Wireless-powered communication under statistical quality of service constraints

In this paper, we study the performance of wireless information and power transfer in the presence of statistical queuing constraints. We consider harvest-then-transmit protocol in which users first harvest energy from a dedicated source and then transmit information through an uplink multiple acces...

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Vydáno v:IEEE International Conference on Communications (2003) s. 1 - 6
Hlavní autoři: Zewde, Tewodros A., Gursoy, M. Cenk
Médium: Konferenční příspěvek Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.05.2016
Témata:
Algorithms
Buffer overflow probability
Channels
Decoding
Downlink
Electronics
Energy harvesting
Fading
Fading channels
Intervals
Mathematical models
Optimization
QoS constraints
Quality of service
Throughput
Uplink
Wireless communication
ISSN:1938-1883
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Abstract In this paper, we study the performance of wireless information and power transfer in the presence of statistical queuing constraints. We consider harvest-then-transmit protocol in which users first harvest energy from a dedicated source and then transmit information through an uplink multiple access channel (MAC). Each user is subject to limitations on the buffer overflow probability, specified by the quality of service (QoS) exponent θ, and the optimal time allocation for energy harvesting and information decoding operations depends on these constraints in addition to the channel characteristics. We formulate optimization problems to maximize the throughput with and without QoS constraints. In both cases, the problems are convex, and hence Karush-Kuhn-Tucker (KKT) conditions are necessary and sufficient for global optimality. However, it is difficult to obtain closed-form expressions for optimal time interval since we assume that operating intervals are independent of each fading state realization. Hence, we develop an algorithm to obtain optimal solutions numerically. Simulation results justify that QoS constraints primarily affect achievable rate distribution among the users, and override the channel conditions.
AbstractList In this paper, we study the performance of wireless information and power transfer in the presence of statistical queuing constraints. We consider harvest-then-transmit protocol in which users first harvest energy from a dedicated source and then transmit information through an uplink multiple access channel (MAC). Each user is subject to limitations on the buffer overflow probability, specified by the quality of service (QoS) exponent [thetas], and the optimal time allocation for energy harvesting and information decoding operations depends on these constraints in addition to the channel characteristics. We formulate optimization problems to maximize the throughput with and without QoS constraints. In both cases, the problems are convex, and hence Karush-Kuhn-Tucker (KKT) conditions are necessary and sufficient for global optimality. However, it is difficult to obtain closed-form expressions for optimal time interval since we assume that operating intervals are independent of each fading state realization. Hence, we develop an algorithm to obtain optimal solutions numerically. Simulation results justify that QoS constraints primarily affect achievable rate distribution among the users, and override the channel conditions.
In this paper, we study the performance of wireless information and power transfer in the presence of statistical queuing constraints. We consider harvest-then-transmit protocol in which users first harvest energy from a dedicated source and then transmit information through an uplink multiple access channel (MAC). Each user is subject to limitations on the buffer overflow probability, specified by the quality of service (QoS) exponent θ, and the optimal time allocation for energy harvesting and information decoding operations depends on these constraints in addition to the channel characteristics. We formulate optimization problems to maximize the throughput with and without QoS constraints. In both cases, the problems are convex, and hence Karush-Kuhn-Tucker (KKT) conditions are necessary and sufficient for global optimality. However, it is difficult to obtain closed-form expressions for optimal time interval since we assume that operating intervals are independent of each fading state realization. Hence, we develop an algorithm to obtain optimal solutions numerically. Simulation results justify that QoS constraints primarily affect achievable rate distribution among the users, and override the channel conditions.
Author Gursoy, M. Cenk
Zewde, Tewodros A.
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SubjectTerms Algorithms
Buffer overflow probability
Channels
Decoding
Downlink
Electronics
Energy harvesting
Fading
Fading channels
Intervals
Mathematical models
Optimization
QoS constraints
Quality of service
Throughput
Uplink
Wireless communication
Title Wireless-powered communication under statistical quality of service constraints
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