This paper presents the design and implementation of HyLink which aims to fill the gap between limited link capacity of LoRa and the diverse bandwidth requirements of IoT systems. At the heart of HyLink is a novel technique named parallel Chirp Spread Spectrum modulation, which tunes the number of modulated symbols to adapt bit-rates according to channel conditions. Over strong link connections, HyLink fully exploits the link capability to transmit more symbols and thus transforms good channel SNRs to high link throughput. While for weak links, it conservatively modulates one symbol and concentrates all transmit power onto the symbol to combat poor channels, which can achieve the same performance as legacy LoRa. HyLink addresses a series of technical challenges on encoding and decoding of multiple payloads in a single packet, aiming at amortizing communication overheads in terms of channel access, radio-on power, transmission air-time, etc. We perform extensive experiments to evaluate the effectiveness of HyLink. Evaluations show that HyLink produces up to$10\times $higher bit rates than LoRa when channel SNRs are higher than$\mathrm {5 dB}$. HyLink inter-operates with legacy LoRa devices and can support new emerging traffic-intensive IoT applications.

LoRaWAN suffers dramatic performance degradation over a long communication range due to signal attenuation and blockages. To ensure reliable data transfer, LoRaWAN adopts retransmission mechanism where an unacknowledged packet is retransmitted multiple times in the hope of successfully delivering the packet at least once over harsh wireless channels. This retransmission mechanism is ill-suited for LoRa: 1) unsuccessful retransmissions lead to high power consumption for battery-powered LoRa nodes, and 2) a retransmission at another time does not necessarily improve the signal strength over harsh wireless channels.

The battery-powered Unmanned Aerial Vehicle (UAV) is a promising alternative to traditional logistics trucks. Using UAVs can achieve much more speedy, cost-effective, and environment-friendly delivery on an urban scale. However, UAVs suffer from insufficient delivery range and battery aging. This paper presents an innovative logistics UAV scheduling framework using public buses, in which logistics UAVs Land and Recharge its battery on Buses (ULRB) to extend its delivery range and decelerate its fading battery capacity. This work correlates physical layer parameters such as the energy consumption rate, the parcels weight, UAV velocity, the battery temperature to the UAVs path planning, the battery discharging, and the capacity fading models. Specifically, the ULRB framework consists of a single-UAV scheduling module and a multi-UAV dispatching module. In the single-UAV module, a Markov-based algorithm is utilized to plan the UAVs flying path to land and dynamically get recharged on the bus. The latter module optimized the delivery progress in a multi-UAV, multi-parcel, and multi-bus scenario. Finally, using a large-scale real-world bus trajectory dataset, extensive evaluations are conducted to verify ULRB. The results show that ULRB can extend the UAVs delivery range by 5.54 and decelerate the battery aging by 3.26 on average.

Unmanned Aerial Vehicles (UAVs) are widely employed in smart city. However, the limited battery capacity is one of the UAV's most critical obstacles to monitoring mission. Recently, leveraging public buses to relay UAVs has been shown to be a promising solution to this critical issue. Existing works on this solution focused on pre-determined scenarios, namely the mission time and location of the UAVs are determined in advance. While in on-demand mission such as emergency response, mission time and location of the UAV is on-demand and stochastic. How the UAV riding on a bus perform in such stochastic missions remains open. In this paper, driven by the bus mobility data, a sampling-based algorithm is designed to navigate UAVs to land on buses in on-demand applications. A simple greedy algorithm is proposed to determine the appropriate buses to relay UAVs, so that the scheduling performance of the UAVs is optimized. Comprehensive evaluation using a large-scale bus trajectory data is conducted.

This paper presents the design and implementation of HyLink which aims to fill the gap between limited link capacity of LoRa and the diverse bandwidth requirements of IoT systems. At the heart of HyLink is a novel technique named parallel Chirp Spread Spectrum modulation, which tunes the number of modulated symbols to adapt bit-rates according to channel conditions. Over strong link connections, HyLink fully exploits the link capability to transmit more symbols and thus transforms good channel SNRs to high link throughput. While for weak links, it conservatively modulates one symbol and concentrates all transmit power onto the symbol to combat poor channels, which can achieve the same performance as legacy LoRa. HyLink addresses a series of technical challenges on encoding and decoding of multiple payloads in a single packet, aiming at amortizing communication overheads in terms of channel access, radio-on power, transmission air-time, etc. We perform extensive experiments to evaluate the effectiveness of HyLink. Evaluations show that HyLink produces up to 10× higher bit rates than LoRa when channel SNRs are higher than 5 dB. HyLink inter-operates with legacy LoRa devices and can support new emerging traffic-intensive IoT applications.