A Classification of Cross-Layer Optimization Approaches in LoRaWAN for Internet of Things

The Internet of Things (IoT) uses Low-Power Wide Area Networks (LPWAN) for applications that require long-range, energy-efficient, and low-cost end devices. LoRaWAN is one of the most popular LPWAN technologies because of its key features and openness making it highly suitable for IoT. Despite its exceptional features, some challenges faced by this technology are optimizing the protocol used for scheduling, low data rate, and duty cycle restrictions. One possible way to address these challenges is by using cross-layer optimization. This optimization technique violates the restrictions of the traditional OSI protocol stack giving freedom to its protocol layers. However, there is currently no summary of cross-layer methods implemented in LoRaWAN. This paper presents a classification of state-of-the-art cross-layer approaches that were used in optimizing the LoRaWAN technology in IoT. The cross-layer techniques were classified based on the merging of adjacent layers, direct communication between layers, and completely new abstractions. In addition, this paper identified the issues and challenges featured in these state-of-the-art cross-layer approaches. Finally, this paper serves as an overview of the performance of cross-layer optimization in LoRaWAN technology for IoT applications.