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The Fuzzy Predictor Performance In 5G Mobile Network Using MATLAB   hello guys.. i complted my final project dessertstion.. when i submitted to my professor i got feedback like this There seems to be no MATLAB code and table 3 should be text or an Excel object. Figures 8, 9, 10,11, 12,13, 14 and 15 seem to include legends as pictures, they should be MATLAB fig files or Excel graphics objects and/or the corresponding .fig files should also be submitted. The raw data for the graphs should be included in an appendix. The full code listing should be in an appendix as text (not screenshot(s)). Detail all citations referred to in preparing the code. so i need help in doing Matlab code.. i am attaching the files for which i need matlab code Page | 2 The Fuzzy Predictor Performance In 5G Mobile Network Using MATLAB BY STUDENT ID: STUDENT NAME: TABLE OF CONTENTS ABSTRACT 2 1 INTRODUCTION 3 1.1 Overview 3 1.2 Problem Statement 4 1.3 Aim And Objectives 4 1.4 Research Contributions 5 1.5 The Structure of Thesis 5 2 LITERATURE REVIEW 6 2.1 Overview 6 2.2 Background Study 6 2.3 Literature Review 6 2.4 Summary 9 3 METHODOLOGY 9 3.1 Overview 9 3.2 Methods 9 3.2.1 Cloud Bursting Technique For Pre-empted Connections 9 3.2.2 Structure Of Fuzzy Logic Controller 10 3.2.3 Queueing System For Preempted Connections 12 3.3 Summary 12 4 CONCEPTS: FUZZY, 5G NETWORK, CALL ADMISSION CONTROL, AND C-RAN 13 4.1 Overview 13 4.2 Fuzzy Theory 13 4.3 5G Mobile Network 14 4.4 Cloud Radio Access Networks (C-RAN) 16 4.5 Call Admission Control 17 4.6 Summary 17 5 IMPLEMENTATION 18 5.1 Overview 18 5.2 Proposed CAC Scheme 18 5.2.1 C-RAN Architecture 18 5.2.2 Fuzzy Logic-Based CAC Scheme 19 5.3 Simulation 21 5.3.1 Simulation Environment 21 5.3.2 Simulation Parameter 21 5.4 Summary 22 6 RESULTS AND DISCUSSION 22 7 CONCLUSION 26 REFERENCES 27 ABSTRACT In this study, we will describe the concept of the based on fuzzy logic a CAC scheme on 5G -C-RAN. With the aid of call admission control (CAC), the network congestion may be avoided and along with that, it may avoid traffic congestion in 5G. Besides, the CAC scheme plays a vital role in the guaranteed QoS provision. The CAC algorithms main role is to choose precisely whether an association might be acknowledged into an asset compelled network without abusing the help responsibilities shaped to the generally conceded associations. An efficient CAC scheme may optimize system utilization, and call blocking probability (CBP) as well as call dropping probability (CDP), etc in the 5G network. But, the traditional CAC scheme is not appropriate for 5G C-RAN. The main goal of the thesis is to utilize the fuzzy predictor approach in determining the performance of the 5G network. Another goal of the study is to present a scheme of CAC based on fuzzy logic in 5G C-RAN using pre-emption. The power of 5G technology is that it may able to connect to all sort of devices and also refers as Wireless Broadband Technology. Another powerful feature of 5G technology is that it may offer a high speed along with the capability of handling a large volume of data. 5G technology makes utilization of tiny cells, so it may meet the growing demands of mobile users as well as may offer better connectivity at any time or any place. With the aid of 5G technology, any sort of IoT device may be connected and may be easily cope-up with such applications of IoT. We may attain high data rates as well as low latency owing to having optimized packet radio access as well as flexible bandwidth in the 5G technology. Since the users channel quality may influence the transmission rates, so the user may obtain higher transmission rates along with better channel conditions. If the transmission rates are not appropriate for attaining the demand of users, then users may lose data due to queue congestion. There is a load of devices such as IoT, Tablets, iPhone, Android, Wearable Devices, etc, with a lot of apps producing network requests in 5G networks. To avoid network congestion from such devices, the 5G network needs to cope with such greater traffic requests. In this case, there is a requirement to build an efficient scheme of CAC that could be embraced in 5G C-RAN for improving resource utilization as well as CBP while maintaining the needed QoS. In this study, we will study a scheme of CAC using fuzzy logic in 5G C-RAN using pre-emption. In this paper, we will explain three techniques covering Cloud Bursting For Pre-Empted Connections, Fuzzy Logic Controller Structure, And For Preempted Connections – Queueing System. In the cloud bursting for pre-empted connections, the operators are allowed to extend dynamically their infrastructure by renting 3rd party sources. In the case of fuzzy controller, three inputs are involved: (a) Network Congestion Factor – Nc. (b) Available Capacity – Ac. (c) Effective Capacity – Ec. And, the yield is represented by Admittance Decision – Ad. The fuzzy controller involves three aspects covering Membership function, Fuzzy rule base, and the method of defuzzification. The next thing that has been covered in the methodology part is the M/M/c/K model. In the cloud, the connections follow the Erlang B Model or M/M/c/K. In this