Elite User Clustering-Based Indoor Heterogeneous VLC Interference Management and Sub-Channel Allocation Strategy

Abstract

The visible light communication (VLC) and wireless fidelity (WIFI) heterogeneous network is considered as a highly competitive candidate for the next generation indoor wireless communication. VLC provides high data rate as downlink transmission while WIFI can be supplied to achieve uplink transmission and make up for link interruptions caused by occlusion. Due to the dense distribution of VLC access points (APs), data rate of users is reduced by inter-cell interference (ICI) seriously, therefore, interference management (IM) is crucial to ensure user satisfaction. Meanwhile, as the number of users increases, in order to ensure the needs of users, reasonable resource allocation is required in such heterogeneous network. Hence, the center of the elite user clustering attracts its non-interfering users to join a cluster that is a user with good channel quality and high demand. And users in one cluster share resources by sub-channel reuse. In consideration of interference management and resource allocation, we investigated resource allocation based on elite users clustering for interference management in heterogeneous network, which is formulated as a throughput maximization problem, and a graph-based IM is proposed to solve it. Compared with the benchmark 1 and benchmark 2 on a rectangular layout and an irregular layout, the simulation results demonstrate that the throughput of the proposed elite user clustering algorithm is increased by 19.5% and 12%, the average user satisfaction ratio is increased by 14% and 9%, respectively. INDEX TERMS VLC heterogeneous networks, interference management, elite user clustering, inter-cell interference, user satisfaction.

Hybrid LiFi and WiFi Networks: A Survey

“…On the opposite, a delicate user association in HLWNets can help mitigating interference in LiFi, e.g. based on a conflict graph in [90]. The AP selection between LiFi and WiFi is a key issue in HLWNets and will be discussed in the following sections.…”

A Reinforcement Learning Approach for Interference Management in Heterogeneous Wireless Networks

“…The problem interference poses to heterogeneous networks has recently dominated discussions in the research community [13]- [26]. In heterogeneous cellular networks, a user equipment (UE) at the cell border always experiences high interference from neighbouring transmitters as their distance dependent attenuation is a critical issue [27].…”

Research on handover strategy of heterogeneous networks based on user service quality

“…Wang et al 8 proposed a dynamic balance method between switching cost and delay requirement under the conditions of a given queue length and optical wireless channel (available or unavailable), which saves 50 % of the cost in this process. Liu et al 9 mainly studied elite user clustering resource management and proposed a graph‐based interference management (IM) solution to solve the problem of inter‐cell interference. Compared with other schemes, throughput and average user satisfaction are significantly improved.…”