# Slotted ALOHA on LoRaWAN-Design, Analysis, and Deployment
## 1 Introduction  
In past years, industry and academia have dedicated significant efforts to developing low-power wide area networks (LPWAN), as a new category of wireless communication standard [1, 2]. Among commercial protocols, LoRaWAN, and the LoRa modulation developed by Semtech, is gaining popularity [3, 4, 5, 6, 7, 8, 9, 10, 11]. The public availability of the specifications [12] combined with low-cost certified transceivers [13] and the fact that a LoRaWAN WSN (Wireless Sensor Network) can operate in the unlicensed radio spectrum, means that anyone can use the radio frequencies without having to pay million dollar fees for transmission rights, and has motivated the global attention on this protocol. LoRa offers a link range of up to 10 km with a single gateway, which is capable of supporting hundreds of thousands of different devices; moreover, a unique feature of LoRa is the ability of the gateway to simultaneously demodulate multiples transmissions, with different data rates, on the same channel and time. LoRaWAN specification describes three classes of operations: low-power bi-directional end devices (Class A), scheduled downlink transmission (Class B) and Class C, designed for always-on bi-directional actuators. In this work, we focus the attention on the most commonly used Class A. Despite the initial success, multiple open issues remain concerning the real performance in terms of scalability and the maximum traffic supported in massive LoRaWAN installations. Most LPWAN protocols promise to manage thousands of devices, but the impact of the LoRaWAN parameters onlarge-scale networks, with packet time that can be more than one second, is still not well explored. Indeed, in Refs. [14; 15; 16] the scalability of LoRaWAN is studied, and the results in [14] show that only 120 nodes can be managed with a packet transmission every 22 min with static configurations. The performance improves, growing up to 1600, with dynamic configurations that minimize the time of air. In Ref. [5], the authors show an impressive reduction of channel capacity, up to 2\(\times\), when message acknowledgments are required. However, these figures are not enough for future IoT deployments [5]. While many existing works have studied the scalability of LoRaWAN networks, most of them do not consider the impact of downstream traffic on channel throughput, interference, and issues related to real deployments, such as clock drifts and delays produced by the restricted computational resources of LoRaWAN gateways and servers. The work presented in this article aims at providing an analysis of the channel throughput of the LoRaWAN protocol, and to investigate the issues associated with its scalability. The results can provide useful guidelines for large-scale deployments and physical configurations. A specific network simulator offers information about the real performance of LoRaWAN Class A with varying number of devices and packet time of air. We studied the effective payload throughput related to the protocol overhead, which decreases with a factor of 2.22\(\times\) (in the worst case) compared to Pure-ALOHA (P-ALOHA). After that, we propose a solution to improve network performance based on Slotted-ALOHA (S-ALOHA). We developed a reliable synchronization algorithm optimized for low-power devices, with an accuracy of 5.37 ms and a success rate over 99%. This reference time is used to keep aligned all the end nodes in LoRaWAN network, allowing deployment of a Slotted LoRaWAN built on top of standard LoRaWAN specifications. Simulations and tests, performed with 24 end nodes, show a throughput improvement of 2\(\times\), and 5.8\(\times\) in crowded conditions. The low-power capabilities of Class A are preserved, and our Slotted LoRaWAN can be implemented on existing commercial products. The remainder of this work is organized as follows: Section 2 presents the related works, while Section 3 introduces the LoRa physical layer and the LoRaWAN protocol.