case, the Poisson process aids in governing the request arrival at arrival rate λ, as well as the times of the service with parameter μ are exponentially distributed, as well as in the cloud processing the requests, there are c servers from the front of the queue. The system capacity is denoted by the K variable. In this case, the requests for connection greater than the queue length are dropped as well as the buffer is assumed to be of finite size. With the aid of the Markov Chain with continuous time, the model may be described. In this paper, the research will let you know how the network congestion may be avoided with the aid of call admission control and how it may avoid congestion in traffic in 5G. Here, the study will explain how the CAC scheme will assist in deciding accurately whether a connection may be admitted into a resource-restricted network without the commitments of the service violation formed to the admitted already connections. In this thesis, we will estimate the performance of the 5G network via fuzzy logic CAC scheme. INTRODUCTION Overview Nowadays, a lot of improvements in the telecommunication sector are being witnessed owing to advancements in technologies. Starting from the 2G network to date to the 4G networks, a lot of improvements have been observed in the network. Now, it is time to launch of 5G network which is now about to launch and several firms are preparing themselves to launch it. The power of 5G technology is that it may able to connect to all sort of devices and also refers as Wireless Broadband Technology. Another powerful feature of 5G technology is that it may offer a high speed along with the capability of handling a large volume of data. 5G technology makes utilization of tiny cells, so it may meet the growing demands of mobile users as well as may offer better connectivity at any time or any place. With the aid of 5G technology, any sort of IoT device may be connected and may be easily cope-up with such applications of IoT. We may attain high data rates as well as low latency owing to having packet radio access with optimized value as well as flexible bandwidth in the 5G technology. Until the rates of the transmission are provided, the data addressed to mobile users get stored at the base station in the queues in the 5G system. Since the users channel quality may influence the transmission rates, so the user may obtain greater transmission rates along with better channel conditions. If the rates of the transmission are not appropriate for attaining the demand of users, then users may lose data due to congestion of the queue. So, the algorithms of the flow rate control may be applied at the base station to arriving network traffic flows, therefore offer more ample service to mobile users. When the flow rate control algorithm is applied to 5G technology, the smaller size queue may be attained at eNodeB, thus leading to obtaining lower loss rates as well as shorter waiting times for users. Nowadays, the demands for high data rates and larger system capacities have much enhanced in high mobility environments over large coverage areas. This has resulted owing to the utilization of multimedia services as well as a load of mobile devices in recent years. So, it is becoming much hard to manage or control the radio access networks (RAN) owing to their growing size. Some of the major challenges for next-generation systems are optimizing resource utilization or maintaining the quality of service (QoS) non-real-time as well as for real-time. Millions of devices form the 5G cellular networks including IoT, Tablets, iPhones, Androids, Wearable Devices, etc, and such devices are further connected to the network with an immense app. Such devices need to avoid traffic congestion as well as network overload in the core network generating from traffic requests which the 5G network needs to cope with it. To solve the shortcomings of conventional RAN via pooling resources of BS to a centralized cloud, a concept of C-RAN was introduced in the next-generation technology that is 5G. In the BBU pool, BS processing resources are allocated dynamically to distinct virtual baseband units by introducing the concept of virtualization on general-purpose processors. With the aid of call admission control (CAC), the network congestion may be avoided and along with that, it may prevent congestion in traffic in 5G. Besides, the CAC scheme plays a prime role in the guaranteed QoS provision. The CAC algorithms main role is to decide accurately whether a connection may be admitted into a resource-restricted network without service commitments violating formed to the already admitted connections. An efficient CAC scheme may optimize system exploitation, call dropping probability (CDP), as well as call blocking probability (CBP), etc in the 5G network. But, the traditional CAC scheme is not suitable for 5G C-RAN. Here are lists of several reasons for the unsuitability of the conventional CAC scheme in the 5G network. First, due to the time-varying parameter nature (for instance – available power, channel conditions, direction, location, speed, etc.) and radio signals real-time processing, the traditional approach of CAC suffers uncertainties in the cellular