A Hybrid RF-VLC System for Energy Efficient Wireless Access

Abstract

In this paper, we propose a new paradigm in designing and realizing energy efficient wireless indoor access networks, namely, a hybrid system enabled by traditional RF access, such as WiFi, as well as the emerging visible light communication (VLC). VLC facilitates the great advantage of being able to jointly perform illumination and communications, and little extra power beyond illumination is required to empower communications, thus rendering wireless access with almost zero power consumption. On the other hand, when illumination is not required from the light source, the energy consumed by VLC could be more than that consumed by the RF. By capitalizing on the above properties, the proposed hybrid RF-VLC system is more energy efficient and more adaptive to the illumination conditions than the individual VLC or RF systems. To demonstrate the viability of the proposed system, we first formulate the problem of minimizing the power consumption of the hybrid RF-VLC system while satisfying the users requests and maintaining acceptable level of illumination, which is NP-complete. Therefore, we divide the problem into two subproblems. In the first subproblems, we determine the set of VLC access points (AP) that needs to be turned on to satisfy the illumination requirements. Given this set, we turn our attention to satisfying the users' requests for real-time communications, and we propose a randomized online algorithm that, against an oblivious adversary, achieves a competitive ratio of log(N) log(M) with probability of success (1 − 1 N ), where N is the number of users and M is the number of VLC and RF APs. We also show that the best online algorithm to solve this problem can achieve a competitive ratio of log(M). Simulation results further demonstrate the advantages of the hybrid system.

Deep Q-Network Learning Based Downlink Resource Allocation for Hybrid RF/VLC Systems

“…Once again, the association parameter and the bandwidth are kept fixed here. In [20], power efficiency maximization for situations when illumination is not needed and the light source is kept on only for the transmission of data has been performed. In this situation, a VLC AP consumes more power than the RF AP.…”

“…In this section, a DQN-based learning algorithm for the resource allocation problem in (20) ij , s 2 ij , . .…”

“…With each iteration, the system moves towards receiving the maximum reward. The action vector, state vector and reward are formulated as follows: As it can be seen in (20), the association and resource allocation variables are α ij , B ij , and P i , the action space A ij will be formulated with α ij , B ij , and P i for i ∈ N and j ∈ M. Let B ij and P i be the discretized sets of B ij and P i respectively, for i ∈ N and j ∈ M. The following formulation is made for B ij and P i :…”

“…The DQN learning for the ith AP at the CU of AP i in(20) while satisfying the constraints in (21)-(27). Learning based algorithms run with the help of three vector variables: state, action, and reward.…”

Optimization of MAC Frame Slots and Power in Hybrid VLC/RF Networks

“…In [10], number of active VLC-APs and link to active APs are optimized to increase energy efficiency while satisfying the illumination requirements and user request. The NP-complete problem is divided into two sub problems.…”