You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey on the Viability of Confirmed Traffic in a LoRaWAN 
Chapter Title:  3) THE IMPACT OF SFs 
1. Abstract of Cited Paper (BIB001):  Low-Power Wide Area Networks (LPWANs) are continuously gaining momentum as fundamental enablers of the Internet of Things (IoT) paradigm. These networks provide longrange coverage to end nodes, exploiting license-free frequency bands. The focus of this work is on one of the most prominent LPWAN technologies: LoRa™. We implemented a new ns-3 module to study the performance of a LoRa-based IoT network in a typical urban scenario. Simulation results show that a LoRa network can scale well, achieving packet success rates above 95% in presence of a number of end devices in the order of 104. 
2. Abstract of Cited Paper (BIB002):  The need for low power, long range and low cost connectivity to meet the requirements of IoT applications has led to the emergence of Low Power Wide Area (LPWA) networking technologies. The promise of these technologies to wirelessly connect massive numbers of geographically dispersed devices at a low cost continues to attract a great deal of attention in the academic and commercial communities. Several rollouts are already underway even though the performance of these technologies is yet to be fully understood. In light of these developments, tools to carry out `what-if analyses' and pre-deployment studies are needed to understand the implications of choices that are made at design time. While there are several promising technologies in the LPWA space, this paper specifically focuses on the LoRa/LoRaWAN technology. In particular, we present LoRaWANSim, a simulator which extends the LoRaSim tool to add support for the LoRaWAN MAC protocol, which employs bidirectional communication. This is a salient feature not available in any other LoRa simulator. Subsequently, we provide vital insights into the performance of LoRaWAN based networks through extensive simulations. In particular, we show that the achievable network capacity reported in earlier studies is quite optimistic. The introduction of downlink traffic can have a significant impact on the uplink throughput. The number of transmit attempts recommended in the LoRaWAN specification may not always be the best choice. We also highlight the energy consumption versus reliability trade-offs associated with the choice of number of retransmission attempts. 
3. Abstract of Cited Paper (BIB003):  LoRaWAN is gaining momentum in the arena of IoT connectivity technologies thanks to the low cost, ease of deployment, and support for adaptable transmission rates and bidirectional communications. The research community has then been working to develop suitable analytical models that can be instrumental in the study of this technology. In this work we propose a mathematical model that makes it possible to accurately estimate the packet success probability of a LoRaWannetwork in presence of bi-directional traffic, i.e., both uplink (UL) and downlink (DL) transmissions, and that accounts for the most critical features of the LoRa chipset and the LoRaWanstandard. The proposed model, furthermore, makes it possible to study the effect of different parameters configurations, thus offering a valid tool to investigate possible improvements to the system configuration. The proposed model is first validated by comparison with some accurate simulation results and, then, its potential is exemplified by analyzing the system settings that yield the best network performance. 
4. Abstract of Cited Paper (BIB004):  The Internet of Things (IoT) addresses a huge set of possible application domains, requiring both short- and long-range communication technologies. When long distances are present, a number of proprietary and standard solutions for low power wide area networks are already available. Among them, LoRaWAN is a candidate technology supported by many network operators. This paper discusses the possible role of LoRaWAN for the IoT. First, the LoRaWAN technology is assessed experimentally through a set of laboratory and on-field tests, to characterize it from the link-level viewpoint; then, a system-level analysis is performed through simulation, to evaluate the capacity of an LoRaWAN gateway and a multigateway network to serve a large area. Finally, the results are discussed considering a broad set of use cases. 
5. Abstract of Cited Paper (BIB005):  LoRaWAN is a Low Power Wide Area Network technology featuring long transmission range and a simple MAC layer that have favored its adoption and usage in large-scale deployments. While LoRaWAN's main use case consists in unconfirmed sensor data collection, the standard also considers confirmed traffic, enabling control applications and reliable services. Although this feature does have important implications in terms of system settings and performance, it has mostly been overlooked in the literature. To contribute filling this gap, in this paper we provide a mathematical model to estimate the performance of a LoRaWAN gateway serving a set of devices that may employ confirmed traffic. The model also features a set of parameters that can be adjusted to investigate different behaviors of the gateway, making it possible to carry out a systematic analysis of various trade-offs. The accuracy of the proposed model is validated against ns-3 LoRaWAN simulations. 
