The HMM-based Modeling for the Energy Level Prediction in Wireless Sensor Networks

Hu, Peng; Zhou, Zude; Liu, Quan; Li, Fangmin

doi:10.1109/iciea.2007.4318812

Cited by 50 publications

(29 citation statements)

References 10 publications

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“…The residual energy state at time slot k is denoted by s E (k). The residual energy is also a Markov chain when relay is active according to the results of [11]. The transition probability is…”

Section: Energy Modelmentioning

confidence: 99%

Distributed Relay Selection and Power Control in Cognitive Radio Networks with Cooperative Transmission

Luo

et al. 2010

2010 IEEE International Conference on Communications

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In this paper, we present a distributed relay selection and power allocation scheme concurrently considering the channel states of all related links and residual energy state of the relay nodes for cooperative transmission in cognitive radio (CR) networks. Specifically, we formulate the CR network with cooperative transmission as a restless bandit system, which has been widely applied in operations research and stochastic control. The channel state and residual energy state are presented by finite state Markov chains. With this stochastic optimization formulation, the optimal policy for relay selection and power allocation is indexable, meaning that the relay with the highest index should be selected. The proposed scheme can achieve the tradeoff between achievable rate and network lifetime. Simulation results are presented to illustrate the performance of the proposed scheme.

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Section: Energy Modelmentioning

confidence: 99%

Distributed Relay Selection and Power Control in Cognitive Radio Networks with Cooperative Transmission

Luo

et al. 2010

2010 IEEE International Conference on Communications

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“…, E H−1 }, where H is the number of available energy state levels. Assume the residual energy realization state to be E n (t) for sender n in time slot t. The authors of [17] model the transition of the energy levels of nodes in wireless networks as the Markov chain. We adopt this model and assume the transition probability matrix to be:…”

Section: B System Modelsmentioning

confidence: 99%

Distributed Multi-Source Transmission in Wireless Mobile Peer-to-Peer Networks: A Restless Bandit Approach

et al. 2009

2009 IEEE International Conference on Communications

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In wireless mobile peer-to-peer (P2P) networks, multiple sources can provide multimedia file sharing at the same time. The selection of multiple sources is one of the key issues in the design of a multi-source transmission system in wireless mobile P2P networks. In this paper, we propose a distributed multi-source sender selection scheme to maximize the receiving data rate and minimize the energy consumption. Our scheme is based on recent advances in restless bandit algorithms. The proposed sender selection scheme has an indexability property that dramatically simplifies the computation and implementation of the policy. In addition, there is no need for a centralized control point, and senders can join and leave from the wireless mobile P2P network freely. Simulation results show that the proposed scheme improves the receiving data rate and energy consumption performance significantly compared to the existing scheme.

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“…Let E n (t) be the residual energy state of R n in time slot t. As discussed in [14], the transition of residual energy levels can be modeled as a Markov chain. We define the energy state transition probability matrix of R n taking action a as Ψ a…”

Section: ) Interference-power Constraintmentioning

confidence: 99%

Energy-efficient cross-layer enhancement of multimedia transmissions over cognitive radio relay networks

Chen

Leung

2011

2011 IEEE Wireless Communications and Networking Conference

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In cognitive radio (CR) networks, cooperative relaying is a promising technology to improve the performance of secondary users (SUs), while ensuring the quality of service (QoS) of primary transmissions. Most previous work in CR relay networks concentrates on maximizing physical layer QoS, e.g., system capacity, as the design criteria. However, the application layer QoS perceived by SUs, such as multimedia distortion, is largely ignored. In this paper, we take a crosslayer design approach to jointly consider optimal relay selection, power allocation, adaptive modulation and coding, as well as intra-refreshing rate to improve multimedia transmissions over underlay CR relay networks, while guaranteeing that the primary link is provided with a minimum-rate for a certain percentage of time. The objective is to minimize multimedia distortion, increase spectral efficiency as well as prolong network lifetime. With this stochastic optimization formulation, the optimal policy has indexability property that dramatically reduces the computation and implementation complexity. Simulation results are presented to show the effectiveness of the proposed scheme.

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The HMM-based Modeling for the Energy Level Prediction in Wireless Sensor Networks

Cited by 50 publications

References 10 publications

Distributed Relay Selection and Power Control in Cognitive Radio Networks with Cooperative Transmission

Distributed Relay Selection and Power Control in Cognitive Radio Networks with Cooperative Transmission

Distributed Multi-Source Transmission in Wireless Mobile Peer-to-Peer Networks: A Restless Bandit Approach

Energy-efficient cross-layer enhancement of multimedia transmissions over cognitive radio relay networks

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