The Experts below are selected from a list of 99174 Experts worldwide ranked by ideXlab platform
Ayfer Ozgur - One of the best experts on this subject based on the ideXlab platform.
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capacity of the Energy Harvesting gaussian mac
IEEE Transactions on Information Theory, 2018Co-Authors: Huseyin A Inan, Dor Shaviv, Ayfer OzgurAbstract:We consider an Energy Harvesting multiple access channel (MAC) where the transmitters are powered by an exogenous stochastic Energy Harvesting process and equipped with finite batteries. We characterize the capacity region of this channel as $n$ -letter mutual information rate and develop inner and outer bounds that differ by a constant gap. An interesting conclusion that emerges from our results is that the sum-capacity approaches that of a standard additive white Gaussian noise MAC (with only an average constraint on the transmitted power), as the number of users in the MAC becomes large.
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capacity of the Energy Harvesting gaussian mac
arXiv: Information Theory, 2016Co-Authors: Huseyin A Inan, Dor Shaviv, Ayfer OzgurAbstract:We consider an Energy Harvesting multiple access channel (MAC) where the transmitters are powered by an exogenous stochastic Energy Harvesting process and equipped with finite batteries. We characterize the capacity region of this channel as n-letter mutual information rate and develop inner and outer bounds that differ by a constant gap. An interesting conclusion that emerges from our results is that the sum-capacity approaches that of a standard AWGN MAC (with only an average constraint on the transmitted power), as the number of users in the MAC becomes large.
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capacity of the Energy Harvesting gaussian mac
International Symposium on Information Theory, 2016Co-Authors: Huseyin A Inan, Dor Shaviv, Ayfer OzgurAbstract:We consider an Energy Harvesting multiple access channel where the transmitters are powered by an exogenous stochastic Energy Harvesting process and equipped with finite batteries. We characterize the capacity region of this channel as n-letter mutual information rate and develop inner and outer bounds that differ by a constant gap. An interesting conclusion that emerges from our results is that in a symmetric system, where transmitters are statistically equivalent to each other, the largest achievable common rate point approaches that of a standard AWGN MAC with an average power constraint, as the number of users in the MAC becomes large.
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online power control for the Energy Harvesting multiple access channel
Modeling and Optimization in Mobile Ad-Hoc and Wireless Networks, 2016Co-Authors: Huseyin A Inan, Ayfer OzgurAbstract:We consider online power control for a K-user Energy Harvesting multiple-access channel (MAC). We show that a simple online power control policy that requires each user to know only the mean of its own Energy Harvesting process and does not require any information regarding the Energy Harvesting processes of the other users is near optimal for any joint distribution of the Energy Harvesting processes and for arbitrary battery sizes at the K users. In particular, for any parameter values this strategy achieves a throughput region which is within a constant gap to the capacity region of the classical additive white Gaussian noise (AWGN) MAC. When the number of users in the MAC becomes large, the gap becomes negligible. Therefore, an interesting consequence of our result is that in the limit when the number of users becomes large, the sum throughput of the online Energy Harvesting MAC approaches the sum capacity of the classical AWGN MAC. While it has been known that the online throughput of an Energy Harvesting system can approach the AWGN capacity in the limit when the battery size goes to infinity, it is interesting that the AWGN capacity can be also approached in limit of large number of users.
Sennur Ulukus - One of the best experts on this subject based on the ideXlab platform.
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Energy Harvesting Wireless Communications: A Review of Recent Advances
IEEE Journal on Selected Areas in Communications, 2015Co-Authors: Sennur Ulukus, Michele Zorzi, Pulkit Grover, Aylin Yener, Elza Erkip, Osvaldo Simeone, Kaibin HuangAbstract:This paper summarizes recent contributions in the broad area of Energy Harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of Energy Harvesting nodes, starting from the information-theoretic performance limits to transmission schedul-ing policies and resource allocation, medium access, and net-working issues. The emerging related area of Energy transfer for self-sustaining Energy Harvesting wireless networks is considered in detail covering both Energy cooperation aspects and simulta-neous Energy and information transfer. Various potential models with Energy Harvesting nodes at different network scales are re-viewed, as well as models for Energy consumption at the nodes.
