| Title | : | UAV-Aided Computation and User Offloading in 5G and Beyond Networks |
| Speaker | : | Chigullapally Sriharsha (IITM) |
| Details | : | Fri, 28 Jun, 2024 11:00 AM @ By Google Meet |
| Abstract: | : | With each generation of mobile communication networks, stringent network performance requirements and challenging use cases are being targeted. Among other things, beyond 5G and 6G networks envision ubiquitous global network coverage, i.e., coverage of every location on the planet, including the remotest areas of the world. While ubiquitous global coverage has many use cases, such as military surveillance, global cargo movement, and weather monitoring, installing conventional cellular infrastructure in remote areas is not justified, both in terms of capital expenditure and utilization. In such situations, Unmanned aerial vehicles (UAVs) offer a cost-effective and efficient alternative.
UAVs can be utilised to provide Mobile Edge Computing (MEC) services to the Internet of Remote Things (IoRT) devices spread over a remote area. In the existing literature, two alternative locations for placing MEC have been suggested - on the UAV and on the satellite. There are some works in which a combination of both alternatives is used. However, both alternatives are inefficient in terms of energy consumption. Alternately, we propose placing the MEC device on the ground while using a UAV to relay the data collected from IoRT devices to the MEC device. The proposed alternative is more energy efficient, albeit with a slight decrease in the average system capacity compared to placing the MEC on the UAV.
The data collected from IoRT devices needs to be processed to extract useful information from it and relevant output data, besides control information, may have to be sent back to the IoRT devices. Therefore, we propose a full-fledged architecture to provide MEC services to IoRT devices using multiple UAVs, considering the two-way movement of data. The UAVs relay the data generated by the IoRT devices to the MEC device located on the ground at a nearby location. After carrying out computations, the MEC device sends the results back to the IoRT devices via the UAVs. We provide a heuristic solution to jointly optimize the UAV trajectory planning, connection scheduling, bit transmission scheduling, bandwidth allocation, and power control for the proposed architecture to minimize total energy consumption while maximizing the system throughput. Besides ubiquitous connectivity, the UAVs are also leveraged in performing user offloading from one gNodeB (base station in 5G networks) to another in hotspot scenarios, i.e., when the traffic load is so high that Service Level Agreement (SLA) violations occur. Offloading the users to neighbouring gNodeB by borrowing the unused bandwidth of the neighbouring gNodeB leads to co-channel interference, as the same frequencies are used by every gNodeB. Therefore, we propose a novel UAV-aided cellular user offloading that uses Successive Interference Cancellation (SIC) at the receivers to mitigate the co-channel interference. As SIC is used at the receivers, it is important to optimize the number and locations of the UAVs, load redistribution among the gNodeBs, power allocation, bandwidth allocation, and user association. We propose a heuristic solution to perform the joint optimization of the aforementioned parameters while minimizing the total cost of SLA violations. Our proposed solution increases the spectral efficiency, decreases the total cost of SLA violations, and can be used in both cell-centred and cell-edge users. While the SIC-based solution is effective for offloading the unblocked cellular users, the same cannot be said for power-constrained devices and blocked cellular users. Intelligent Reflecting Surface (IRS) technology can be used to reach the blocked users. Therefore, we propose using a UAV mounted with two IRS panels to offload the blocked users while minimizing the co-channel interference. We propose a heuristic solution to jointly optimize the location of the UAV, user association, phase shifts of the IRS elements, transmit power allocation, and bandwidth allocation while offloading the blocked users. The proposed solution decreases the number of SLA violations and improves the overall spectral efficiency. Web Conference Link :https://meet.google.com/fer-hbsu-seu |
