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Power allocation algorithm for an energy-harvesting wireless transmission system considering energy losses. (English) Zbl 1461.94002

Summary: For an energy-harvesting wireless transmission system, considering that a transmitter which can harvest energy from nature has two kinds of extra energy consumption, circuit consumption and storage losses, the optimization models are set up in this paper for the purpose of maximizing the average throughput of the system within a certain period of time for both a time-invariant channel and time-varying channel. Convex optimization methods such as the Lagrange multiplier method and the KKT (Karush-Kuhn-Tucker) condition are used to solve the optimization problem; then, an optimal offline power allocation algorithm which has a three-threshold structure is proposed. In the three-threshold algorithm, two thresholds can be achieved by using a linear search method while the third threshold is calculated according to the channel state information and energy losses; then, the offline power allocation is based on the three thresholds and energy arrivals. Furthermore, inspired by the optimal offline algorithm, a low-complexity online algorithm with adaptive thresholds is derived. Finally, the simulation results show that the offline power allocation algorithms proposed in this paper are better than other algorithms, the performance of the online algorithm proposed is close to the offline one, and these algorithms can help improve the average throughput of the system.

MSC:

94A05 Communication theory
68W27 Online algorithms; streaming algorithms
68W40 Analysis of algorithms
90B18 Communication networks in operations research
94A40 Channel models (including quantum) in information and communication theory
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References:

[1] Wu, J.; Thompson, J.; Zhang, H.; Kilper, D.C.; Green Communications and Computing Networks; Commun. Mag. IEEE: 2016; Volume 52 ,102-103.
[2] Guan, L.; Zhu, A.; Green Communications: Digital Predistortion for Wideband RF Power Amplifiers; IEEE Microw. Mag.: 2014; Volume 15 ,84-99.
[3] Jing, Y.; Ulukus, S.; Optimal Packet Scheduling in an Energy Harvesting Communication System; IEEE Trans. Commun.: 2012; Volume 60 ,220-230.
[4] Tutuncuoglu, K.; Yener, A.; Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes; IEEE Trans. Wirel. Commun.: 2012; Volume 11 ,1180-1189.
[5] Sharma, V.; Mukherji, U.; Joseph, V.; Gupta, S.; Optimal Energy Management Policies for Energy Harvesting Sensor Nodes; IEEE Trans. Wirel. Commun.: 2008; Volume 9 ,1326-1336.
[6] Ozel, O.; Tutuncuoglu, K.; Yang, J.; Ulukus, S.; Yener, A.; Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies; IEEE J. Sel. Areas Commun.: 2011; Volume 29 ,1732-1743.
[7] Ho, C.K.; Zhang, R.; Optimal Energy Allocation for Wireless Communications with Energy Harvesting Constraints; IEEE Trans. Signal Process.: 2012; Volume 60 ,4808-4818. · Zbl 1393.94822
[8] He, P.; Zhao, L.; Zhou, S.; Niu, Z.; Recursive Waterfilling for Wireless Links with Energy Harvesting Transmitters; IEEE Trans. Veh. Technol.: 2014; Volume 63 ,1232-1241.
[9] Devillers, B.; Gündüz, D.; A general framework for the optimization of energy harvesting communication systems with battery imperfections; J. Commun. Netw.: 2012; Volume 14 ,130-139.
[10] Xu, J.; Zhang, R.; Throughput Optimal Policies for Energy Harvesting Wireless Transmitters with Non-Ideal Circuit Power; IEEE J. Sel. Areas Commun.: 2014; Volume 32 ,322-332.
[11] Wang, X.; Nan, Z.; Chen, T.; Optimal MIMO Broadcasting for Energy Harvesting Transmitter With non-Ideal Circuit Power Consumption; IEEE Trans. Wirel. Commun.: 2015; Volume 14 ,2500-2512.
[12] Orhan, O.; Gunduz, D.; Erkip, E.; Energy Harvesting Broadband Communication Systems with Processing Energy Cost; IEEE Trans. Wirel. Commun.: 2013; Volume 13 ,6095-6107.
[13] Tutuncuoglu, K.; Yener, A.; Ulukus, S.; Optimum Policies for an Energy Harvesting Transmitter under Energy Storage Losses; IEEE J. Sel. Areas Commun.: 2012; Volume 33 ,467-481.
[14] Hsu, J.; Power management in energy harvesting sensor networks; ACM Trans. Embed. Comput. Syst.: 2007; Volume 6 ,32.
[15] Neely, M.J.; Modiano, E.; Rohrs, C.E.; Power allocation and routing in multibeam satellites with time-varying channels; IEEE/ACM Trans. Netw.: 2003; Volume 11 ,138-152.
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