Resource Allocation for Hybrid Visible Light Communications (VLC)-WiFi Networks

Abstract

Visible Light Communication (VLC) is becoming a promising technology of wireless communication, due to high data rate, low cost, and immunity to Radio Frequency (RF) interference. However, the VLC systems often suffer from service disruptions because of the limited coverage of light. Therefore, the heterogeneous networks of VLC and WiFi are proposed to achieve high-speed indoor communication and seamless coverage. This paper investigates an efficient heterogeneous network resource management algorithm, which is not only significant to integrate the current network resources but also has practical significance to improve the performance of heterogeneous networks. We establish a distributed joint resource management system model and propose two kinds of resource management allocation strategies to allocate bandwidth among the users with maximum fairness. The simulation results show the feasibility of the heterogeneous network and the effectiveness of the algorithm.

Sub-Decimeter VLC 3D Indoor Localization With Handover Probability Analysis

“…where the variance of the shot noise would be as σ 2 shot = 2qRP VLC , where q, R, and P VLC indicate the electric charge, photodiode responsivity, and transmitter power, respectively. In addition, the variance of the background noise, denoted by σ 2 bg , and the thermal noise variance, σ 2 thermal , are given by…”

“…Moreover, γ (N mode +1) th = ∞ indicates that the coding mode is chosen for each value of γ ∈ [γ (1) th , +∞). Case 2: In this case, the coding mode is selected such that the average effective throughput η (2) (i), defined in (29), is maximized, i.e.,…”

“…Finally, we obtain the average effective throughput as the expectation of conditional probability of the effective number of signals transmitted successfully given the pdf of γ im,jn , expressed as (36), where (a) comes from the formula η 1) is re-expressed as (37), where Γ (s, x) is an incomplete gamma function, defined as Γ(s, x) = +∞ x t s−1 e −t dt. With a similar argument as mentioned above, η (2) is computed by Wol-fram|Alpha as (38), where i * = arg max 1≤i≤N mode η (2) . Moreover,…”

“…The coordinates of the center of each VLC transmitter is shown in Table 2. Each LED has the semi-angle of half power at θ 1/2 = 60 • resulting in Lambertian factor w = − ln (2) ln cos(Φc) = 2. In addition, each user u m , as a receiver, has P = 4 PDs positioned on the smart device where each PD has FoV of Φ c = 85 • and area of A r = 1cm 2 .…”

“…H IGHLY precise and robust user localization has become an inseparable part of 6G and beyond wireless networks to support various location-based services in many emerging applications such as smart homes and automatic factories [1]. Although the Global Positioning System (GPS) is widely used for outdoor applications such as road transport services, it is not able to provide sub-meter level accuracy in an indoor environment as satellite signals are scattered and attenuated by indoor roofs and walls [2]. In the past decade, Radio Frequency (RF) systems such as WiFi have been widely used for indoor localization, by employing high-level software and hardware resources [3].…”