• Journal of Communications and Networks
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• v.16 no.2
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• pp.193-201
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• 2014

In cognitive radio networks, the packet transmissions of the secondary users (SUs) can be interrupted randomly by the primary users (PUs). That is to say, the PU packets have preemptive priority over the SU packets. In order to enhance the quality of service (QoS) for the SUs, we propose a spectrum access strategy with an ${\alpha}$-Retry policy. A buffer is deployed for the SU packets. An interrupted SU packet will return to the buffer with probability ${\alpha}$ for later retrial, or leave the system with probability (1-${\alpha}$). For mathematical analysis, we build a preemptive priority queue and model the spectrum access strategy with an ${\alpha}$-Retry policy as a two-dimensional discrete-time Markov chain (DTMC).We give the transition probability matrix of the Markov chain and obtain the steady-state distribution. Accordingly, we derive the formulas for the blocked rate, the forced dropping rate, the throughput and the average delay of the SU packets. With numerical results, we show the influence of the retrial probability for the strategy proposed in this paper on different performance measures. Finally, based on the trade-off between different performance measures, we construct a cost function and optimize the retrial probabilities with respect to different system parameters by employing an iterative algorithm.

• 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.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.217-226
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• 2014

In this research, we study the problem of opportunistic spectrum access (OSA) in a time-varying environment with fading channels, where the channel state is characterized by both channel quality and the occupancy of primary users (PUs). First, a finite-state Markov channel model is introduced to represent a fading channel. Second, by probing channel quality and exploring the activities of PUs jointly, a two-dimensional partially observable Markov decision process framework is proposed for OSA. In addition, a greedy strategy is designed, where a secondary user selects a channel that has the best-expected data transmission rate to maximize the instantaneous reward in the current slot. Compared with the optimal strategy that considers future reward, the greedy strategy brings low complexity and relatively ideal performance. Meanwhile, the spectrum sensing error that causes the collision between a PU and a secondary user (SU) is also discussed. Furthermore, we analyze the multiuser situation in which the proposed single-user strategy is adopted by every SU compared with the previous one. By observing the simulation results, the proposed strategy attains a larger throughput than the previous works under various parameter configurations.

• 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.

• ETRI Journal
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• v.45 no.5
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• pp.874-886
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• 2023

A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.449-462
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• 2014

As mobile traffic is growing, the demand for spectrum is increasing but the deficiency of spectrum becomes serious as the supply is restricted essentially. For resolving the issue, spectrum sharing system is discussed from the technical and regulatory point of view, where multiple radio users occupy same frequency. In this paper, the policies and adoptions of spectrum sharing system in some countries are analyzed with a focus on TV white space and licensed shared access, which are based on unlicensed and licensed spectrum usage respectively. Some legal and regulatory plans to adopt and activate spectrum sharing in the Radio Waves Act system of Korea are proposed as well.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.340-350
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• 2016

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

• 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.9 no.1
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• pp.34-49
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• 2015

Market means of spectrum trading have been utilized as a vital method of spectrum sharing and access in future cognitive radio system. In this paper, we consider the spectrum trading with multiple primary carrier providers (PCP) leasing the spectrum to multiple secondary carrier providers (SCP) for a short period of time. Several factors including the price of the resource, duration of leasing, and the spectrum quality guides the proposed model. We formulate three trading policies based on the game theory for dynamic spectrum access in a LTE based cognitive radio system (CRS). In the first, we consider utility function based resource sharing (UFRS) without any knowledge of past transaction. In the second policy, each SCP deals with PCP using a non-cooperative resource sharing (NCRS) method which employs optimal strategy based on reinforcement learning. In variation of second policy, third policy adopts a Nash bargaining while incorporating a recommendation entity in resource sharing (RERS). The simulation results suggest overall increase in throughput while maintaining higher spectrum efficiency and fairness.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.140-145
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• 2014

In this paper, we propose an anti-interference cooperative spectrum sharing strategy for cognitive system, in which a secondary system can operate on the same spectrum of a primary system. Specifically, the primary system leases a fraction of its transmission time to the secondary system in exchange for cooperation to achieve the target rate. To gain access to the spectrum of the primary system, the secondary system needs to allocate a fraction of bandwidth to help forward the primary signal. As a reward, the secondary system can use the remaining bandwidth to transmit its own signal. The secondary system uses different bandwidth to transmit the primary and its own signal. Thus, there will be no interference felt at primary and secondary systems. We study the joint optimization of time and bandwidth allocation such that the transmission rate of the secondary system is maximized, while guaranteeing the primary system, as a higher priority, to achieve its target transmission rate. Numerical results show that the secondary system can gain significant improvement with the proposed strategy.