## 4 LoRaWAN Issues and Recent Solutions
### Power Consumption  
There are three important characteristics of LPWAN that can meet the key requirements of IoT applications, which are high energy efficiency, large-scale deployment, and low cost. Power efficiency is a major parameter in improving a system's lifetime. This criterion is well met by LoRa networks, where LoRa nodes can operate with minimum maintenance for a longer lifetime of up to 10 years. Among the obstacles for LoRa networking is, therefore, power consumption. The consumed energy of the end devices can be divided into two types: (1) the energy consumption of the micro-controller, which varies according to the chosen host board, and (2) the consumed energy by wireless transmissions, which depends entirely on the LoRa technology and node activity [11]. Many studies have been conducted to improve the power efficiency in LoRa. The proposed solution in [38] is divided into two phases. In the first phase, an improved compressed sensing algorithm known as ISL0 is proposed by using a complicated trigonometric function rather than a Gaussian function for reconstructing network data and reducing the number of LoRa nodes that transmit data, thus avoiding collision and latency. In phase two, a sleep schedule mechanism is proposed for reliable data acquisition with monitoring of the device's status. The network server configures the proposed sleep schedule. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Criteria** & **Class A** & **Class B** & **Class C** \\ \hline Access approach & ALOHA & Slotted ALOHA & ALOHA \\ Collision & High & Moderate & Moderate \\ Time of reception & 2 s if ON & Relay on slot time & Always unless transmitting \\ DL latency & High & Moderate & Low \\ Real-time support & No & No & Yes \\ Most of time state & Sleeping & Beacon & Listening \\ Power consumption & Very low & Low & Moderate \\ \hline \hline \end{tabular}
\end{table} 
Table 2: LoRaWAN device class comparison. Hence, each node executes its sleep interval cyclically. Two modes are involved in the sleep schedule--sleep mode and semi-sleep mode--and the nodes in the semi-sleep mode are selected randomly in each cycle. This method enables the instantaneous detection of abnormal information and duly records the overall network data. The authors claimed that the results showed that the proposed approaches balanced the energy consumption among all nodes and maximized the network's lifetime. The compressed sensing algorithm can substantially reduce the number of LoRa nodes that transmit data concurrently and then decrease the gateway delay, giving LoRaWAN a new idea for penetrating boundaries with the proposed sleep schedule as only being linked to sampling. The compression values and total number of nodes do not affect the network length. The merging of ISL0 algorithms and mechanisms for energy planning greatly improved the lifespan of the network without affecting the impact of the network observation. The authors of [39] proposed three schemes for improving power consumption. The first scheme suggested an algorithm that prevents the collision between two colliding signals and thus recovers entire frames without any loss. The second scheme is a special MAC beacon-based protocol that is used to decode two or more overlapping LoRa signals using a collision resolution technique. The third strategy is to decode an algorithm that slightly disconcerts and overlays the characteristics of a LoRa physical layer as well as the overlays. The simulation results show that the decoding scheme can be further improved by the use of the already offered CRC in each frame under the suggested collision resolution process. Additionally, the simulation findings revealed that significant performance increases in terms of both device energy consumption and throughput were achieved when comparing the ALOHA LoRaWAN protocol with the CR-MAC protocol, as demonstrated by the simulation results. Furthermore, the proposed protocol reduced the delay significantly.