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Energy cooperation in Energy Harvesting communications
IEEE Transactions on Communications, 2013Co-Authors: Berk Gurakan, Omur Ozel, Jing Yang, Sennur UlukusAbstract:In Energy Harvesting communications, users transmit messages using Energy harvested from nature during the course of communication. With an optimum transmit policy, the performance of the system depends only on the Energy arrival profiles. In this paper, we introduce the concept of Energy cooperation, where a user wirelessly transmits a portion of its Energy to another Energy Harvesting user. This enables shaping and optimization of the Energy arrivals at the Energy-receiving node, and improves the overall system performance, despite the loss incurred in Energy transfer. We consider several basic multi-user network structures with Energy Harvesting and wireless Energy transfer capabilities: relay channel, two-way channel and multiple access channel. We determine Energy management policies that maximize the system throughput within a given duration using a Lagrangian formulation and the resulting KKT optimality conditions. We develop a two-dimensional directional water-filling algorithm which optimally controls the flow of harvested Energy in two dimensions: in time (from past to future) and among users (from Energy-transferring to Energy-receiving) and show that a generalized version of this algorithm achieves the boundary of the capacity region of the two-way channel.
Faisal Karim Shaikh - One of the best experts on this subject based on the ideXlab platform.
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Energy Harvesting in wireless sensor networks a comprehensive review
Renewable & Sustainable Energy Reviews, 2016Co-Authors: Faisal Karim Shaikh, Sherali ZeadallyAbstract:Recently, Wireless Sensor Networks (WSNs) have attracted lot of attention due to their pervasive nature and their wide deployment in Internet of Things, Cyber Physical Systems, and other emerging areas. The limited Energy associated with WSNs is a major bottleneck of WSN technologies. To overcome this major limitation, the design and development of efficient and high performance Energy Harvesting systems for WSN environments are being explored. We present a comprehensive taxonomy of the various Energy Harvesting sources that can be used by WSNs. We also discuss various recently proposed Energy prediction models that have the potential to maximize the Energy harvested in WSNs. Finally, we identify some of the challenges that still need to be addressed to develop cost-effective, efficient, and reliable Energy Harvesting systems for the WSN environment.
Kaibin Huang - One of the best experts on this subject based on the ideXlab platform.
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Energy Harvesting Wireless Communications: A Review of Recent Advances
IEEE Journal on Selected Areas in Communications, 2015Co-Authors: Sennur Ulukus, Michele Zorzi, Pulkit Grover, Aylin Yener, Elza Erkip, Osvaldo Simeone, Kaibin HuangAbstract:This paper summarizes recent contributions in the broad area of Energy Harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of Energy Harvesting nodes, starting from the information-theoretic performance limits to transmission schedul-ing policies and resource allocation, medium access, and net-working issues. The emerging related area of Energy transfer for self-sustaining Energy Harvesting wireless networks is considered in detail covering both Energy cooperation aspects and simulta-neous Energy and information transfer. Various potential models with Energy Harvesting nodes at different network scales are re-viewed, as well as models for Energy consumption at the nodes.
Sherali Zeadally - One of the best experts on this subject based on the ideXlab platform.
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Energy Harvesting in wireless sensor networks a comprehensive review
Renewable & Sustainable Energy Reviews, 2016Co-Authors: Faisal Karim Shaikh, Sherali ZeadallyAbstract:Recently, Wireless Sensor Networks (WSNs) have attracted lot of attention due to their pervasive nature and their wide deployment in Internet of Things, Cyber Physical Systems, and other emerging areas. The limited Energy associated with WSNs is a major bottleneck of WSN technologies. To overcome this major limitation, the design and development of efficient and high performance Energy Harvesting systems for WSN environments are being explored. We present a comprehensive taxonomy of the various Energy Harvesting sources that can be used by WSNs. We also discuss various recently proposed Energy prediction models that have the potential to maximize the Energy harvested in WSNs. Finally, we identify some of the challenges that still need to be addressed to develop cost-effective, efficient, and reliable Energy Harvesting systems for the WSN environment.
