# A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
## 1 Introduction  
Increasingly, organizations in many industries are employing the Internet of Things (IoT) to function more efficiently, to understand their customers better, to provide improved customer service, enhance decision-making and boost the value of the business. This has resulted in a considerable upsurge in the number of devices connected to the internet. A \"thing\" in the IoT, can be a patient implanted with a heart monitor, smart home that automatically regulate heating and lighting, a farm animal with a biochip transponder, a smart city or a smart factory monitoring industrial machines searching for glitches, then automatically regulates to avoid breakdowns [1; 2; 3; 4]. These devices need to be capable of getting an Internet Protocol (IP) address assigned to them and possess the ability to transfer data over a network. Low Power Wide Area Networks (LPWAN) is a novel kind of wireless communication, attributed to low power, low bit rate and long-range communication technologies in the unlicensed industrial, scientific and medical (ISM) frequency bands, configured in a star topology network. This makes it suitable for many IoT applications that simply require transmission of small data packets over long distances. LPWAN allows long-range transmission up to ten to forty kilometres in rural environments and one to five kilometres in urban environments [5]. LPWAN is extremely scalable and energy efficient [6]. In the LPWAN space there are contending technologies, for instanceSigfox, NB-IoT and Long-Range Wide Area Networks (LoRaWAN). A comparison of these LPWAN technologies is found in [7]. In this review paper the focus is on LoRaWAN, which exhibits the attributes of straightforward deployment, low power consumption, and long-distance coverage. LoRaWAN is an open LPWAN standard that uses unlicensed spectrum. LoRaWAN is a key technology for the IoTs, suitable for a variety of fixed and mobile IoT applications. An essential LoRaWAN feature is the Adaptive Data Rate (ADR) scheme. The objective of this scheme is to minimize energy consumption and maximize throughput by adjusting the data rate dependent on the link budget for every end node in a LoRaWAN. ADR controls the transmission parameters, namely Bandwidth (BW), Spreading Factor (SF), Transmission Power (TP) and Coding Rate (CR). Optimizing the ADR increases the network capacity since data packets transmitted with different SFs are orthogonal and therefore can be received concurrently, thus reducing airtime. ADR is a mechanism that controls the uplink (UL) transmission parameters of LoRa devices depending on the link budget. The ADR functionality needs to be enabled at the end node for it to be employed. In the LoRa implementations found in the literature, ADR schemes are implemented and evaluated using different approaches such as mathematical models, simulations, and testbeds. The major challenge with the ADR algorithm is that the LoRa specification does not state the way the Network Server (NS) should instruct end nodes regarding rate adaptation. This has resulted in a gap in terms of ADR implementation as vendors keep their implementations private, consequently, many different ADR schemes have been proposed. The surge in IoT deployments results in different quality of service (QoS) requirements, metrics, and implementation approaches, which provide a challenge in the reliability and suitability of the ADR schemes. The main contributions of this paper are as follows:  
* An overview of the LoRaWAN system and its parameters are thoroughly reviewed
* An investigation of the existing ADR schemes that have been proposed in the public domain and an evaluation of how these approaches address the challenges of ADR. * A discussion of the strengths and drawbacks of the proposed schemes. * Finally, the identification of research gaps and potential future direction.