In order to meet the new escalating demand for high data rate services and applications, visible light communication (VLC) has emerged as a promising solution for the fifth-generation (5G) wireless networks and beyond. Consider a VLC network, where multiple access points (APs) serve both energy-harvesting users (EHUs), i.e., users which harvest energy from light intensity, and information-users (IUs), i.e., users which gather data information. The performance of the system becomes a function of the direct current (DC) bias values allocated to each AP. After adopting a zero-forcing (ZF) precoding approach to cancel the inter-cell interference, the paper formulates the problem of maximizing the network harvested energy subject to individual harvested energy and data rate constraints at the EHUs and IUs, respectively, so as to determine the DC bias of every AP. The paper then proposes solving such a difficult non-convex optimization problem using an iterative approach. The proposed algorithm uses well-chosen approximations of the objective and constraints functions, and compensates for the approximations using proper outer-loop updates. The paper further proposes a sub optimal heuristic which provides a feasible, yet simple, solution to the problem. Numerical results illustrate the convergence of our proposed algorithms, and highlight the significant performance improvement of the proposed algorithm as compared to the proposed baseline approach.
|Title of host publication
|2018 IEEE Global Communications Conference (GLOBECOM)
|Institute of Electrical and Electronics Engineers (IEEE)
|Published - Feb 21 2019
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was funded by the National Plan for Science, Technology and Innovation (Maarifah)-King Abdulaziz City for Science and Technology through the Science and Technology Unit at King Fahd University of Petroleum & Minerals (KFUPM)-the Kingdom of Saudi Arabia, under grant number 15-ELE4157-04. The work was also supported by the Deanship of Scientific Research in KFUPM through grant number IN161023. Hayssam Dahrouj would like to thank Effat University in Jeddah, Saudi Arabia, for funding the research reported in this paper through the Research and Consultancy Institute.