TY - GEN
T1 - On the Optimization of Multi-Cell SLIPT Systems
AU - Abdelhady, Amr Mohamed Abdelaziz
AU - Amin, Osama
AU - Shihada, Basem
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2019/2/21
Y1 - 2019/2/21
N2 - In this paper, we study the performance of simultaneous lightwave information and power transfer (SLIPT) systems of multi-cell indoor scenario. We aim to investigate the energy harvesting and data rate performance of multiple users while meeting the lightning constraints. To this end, we develop optimization frameworks and tune the light emitting diodes average currents to improve the performance of the SLIPT system. Firstly, we propose an algorithm to maximize the spectral efficiency (SE) subject to lighting and minimum harvested energy per user requirements. The proposed algorithm can be implemented in a distributed fashion with a reduced computational burden at each node. Then, we consider the energy harvesting maximization problem to investigate the maximum possible energy gain and its corresponding SE performance. Finally, we present some extensive simulations to explore the benefit of the optimization frameworks with respect to standard equal allocation setting. In addition, we monitor the effect of changing several system parameters on the two objectives and highlight the underlying trade-off between them.
AB - In this paper, we study the performance of simultaneous lightwave information and power transfer (SLIPT) systems of multi-cell indoor scenario. We aim to investigate the energy harvesting and data rate performance of multiple users while meeting the lightning constraints. To this end, we develop optimization frameworks and tune the light emitting diodes average currents to improve the performance of the SLIPT system. Firstly, we propose an algorithm to maximize the spectral efficiency (SE) subject to lighting and minimum harvested energy per user requirements. The proposed algorithm can be implemented in a distributed fashion with a reduced computational burden at each node. Then, we consider the energy harvesting maximization problem to investigate the maximum possible energy gain and its corresponding SE performance. Finally, we present some extensive simulations to explore the benefit of the optimization frameworks with respect to standard equal allocation setting. In addition, we monitor the effect of changing several system parameters on the two objectives and highlight the underlying trade-off between them.
UR - http://hdl.handle.net/10754/628870
UR - https://ieeexplore.ieee.org/document/8647447
UR - http://www.scopus.com/inward/record.url?scp=85063481347&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2018.8647447
DO - 10.1109/GLOCOM.2018.8647447
M3 - Conference contribution
SN - 9781538647271
BT - 2018 IEEE Global Communications Conference (GLOBECOM)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -