users(cu) into real and non real time services, and then permit only real time services to reserve the demanded resource for spectrum handoff in guard channel for provisioning the desired QoS. Neural net is employed to predict primary user's arrival on time and demanded channels. Resource scheduling scheme is based on $C_IA$(cognitive user I complete access) shown in this paper. For keeping primary users from interference, the CAC is performed on only cognitive user not primary user. Simulation results show that our schemes can guarantee the desired QoS by cognitive real time services.