A LiFi-RF heterogeneous network can provide additional capacity to standalone wireless technologies due to their non-interfering nature. However, due to the properties of the short-range LiFi channel, the network is prone to transient channel variations that result in frequent, unnecessary handovers. This handover process creates an overhead and can result in the loss of connection. To ensure a stable connection for all users, a low complexity resource allocation algorithm, that considers the loss due to handovers, is proposed to minimize the number of handovers. This algorithmic approach is evaluated with simulations. For scenarios with unavoidable handovers, a system approach to manage vertical handovers is proposed to minimize the vertical handoff overhead and to offer a seamless interface switch, thereby resulting in a stable network. This protocol is implemented in hardware and the results show a negligible overhead.
Ubiquity in network coverage is one of the main features of 5G and is expected to be extended to the computing domain in 6G. In order to provide this holistic approach of ubiquity in communication and computation, an integration of satellite, aerial and terrestrial networks is foreseen. In particular, the rising amount of applications such as In-Flight Entertainment and Connectivity Services (IFECS) and SDN-enabled satellites renders network management more challenging. Moreover, due to the stringent Quality of Service (QoS) requirements edge computing gains in importance for these applications. Here, network performance can be boosted by considering components of the aerial network, like aircrafts, as potential Multi-Access Edge Computing (MEC) nodes. Thus, we propose an Aerial-Aided Multi-Access Edge Computing (AA-MEC) architecture that provides a framework for optimal management of computing resources and internet-based services in the sky. Furthermore, we formulate optimization problems to minimize the network latency for the two use cases of providing IFECS to other aircrafts in the sky and providing services for offloading AI/MLtasks from satellites. Due to the dynamic nature of the satellite and aerial networks, we propose a re-configurable optimization. For the transforming network we continuously identify the optimal MEC node for each application and the optimal path to the destination MEC node. In summary, our results demonstrate that using AA-MEC improves network latency performance by 10.43% compared to the traditional approach of using only terrestrial MEC nodes for latency-critical applications such as online gaming. Furthermore,
While 5G delivers high quality services mostly in a two dimensional terrestrial area covering our planet's surface, with 6G we aim at a full exploitation of three dimensions. In this way, 6G includes all kinds of non-terrestrial networks. In particular, Unmanned Aerial Vehicles (UAVs), High-Altitude Platforms (HAPs), (self-)flying taxis and civil aircrafts are new additions to already existing satellite networks complementing the cellular terrestrial network. Their integration to 6G is promising with respect to service coverage, but also challenging due to the so far rather closed systems. Emerging technology concepts such as Mobile Edge Computing (MEC) and Software-Defined Networking (SDN) can provide a basis for a full integration of aeronautical systems into the terrestrial counterpart. However, these technologies render the management and orchestration of aeronautical systems complex. As a step towards the integration of aeronautical communication and services into 6G, we propose a framework for the collection, monitoring and distribution of resources in the sky among heterogeneous flying objects. This enables high-performance services for a new era of 6G aeronautical applications. Based on our aeronautical framework, we introduce emerging application use-cases including Aeronautical Edge Computing (AEC), aircraft-as-a-sensor, and in-cabin networks.
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