• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.141-144
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• 2010

OSA(Opportunistic Spectrum Access) allows secondary users not having a license for spectrum usage to opportunistically occupy an idle spectrum owned by a licensee named primary users. We propose two OSA schemes for un-slotted secondary users exploiting spectrum opportunities in un-slotted primary networks. We provide mathematical analysis and simulation results to reveal the impact of various system parameters.

• East Asian mathematical journal
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• v.27 no.1
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• pp.23-33
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• 2011

Due to underutilization of spectrum under current inefficient and static spectrum management policy, various kinds of opportunistic spectrum access (OSA) strategies have appeared. Myopic policy is a simple and robust OSA strategy with reduced complexity that maximizes immediate throughput. In this paper, we propose mathematical models to evaluate the throughput and the MAC delay of a myopic policy under saturation tra c conditions. Using the MAC delay distribution, we evaluate the packet delay of secondary users under nonsaturation conditions. Numerical results are given to show the performance of the myopic policy in cognitive radio networks.

• 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 Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.162-170
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• 2012

We propose a new priority discipline called the strict T-preemptive priority discipline, and derive the waiting time distributions of each class in the strict T-preemptive priority M/G/1 queue. Using this queueing analysis, we evaluate the performance of an opportunistic spectrum access in cognitive radio networks, where a communication channel is divided into time slots, a licensed primary user is assigned to one channel, and multiple unlicensed secondary users may opportunistically exploit time slots unused by the primary user. We also present a numerical example of the analysis of the opportunistic spectrum access where the arrival rates and service times distributions of each users are identical.

• 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 the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1318-1323
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• 2013

We consider the design of opportunistic spectrum access schemes where secondary users can opportunistically access unused spectrum in non-slotted primary systems. Two non-slotted spectrum sensing and access schemes for secondary users are considered. We present experimental results that demonstrate the performance of the considered schemes.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3867-3886
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• 2015

This article investigates the problem of opportunistic spectrum access in dynamic environment, in which the signal-to-noise ratio (SNR) is time-varying. Different from existing work on continuous feedback, we consider more practical scenarios in which the transmitter receives an Acknowledgment (ACK) if the received SNR is larger than the required threshold, and otherwise a Non-Acknowledgment (NACK). That is, the feedback is discrete. Several applications with different threshold values are also considered in this work. The channel selection problem is formulated as a non-cooperative game, and subsequently it is proved to be a potential game, which has at least one pure strategy Nash equilibrium. Following this, a multi-agent Q-learning algorithm is proposed to converge to Nash equilibria of the game. Furthermore, opportunistic spectrum access with multiple discrete feedbacks is also investigated. Finally, the simulation results verify that the proposed multi-agent Q-learning algorithm is applicable to both situations with binary feedback and multiple discrete feedbacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2675-2690
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• 2014

We study the problem of optimal opportunistic spectrum access with unknown and heterogeneous channel dynamics in cognitive radio networks. There is neither statistic information about the licensed channels nor information exchange among secondary users in the respective systems. We formulate the problem of maximizing network throughput. To achieve the desired optimization, we propose a win-shift lose-stay algorithm based only on rewards. The key point of the algorithm is to make secondary users tend to shift to another channel after receiving rewards from the current channel. The optimality and the convergence of the proposed algorithm are proved. The simulation results show that for both heterogeneous and homogenous systems the proposed win-shift lose-stay algorithm has better performance in terms of throughput and fairness than an existing algorithm.