• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.821-827
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• 2014

Many researches on the usage of shared spectrum have continuously been carried out to solve the recent frequency shortage problem and to use efficiently the spectrum without interference. Also, exponential mobile data growth and the solutions needed to address this challenge are parallel key objectives addressed in many countries. Spectrum policy innovation to meet this challenge is the ASA/LSA (Authorized Shared Access/Licensed Shared Access), which is the best access model to employ the small cell technology to meet this mobile traffic growth. Because 3.5 GHz bands is considered as the ASA/LSA frequency, in this paper, we propose the SAM(Spectrum Access Model) in 3~4 GHz bands to estimate the available ASA/LSA bands and to open more free spectrum. These results are utilized as the data to develop the SAM for the small cell and the open frequency in future.

• East Asian mathematical journal
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• v.30 no.1
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• pp.23-29
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• 2014

To solve inefficient spectrum usage problem under current static spectrum management policy, various kinds of dynamic spectrum access strategies have appeared. Myopic policy, which maximizes immediate throughput, is a simple and robust strategy with reduced complexity. In this paper, we present a simple mathematical model to evaluate the saturation throughput and medium access delay of a myopic policy in the presence of multiple channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1489-1503
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• 2018

Spectrum reuse has attracted much concern of researchers and scientists, however, the dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that spectrum usage forecasting among secondary users, this inspiration enables users to obtain more informed spectrum opportunities. Therefore, spectrum usage forecasting is vital to cognitive radio networks (CRNs). With this insight, a spectrum usage forecasting model for the occurrence of primary users prediction is derived in this paper. The proposed model is based on auto regressive enhanced primary user emergence reasoning (AR-PUER), which combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the spectrum usage forecasting model in order to capture the current distinction pattern of primary users. The proposed scheme does not require the knowledge of signal or of noise power. To verify the performance of proposed spectrum usage forecasting model, we apply it to the data during the past two months, and then compare it with some other sensing techniques. The simulation results demonstrate that the spectrum usage forecasting model is effective and generates the most accurate prediction of primary users occasion in several cases.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.222-227
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• 2013

This paper presents an analytical framework for dynamic spectrum allocation in cognitive radio networks. We propose a distributed queuing based Markovian model each for single channel and multiple channels access for a contending user. Knowledge about spectrum mobility is one of the most challenging problems in both these setups. To solve this, we consider probabilistic channel availability in case of licensed channel detection for single channel allocation, while variable data rates are considered using channel aggregation technique in the multiple channel access model. These models are designed for a centralized architecture to enable dynamic spectrum allocation and are compared on the basis of access latency and service duration.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1295-1302
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• 2011

We present an analytic model of an unslotted opportunistic spectrum access (OSA) network and evaluate its performance such as interruption probability, service completion time, and throughput of secondary users. Numerical examples are given to show the performance of secondary users in cognitive networks. The developed modeling and analysis method can be used to evaluate the performance of various OSA networks.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.40-44
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• 2010

opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. A dynamical sensing range as a important parameter introduced to maintain the our protocol performance. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.

• ETRI Journal
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• v.34 no.2
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• pp.276-279
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• 2012

In this letter, a modified 802.11-based opportunistic spectrum access is proposed for single-channel cognitive radio networks where primary users operate on a slot-by-slot basis. In our opportunistic spectrum access, control frames are used to reduce the slot-boundary impact and achieve channel reservation to improve throughput of secondary users. An absorbing Markov chain model is used to analyze the throughput of secondary users. Simulation results show that the analysis accurately predicts the saturation throughput.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2663-2674
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• 2014

For cognitive radio sensor networks (CRSNs) that use underlay-based spectrum access, the location of the primary user (PU) plays an important role in the power control of the secondary users (SUs), because the SUs must keep the minimum interference level required by the PU. Received signal strength (RSS)-based localization schemes provide low-cost implementation and low complexity, thus it is suitable for the PU localization in CRSNs. However, the RSS-based localization schemes have a high localization error because they use an inexact path loss exponent (PLE). Thus, applying a RSS-based localization scheme into the PU localization would cause a high interference to the PU. In order to reduce the localization error and improve the channel reuse rate, we propose a RSS-based PU localization scheme that uses distance calibration for CRSNs using underlay model-based spectrum access. Through the simulation results, it is shown that the proposed scheme can provide less localization error as well as more spectrum utilization than the RSS-based PU localization using the mean and the maximum likelihood calibration.