6. Abstract of Cited Paper (BIB006):  LoRaWAN is an emerging low-power wide-area network (LPWAN) technology, which is gaining momentum thanks to its flexibility and ease of deployment. Conversely to other LPWAN solutions, LoRaWAN indeed permits the configuration of several network parameters that affect different network performance indexes, such as energy efficiency, fairness, and capacity, in principle making it possible to adapt the network behavior to the specific requirements of the application scenario. Unfortunately, the complex and sometimes elusive interactions among the different network components make it rather difficult to predict the actual effect of a certain parameters setting, so that flexibility can turn into a stumbling block if not deeply understood. In this article, we shed light on such complex interactions for a single-gateway (GW) system by analyzing the effect of some built-in features and configurations, including the GW’s limitations in terms of duty cycle and the number of parallel reception paths, the number of allowed retransmissions for confirmed traffic, and the preconfigured data rate used in downlink transmissions. The simulation-based analysis reveals various tradeoffs and highlights some inefficiencies in the design of the LoRaWAN standard. Furthermore, we show how significant performance gains can be obtained by wisely setting the system parameters, possibly in combination with some novel network management policies (e.g., enabling selective prioritization of downlink transmissions at the GW).

Literature Review:
The MATLAB simulator presented in BIB001 also examined the impact of SFs. Their evaluation of the different SFs found that performance is impacted negatively, due to the additional collisions caused by the increase in transmission time from one SF to the next. Their simulator does have some flaws as it assumes perfect SF orthogonality, does not randomise the time interval between retransmissions (ACK_TIMEOUT) and handles ACK transmissions on the second windows differently. In their setup an ACK is always transmitted with the same SF used by their corresponding uplink regardless of the used window, however, the second window normally uses a fixed value, the suggested is SF12. The work presented in  was followed up with the development of a mathematical model for single gateway networks in BIB006 and used to study LoRaWAN in BIB007 . This model was compared with the simulator described in  and BIB002 and was found to match favourably. The impact of using SF12 versus matching the uplink packet's SF was investigated and it was found that by not restricting the gateway more packets could be successfully acknowledged. This effect depends, however, on the traffic volumes. When SF12 is used, the gateway would quickly reach its DC restrictions, keeping it in receive mode. When other SFs are used, the gateway spends more time in transmit mode. Whilst it is thus able to transmit more ACKs, it also missed more uplinks due to the half-duplex nature of the gateway BIB007 . The mathematical model was presented in BIB004 also examined the impact of SFs. Their model assumes perfect SF orthogonality and is for a single gateway scenario. Restricting acknowledgements sent using window 2 to the use of SF12 was found to be sub-optimum, as allowing these ACKs to be sent with the same SF as the corresponding uplink improved network performance as this eases meeting the DC restrictions on the gateway BIB004 . Finally, prioritising reception of packets over the transmission of an ACK resulted in a better PDR. This prioritising was also investigated in BIB006 , who found that this is true of NbTrans is one. Prioritising transmissions will, however, perform better if NbTrans is more than one as this prevents the further retransmission of packets. A further problem highlighted in BIB003 and  , is that the congestion caused by the retransmission mechanism of version 1.0.x networks, detailed in Section III-B. The strategy continually increases the SF used by successive retransmission attempts as it assumes no ACK was received because of distance and does not consider congestion as a cause. Protocol version 1.1 removes this auto-reduction of the used data rate and also allows the number of retransmission to be configurable. The ns-3 simulator presented in  also examined the ADR scheme and found that it tended to assign the same SF to several users and does not consider the resultant loss of SF orthogonality between these nodes. The ACK_TIMEOUT parameter was also evaluated with the simulations performed showing no benefit to this random delay of between one and three seconds. Upon investigation, it was found that collisions occurred amongst nodes using the same SF and that the backoff time is too small for the higher SFs. During retransmissions, the packets would simply collide again as a maximum length SF12 packets take 3.15 s to transmit, which is more than the ACK_TIMEOUT delay. In BIB005 , several IoT use cases were grouped into one of three groups based on traffic considerations. Out of each group, one use case was selected and network throughput and packet success rate analysed via simulation for confirmed versus unconfirmed SF 7 and SF 12. In terms of network throughput, unconfirmed outperforms confirmed traffic, but the authors note that this result should not be viewed in isolation, instead the PDR should also be examined. The authors examined two scenarios: a small area with a single gateway and a large area covered using multiple gateways. In the first scenario, SF 7 confirmed mode outperformed SF 7 unconfirmed mode up to a point whilst in SF12's case unconfirmed mode remained consistently better than confirmed. As throughput and a result congestion increases, confirmed traffic will start to result in more collisions, causing confirmed mode to no longer outperform unconfirmed mode.