Browsing by Author "Adachi, Fumiyuki"

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Load-Balancing Spectrum Decision for Cognitive Radio Networks
(2011-04-01)
Wang, Li-Chun
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Wang, Chung-Wei
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Adachi, Fumiyuki
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電機工程學系
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電信工程研究所
In this paper, we present an analytical framework to design system parameters for load-balancing multiuser spectrum decision schemes in cognitive radio (CR) networks. Unlike the non-load-balancing methods that multiple secondary users may contend for the same channel, the considered load-balancing schemes can distribute the traffic loads of secondary users to multiple channels. Based on the preemptive resume priority (PRP) M/G/1 queueing theory, a spectrum decision analytical model is proposed to evaluate the effects of multiple interruptions from the primary user during each link connection, the sensing errors (i.e., missed detection and false alarm) of the secondary users, and the heterogeneous channel capacity. With the objective of minimizing the overall system time of the secondary users, we derive the optimal number of candidate channels and the optimal channel selection probability for the sensing-based and the probability-based spectrum decision schemes, respectively. We find that the probability-based scheme can yield a shorter overall system time compared to the sensing-based scheme when the traffic loads of the secondary users is light, whereas the sensing-based scheme performs better in the condition of heavy traffic loads. If the secondary users can intelligently adopt the best spectrum decision scheme according to sensing time and traffic conditions, the overall system time can be improved by 50% compared to the existing methods.
Modeling and Analysis for Reactive-decision Spectrum Handoff in Cognitive Radio Networks
(2010)
Wang, Chung-Wei
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Wang, Li-Chun
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Adachi, Fumiyuki
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電信工程研究所
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Institute of Communications Engineering
This paper investigates how to characterize the effect of multiple spectrum handoff delay on the extended data delivery time of the secondary users' connections in cognitive radio (CR) networks. Whenever a primary user appears, the spectrum handoff procedures are initiated for the interrupted secondary users. Through spectrum sensing, the secondary user can reactively decide the target channel for spectrum handoff to resume its unfinished transmission. Clearly, many interruptions from the primary users will result in multiple handoffs, thereby increase the extended data delivery time of a secondary connection. In this paper, we develop a Markov transition model integrating with the preemptive resume priority (PRP) M/G/1 queueing network to characterize the multiple handoff delay, resulting from the sensing time, the handshaking time, the channel switching time, and the waiting time. The analytical results can facilitate the designs of admission control rules for the secondary users subject to their latency requirements and provide a framework to determine whether the spectrum sensing technology can effectively shorten the extended data delivery time under various traffic arrival rates and service time as well as sensing time(1).
Modeling and Analysis of Multi-User Spectrum Selection Schemes in Cognitive Radio Networks
(2009)
Wang, Chung-Wei
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Wang, Li-Chun
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Adachi, Fumiyuki
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電信工程研究所
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Institute of Communications Engineering
In this paper, we study the spectrum selection problem in cognitive radio network with emphasis on resolving the channel contention and the spectrum sharing issues of multiple secondary users. For the traditional channel selection methods, the secondary users select their operating channels based on various criteria. However, these methods neglect the effect that multiple secondary users may content for the same channel if they have the same consensus on one particular good channel. Compared to the existing spectrum selection methods, we consider the sensing-based and the probability-based spectrum selection schemes which can prevent too many secondary users from contending the same channel. An analytical model integrated with the preemptive resume priority M/G/1 queuing network theory is developed to evaluate the overall transmission time of the both schemes. Based on this model, we discuss how to find the optimal selection probability for the probability-based scheme. Furthermore, we also analyze in which condition dependent of sensing time and traffic parameters that the sensing-or the probability-based scheme should be used. Based on the analytical results, we provide a principle to guide system operators which scheme should be used in CR networks. Then, we conclude that channel selection scheme should be adaptive to the variations of the traffic characteristics.