In this paper, we present results of a study of the data rate fairness among nodes within a LoRaWAN cell. Since LoRa LoRaWAN supports various data rates, we firstly derive the fairest ratios of deploying each data rate within a cell for a fair collision probability. LoRa LoRaWAN, like other frequency modulation based radio interfaces, exhibits the in which only the stronger signal of colliding signals will be extracted. This leads to unfairness, where far nodes or nodes experiencing higher attenuation are less likely to see their packets received correctly. Therefore, we secondly develop a transmission power control algorithm to balance the received signal powers from all nodes regardless of their distances from the gateway for a fair data extraction. Simulations show that our approach achieves higher fairness in data rate than the state-of-art in almost all network configurations.
Recent research on LoRa LoRaWAN has mainly focused on LoRa performance evaluation in terms of coverage, capacity, scalability and lifetime. The studies have been carried out using real deployments in @cite_12 and @cite_19 , mathematical models in @cite_2 and @cite_3 , or computer simulations in @cite_4 and @cite_14 . Almost all these works have assumed perfectly orthogonal @math although it has been shown in @cite_20 and @cite_5 that this is not a valid assumption.
@cite_14 @cite_4 @cite_3 @cite_19 @cite_2 @cite_5 @cite_20 @cite_12
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In addition to long battery life and low cost, coverage is one of the most critical performance metrics for the low power wide area networks (LPWAN). In this work we study the coverage of the recently developed LoRa LPWAN technology via real-life measurements. The experiments were conducted in the city of Oulu, Finland, using the commercially available equipment. The measurements were executed for cases when a node located on ground (attached on the roof rack of a car) or on water (attached to the radio mast of a boat) reporting their data to a base station. For a node operating in the 868 MHz ISM band using 14 dBm transmit power and the maximum spreading factor, we have observed the maximum communication range of over 15 km on ground and close to 30 km on water. Besides the actual measurements, in the paper we also present a channel attenuation model derived from the measurement data. The model can be used to estimate the path loss in 868 MHz ISM band in an area similar to Oulu, Finland. In this paper we study the impact of imperfect-orthogonality in LoRa spreading factors (SFs) in simulation and real-world experiments. First, we analyze LoRa modulation numerically and show that collisions between packets of different SFs can indeed cause packet loss if the interference power received is strong enough. Second, we validate such findings using commercial devices, confirming our numerical results. Third, we modified and extended LoRaSim, an open-source LoRa simulator, to measure the impact of inter-SF collisions and fading (which was not taken into account previously in the simulator). Our results show that non-orthogonality of the SFs can deteriorate significantly the performance especially of higher SFs (10 to 12) and that fading has virtually no impact when multiple gateways are available in space diversity. LoRaWAN is emerging as an attractive network infrastructure for ultra low power Internet of Thing devices. Albeit the technology itself is quite mature and specified, how to effectively allocate wireless resources so as to support a large amount of devices in a same terrestrial area is an open challenge. This paper contributes by proposing two algorithms (of incremental complexity) which are shown to outperform the basic Adaptive Rate Strategy (ADR) so far considered. A first approach, named EXPLoRa-SF, shows the benefits of a simple strategy which does not limit to use (as per ADR) distance RSSI measurements, but also selects Spreading Factors (SF) based on the total number of connected devices. The advantages attained with EXPLoRa-SF further lead us to propose a more sophisticated algorithm, named EXPLoRa-AT, which employs an innovative “ordered waterfilling” approach which attempts to allocate the spreading factors so as to equalize the Time on Air of the packets transmitted by the system's end devices in each spreading factor's group. Simulation results show that the proposed algorithms significantly outperform the basic ADR strategy, and particularly the EXPLoRa-AT algorithm appears very robust to different operating conditions and consistently guarantees high bit rates in the case of high traffic loads. Internet of Things (IoT) solutions are increasingly being deployed for smart applications. To provide good communication for the increasing number of smart applications, there is a need for low cost and long range Low Power Wide Area Network (LPWAN) technologies. LoRaWAN is an energy efficient and inexpensive LPWAN solution that is rapidly being adopted all around the world. However, LoRaWAN does not guarantee reliable communication in its basic configuration. Transmitted frames can be lost due to the channel effects and mobility of the end-devices. In this study, we perform extensive measurements on a new LoRaWAN network to characterise spatial and temporal properties of the LoRaWAN channel. The empirical outage probability for the farthest measured distance from the closest gateway of 7.5 km in our deployment is as low as 0.004, but the frame loss measured at this distance was up to 70 . Furthermore, we show that burstiness in frame loss can be expected for both mobile and stationary scenarios. Frame loss results in data loss, since in the basic configuration frames are only transmitted once. To reduce data loss in LoRaWAN, we design a novel coding scheme for data recovery called DaRe, which extends frames with redundant information that is calculated from the data from previous frames. DaRe combines techniques from convolutional codes and fountain codes. We develop an implementation for DaRe and show that 99 of the data can be recovered with a code rate of 1 2 for up to 40 frame loss. Compared to repetition coding DaRe provides 21 more data recovery, and can save up to 42 energy consumption on transmission for 10 byte data units. DaRe also provides better resilience to bursty frame loss. This study provides useful results to both LoRaWAN network operators as well as developers of LoRaWAN applications. Network operators can use the characterisation results to identify possible weaknesses in the network, and application developers are offered a tool to prevent possible data loss.