## 5 Further Challenges and Solutions in 5G and LPWAN-IoT
### QoS/QoE Challenges and Solutions in 5G and LPWAN-IoT  
Quality of Service (QoS) takes into account features such as throughput, latency, etc., of a telecommunications service that bears on its ability to satisfy the stated and implied needs of the user of the service. The International Telecommunication Union (ITU) defines Quality of Experience (QoE) as \"the degree of delight or annoyance of the user of an application or service\" [91]. QoS involves objectives and thresholds based on technical needs for applications. In QoS, Applications will become much more adaptive to network conditions than today by machine learning (ML) and artificial intelligence (AI) techniques. QoE is based on Experience, i.e., experience on Expectation. In QoE, Expectations will change with new and evolving applications over time [92].  
Figure 8: 5G network endogenous defense security architecture (adapted from [26]).  
5G is meant to virtually connect everyone and everything with different services in different industries. But different services in different industries require different Quality of Service (QoS)/Quality of Experience (QoE), should we use one physical network or multiple physical networks to satisfy requirements? The answer is one physical network [93]. Hence, 5G can be implemented with a new technology such as SDN/NFV to provide cost-effective and flexible service for the different industries with varying end-user QoS/QoE. This will help to determine and prioritize the instantaneous level of services in the network for prime performance. Network slicing which involves the slicing of virtual networks based on different QoS can be used to satisfy different services. The 5G network slicing is based on SDN/NFV. Consequently, research involving network slicing will help to solve the problem of QoS/QoE encountered by the users. Some works related to QoS and/ or QoE in 5G and LPWAN for IoT solutions have been advocated. For instance, the authors in [10; 19] opened that network congestion due to massive MTC and huge traffics will lower the QoS and IoT performance. They also advocated the need for a lightweight context-aware congestion control (CACC) mechanism that will enable IoT networks to mitigate the consequences of traffic congestion for better QoS.  
The authors in [19] advocated that non-orthogonal multiple access (NOMA) for 5G access networks can be applied to support various quality of service (QoS) requirements for different types of end devices. They opined those technologies operating on licensed bands achieve QoS management, but the greatest disadvantage is cost due to licensed spectrum acquisition. The authors in [12; 94; 95] explained that NB-IoT employs a licensed spectrum and an LTE-based synchronous protocol, which are best for QoS at the expense of cost. Considering the tradeoff in QoS and cost, they revealed that NB-IoT is preferred for applications that require guaranteed QoS, but applications that do not have this constraint should choose LoRa or Sigfox. [PERSON] et al. [96] explained that network QoS and user QoE needs to be jointly considered. They illustrated the concept using a highly localized scenario, in which precise tracking of users and objects is critical. Thus, failing to locate objects precisely results in degraded QoE even though QoS requirements might be satisfied. [PERSON] et al. [97] also pointed out that QoE may be further improved by emotional feedback according to where 5G and mobile cloud computing has reconsidered resource cognition and emotion-aware action feedback.