DC-Bias Allocation in Cooperative VLC Networks via Joint Information and Energy Transfer

Mohanad Obeed, Hayssam Dahrouj, Anas M. Salhab, Salam A. Zummo, Mohamed Slim Alouini

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


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.

Original languageEnglish
Article number8647944
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 IEEE.


  • convex optimization
  • energy harvesting
  • Visible light communication

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


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