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The value of the location data for the Internet of Things (IoT) devices is undisputed, and today’s radio technologies provide various means to obtain these data. In this paper, we shed light on the utility of the four illustrative radio-based localization techniques, including satellite navigation and the use of BLE, LoRaWAN, and Cat-NB1 communication technologies. First, we instrument a prototype device comprising all these solutions, thus confirming the feasibility of multi-radio– enabled IoT devices supporting localization. Then, we employ this prototype to empirically assess the energy utility of different localization approaches. Our results demonstrate that in terms of energy consumption, the difference between these techniques approaches five orders of magnitude. By conducting a follow-up survey of the relevant research papers, we assess other important performance metrics, such as the operating environment and the required infrastructure, as well as their effect on the localization accuracy. By combining these results, we show that multi-radio– enabled localization solutions are more flexible than those based on a single localization solution and provide space for further optimizations, especially with regards to energy consumption. Development of such devices is an crucial step toward enabling “anytime, anywhere” localization for IoT devices.

While the IoT has made significant progress along the lines of supporting its individual applications, there are many MMTC scenarios in which the performance offered by any single RAT available today might be insufficient. To address these use cases, we introduce the concept of MR-MMTC, which implies the availability and utilization of several RATs within a single IoT device. We begin by offering insights into which use cases could be beneficial and what the key challenges for MR-MMTC implementation are. We continue by discussing the potential technical solutions and employing our own prototype of an MR-MMTC device capable of using LoRaWAN and NB-IoT RATs to characterize its energy-centric performance across the alternative feasible MR-MMTC implementation strategies. The obtained results reveal that an increased flexibility delivered by MR-MMTC permits the selection of more energy-efficient RAT options. The IoT devices capable of utilizing multiple radios simultaneously can thus improve their energy utilization by leveraging the synergy between RATs. The novel vision of MR-MMTC outlined in this work could be impactful across multiple fields, and calls for cross-community research efforts in order to adequately design, implement, and deploy future multi-RAT MMTC solutions.