5 research outputs found

    Light-Fidelity as Next Generation Network Technology: A Bibliometric Survey and Analysis

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    This paper delivers a systematic review and a bibliometric survey analysis of Light-Fidelity (Li-Fi) indoor implementation in Next Generation Network (NGN). The main objective of this study is to design a communication network based on NGN-Li-Fi for the indoor implementation which aims to increase user Quality of Service (QoS). The main merits and contributions of this study are the thorough and detailed analysis of the review, both in literature surveys and bibliometric analysis, as well as the discussion of the implementation model challenges of Li-Fi in both indoor and outdoor environments. The issue articulated in an indoor communication network is the possibility of intermittent connectivity due to barriers caused by line-of-sight (LOS) between the LED transmitter and receiver, handover due to channel overlap, and other network reliability issues. To realize the full potential and significant benefits of the Next Generation Network, challenges in indoor communication such as load-balancing and anticipating network congestion (traffic congestion) must be addressed. The main benefit of this study is the in-depth investigation of surveys in both selected critical literatures and bibliometric approach. This study seeks to comprehend the implications of Next Generation networks for indoor communication networks, particularly for visible light communication channels

    Load balancing in hybrid LiFi and RF networks

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    The increasing number of mobile devices challenges the current radio frequency (RF) networks. The conventional RF spectrum for wireless communications is saturating, motivating to develop other unexplored frequency bands. Light Fidelity (LiFi) which uses more than 300 THz of the visible light spectrum for high-speed wireless communications, is considered a promising complementary technology to its RF counterpart. LiFi enables daily lighting infrastructures, i.e. light emitting diode (LED) lamps to realise data transmission, and maintains the lighting functionality at the same time. Since LiFi mainly relies on line-of-sight (LoS) transmission, users in indoor environments may experience blockages which significantly affects users’ quality of service (QoS). Therefore, hybrid LiFi and RF networks (HLRNs) where LiFi supports high data rate transmission and RF offers reliable connectivity, can provide a potential solution to future indoor wireless communications. In HLRNs, efficient load balancing (LB) schemes are critical in improving the traffic performance and network utilisation. In this thesis, the optimisation-based scheme (OBS) and the evolutionary game theory (EGT) based scheme (EGTBS) are proposed for load balancing in HLRNs. Specifically, in OBS, two algorithms, the joint optimisation algorithm (JOA) and the separate optimisation algorithm (SOA) are proposed. Analysis and simulation results show that JOA can achieve the optimal performance in terms of user data rate while requiring high computational complexity. SOA reduces the computational complexity but achieves low user data rates. EGTBS is able to achieve a better performance/complexity trade-off than OBS and other conventional load balancing schemes. In addition, the effects of handover, blockages, orientation of LiFi receivers, and user data rate requirement on the throughput of HLRNs are investigated. Moreover, the packet latency in HLRNs is also studied in this thesis. The notion of LiFi service ratio is introduced, defined as the proportion of users served by LiFi in HLRNs. The optimal LiFi service ratio to minimise system delay is mathematically derived and a low-complexity packet flow assignment scheme based on this optimum ratio is proposed. Simulation results show that the theoretical optimum of the LiFi service ratio is very close to the practical solution. Also, the proposed packet flow assignment scheme can reduce at most 90% of packet delay compared to the conventional load balancing schemes at reduced computational complexity
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