## 1 Introduction
This method offers additional benefits on increasing the overall network capacity, as messages sent with different spreading factors are orthogonal, so they can be simultaneously received and decoded by a GW [7]. The ADR consists of two independent algorithms, one running on the ED, while the other runs on the Network Server [14]. At the moment, studies related to LoRaWAN networks are continuously taking place in order to help understanding and improving the performance of such deployments. For instance, in [9; 13; 15; 16] it is proposed that by limiting the number of messages sent by each device per day, long power autonomy could be possible. However, this choice limits the range of suitable applications, while at the same time reduces the capacity a LoraWAN network can achieve. Such remarks indicate that an important step before a communication protocol is adopted for deployment in a wireless sensor network (WSN), is the determination of its limits for a specific application under a constrained amount of resources. However, a common problem is that during the dimensioning of a network several questions cannot be clearly answered. For example, what capacity can we achieve with three LoRaWAN GWs in a rural area of 10 square kilometers? Or, how many GWs will we need for such a terrestrial area? In addition, where do we need to place them? Where is it beneficial to place EDs when the locations of GWs are mostly pre-specified due to the ground elevations? How many devices, exchanging payloads with the server every hour or even days following a low data rate scheme, can be successfully deployed? alongway joint problems of GW placement, spreading factor assignment or power allocation are just a few issues that need to be addressed during the planning and deployment of a LoRaWAN network. Some reports [4; 11; 17; 18] even state that the long-term performance of a LoRaWAN is not only a matter of logical and geographical layout but is also impacted by interference from other networks. A fact is that, as ISM bands become more and more congested, LoRaWAN networks may no longer provide their original performance. LoRa deployments will interfere with each other especially in close proximity scenarios [5]. Though, LoRaWAN available configuration parameters, including spreading factors, bandwidth, transmit power and duty cycling could alleviate various problems, but only when configured properly, which itself is a definite challenge. At the moment there are several identified open issues related to LoRaWAN including network management, ADR optimization, high-density LoRaWAN installations and device interoperability [19]. Additionally, most of the existing studies are trying to tackle challenges by leveraging LoRa features to extend the capacity issue, while others designed new relaying or routing protocols or relied on signal processing techniques to cancel the interference issue [20]. conclusively, while several studies on LoRaWAN performance, scalability and security exist, the common problem of how to efficiently plan such a network has not yet received the appropriate attention [9]. At the moment, a lot of interest is taken by researchers on modeling alternative mechanisms for adaptive data rate [1; 14; 21], which, however, could only partially address the scalability performance of a network. We identify that to efficiently deploy someone a LoRaWAN network with optimal performance, he/she needs to overcome issues that deform the trade-off triangle of coverage, scalability and energy efficiency. The scope of this study is to contribute to the alleviation of the dimensioning issue.of large LoraWAN networks. To this end, we, at first, critically reviewLoRaWAN's protocol limitations as they are revealed via the literature, and summarize the factors that affect the performance of such deployments.