# A Comprehensive Worst Case Bounds Analysis of IEEE 802.15.7
## 2 Related Work
Instead, in their research, they propose to integrated VLC and a VLC positioning network for IoT, to support both high-speed communication and high-accuracy positioning services in smart industry IoT networks. The security advantages of such usage in this domain are also extensively mentioned in ref. [13], in which the authors propose a VLC system to control electrical appliances. Recently, harmonization of protocols is becoming a key to achieve efficient trade offs in IoT for several application domains. One such methodology is the Fault-Tolerant and Medium Access Control (FTMAC) protocol for IoT over VLC. In this work [14], the authors carry out primary data communication over a VLC link. In the event of VLC link failures, communication can be restored using a WiFi link. Such methods, besides supporting additional redundancy, can enable multiple link prioritization. Besides these domains, IEEE 802.15.7 can easily be a forerunner in the field of wireless body area networks due to its support of large data rates, minimal latency and strong security, while avoiding RF proximity to the body or potential interference with medical equipment, for instance. Authors in ref. [15] use full duplex bidirectional communication supported by an infrared uplink and visible light downlink. Using a ray-tracing technique they determine the overall outage performance. The approach is capable of satisfying the WBAN QoS requirements in terms of bit error rate and data rate using VLC links. As observed, most of the work in the literature fails to achieve the full potential of this federated communication protocol, by not exploring its time critical properties. To truly foster the deployment of such communication technologies in application domains such as Industrial IoT, it is paramount to understand the performance limits in terms of latency and throughput guaranteed by such networks. In some of our previous works [16; 17], we used network calculus to determine the worst case bounds of IEEE 802.15.4e in terms of delay and throughput for GTS utilization. This knowledge and model was then used to enable a set of critical application scenarios, like enabling a Wireless Advanced Driving Assistance System, such as in ref. [18]. In the aforementioned application, we took the deterministic capabilities of the network and analyzed the relationship between different vehicle dynamics and the delay required for the system to operate safely, exploring the performance limits of the respective wireless network configurations. Researchers also look into the possibility of LiFi modules, which can be mounted in the head lamp as well as tail lamps of a four-wheeler, which will help to transmit real-time information such as -speed data, anti-lock braking data, turn indication, certain emergencies in car, tire related data [19]. Researchers are venturing into the possibilities of implementation of VLC networks in complex geographical monitoring systems like underground mining fields [20] where there is a need for a reliable system of continuous personnel monitoring and localization with the aim to keep a real-time, up-to-date database of personnel, and their specific location underground. Interestingly, the IEEE 802.15.7 also facilitates a GTS mechanism to support time-critical communications. In this paper, we take a similar approach to learn the impact of the different network parameters over the QoS of the network, drawing the performance bounds in terms of network delay and throughput. In what follows we provide a technical overview of the various PHY layers of IEEE 802.15.7 and the mechanisms of the MAC sub-layer. In Section 4, we derive the network calculus model of the GTS service mechanism of IEEE 802.15.7. In Section 5, we use it to compute the worst case bounds of the service in terms of delay and throughput, in regard to different settings of the protocol.