## 1 Introduction  
IoT (Internet-of-Things) [1] is a paradigm where constrained computing devices with embedded sensing and wireless communication capabilities are used to collect data from physical processes in a distributed fashion. The data from multiple end-devices is then aggregated by an edge network coordinator and forwarded to a cloud-based back-end to be further stored, processed and analyzed [2]. The results of the aggregated data analysis provide valuable insight regarding the physical processes and allow to optimize its operation [3]. Hence, given its potential value, the IoT paradigm is currently being applied to homes [4], cities [5], health care [6] and industries [7], among others. However, as the adoption of the IoT paradigm increases, there are several aspects of the data chain that need to be properly engineered to ensure that the solution is both scalable, reliable and of low power. One of the weakest links in the IoT data chain is the communication between end-devices and the network coordinator. As end-devices are physically distributed, power-constrained and cost sensitive, communications are typically based on long-range and low-power wireless technologies (i.e., IEEE 802.15.4, SigFox or LoRa) [8]. Despite being standardized [9; 10], these technologies operate in unlicensed bands (i.e., 868 MHz in Europe, 915 MHz in USA and 2.4 GHz world-wide) and rely on simple radio modulation techniques. Hence, despite the fact that end-devices transmit seldomly (i.e., one packet per minute) and packets are small (i.e., tens of bytes per packet), and that most use cases tolerate certain latency and packet loss, as IoT deployments become denser (i.e., thousands of devices) the scalability and reliability of communications between the end-device and the network coordinator will become a limiting factor for its success. Given the idiosyncrasies of low-power wireless communications (i.e., propagation and interference), Medium Access Control (MAC) protocols [11] are deployed on top of the physical layer to coordinate access to the wireless channel among end-devices. MAC protocols can be broadly classified into deterministic and random access depending on how they organize transmissions among end-devices that form a network [12]. In deterministic MAC protocols, the network coordinator assigns resources (i.e., time, frequency or code) to each end-device, thus ensuring that they do not collide when transmitting their data packets. Contrarily, random access MAC protocols are based on contention, meaning that end-devices can transmit without central coordination. This approach simplifies implementation and relaxes requirements, but collisions between packets transmitted by end-devices simultaneously may occur. Ultimately, collisions lead to re-transmissions, which may cause congestion and become a hindrance for network scalability, reliability and low-power. Over the years, there have been various works that have studied the limits of low-power wireless communication technologies operating in unlicensed bands and have made proposals to improve their performance and robustness, as well as to reduce the energy consumption of both the end-devices and the network coordinator. Regarding LoRa, the authors in [13] study the limits of the technology, whereas in [14] the authors propose a lightweight scheduling mechanism to improve its performance. Regarding IEEE 802.15.4, in [15] the authors study the effects of multi-path propagation and how to mitigate it using channel hopping, whereas in [16] the authors propose the use of path diversity to further enhance the reliability of these networks. Finally, in [17] the authors study the robustness of three new modulations (i.e., SUN-FSK, SUN-OQPSK and SUN-OFDM) introduced in IEEE 802.15.4g for industrial settings.