network. If the network is indeed servicing incapable the request as well as incorrect rejection, then the traditional CAC scheme may lead to incorrect request admission. The static state of information in the network is assumed by such sort of CAC schemes. But, the network is dynamic as well as values measured keep altering in practice. Second – It is the standalone RAN base station on which the traditional CAC scheme is based whereas 5G will be based on centralized cloud BS’ss. Such BS’s have computation resources as well as unshared processing situated in the BS cell sites along they are preconfigured for peak load. Such BSs resources may not be shared for addressing varied traffic requirements on other cell sites, thus causing high CDP as well as CBP, or poor resource utilization. So, an efficient CAC scheme is needed in such cases. In cellular networks, the issue of uncertainties and imprecision may be solved through the method of intelligent schemes of the CAC based on intelligent decision-making that is also a promising solution. Without the requirement for complex modeling of mathematical, the schemes mimic the behavior cognitively of the human mind, thus making them suitable, flexible, less complex, or adaptive for coping with rapidly altering network situations of cellular networks in 5G. In this study, a scheme of CAC in 5G C-RAN based on fuzzy logic using pre-emption has been presented. In this paper, the research will let you know how the network congestion may be avoided with the aid of call admission control and how it may avoid congestion in traffic in 5G. Here, the study will explain how the CAC scheme will assist in deciding accurately whether a connection may be admitted into a resource-restricted network without the commitments of the service violation formed to the admitted already connections. In this thesis, we will estimate the performance of the 5G network via fuzzy logic CAC scheme. Problem Statement Here is the description of the problem statement. There is a load of devices such as IoT, Tablets, iPhone, Android, Wearable Devices, etc, with a lot of apps producing requests to the network in 5G. To avoid network congestion from such devices, the 5G network needs for coping with such higher requests of traffic. In this case, the question to be answered is how to build efficient schemes of the CAC that could be embraced in 5G C-RAN for improving resource utilization as well as CBP while maintaining the needed QoS. Aim And Objectives Aim – The paper aims to utilize the fuzzy predictor approach in determining the performance of the 5G network. Another goal of the study is to present a scheme of CAC in 5G C-RAN in fuzzy logic-based using pre-emption. Objectives – Various Objectives are: · Understanding the concept of 5G · Understanding the fuzzy logic approach · Utilizing the proposed system for mitigating the congestions and thus maintaining the energy optimization · To develop a simulated environment for attaining the goal of performance · Using MATLAB for evaluating the performance and understanding how it happens. Research Contributions Here are the contributions of the research areas: a) In this study, a fuzzy logic-based scheme of the CAC in 5G C-RAN using pre-emption is proposed. The main task of fuzzy logic is to prevent uncertainties in RAN distributed systems caused by traditional schemes of the CAC. b) Another technique is proposed called cloud bursting. NRT connections with Low priority as well as delay-tolerant are pre-empted as well as outsourced at a certain price penalty to a public cloud for accommodating the RT connections during congestion. Here, it is considered that the infinite processing capacity is carried out by the public cloud as such it will not be captured in the simulation or it may not get congested. c) For validating the proposed scheme, a rigorous study of the simulation is conducted that exhibits a significant performance improvement. The Structure of Thesis Now, we will appraise you the organization of the thesis. This will aid you in knowing what would be covered in the thesis in the stepwise manner which is described as follows. S.No. CHAPTER DESCRIPTION 1 Chapter – 1: Introduction The section describes a brief overview of the fuzzy predictor in the 5G technology and along with this, here will cover the problem description of the thesis, its aim and objectives, and contributions of the thesis as well. 2 Chapter – 2: Literature Review In this section, a brief overview of some literature reviews presented by various researchers will be covered. 3 Chapter – 3: Methodology The section covers the methodology part including Cloud Bursting For Pre-Empted Connections, Fuzzy Logic Controller Structure, And Queueing System For Pre-empted Connections, etc. 4 Chapter – 4: Concepts – Fuzzy, 5G Network, Call Admission Control The section covers a few concepts related to the thesis involving fuzzy theory, 5G mobile networks, cloud radio access networks (C-RAN) along call admission control. 5 Chapter – 5: Implementation Here, we will explain the simulation of the proposed method. 6 Chapter – 6: Results And Discussion Here, we will discuss the obtained results through simulation of the proposed system. 7 Chapter – 7: Conclusion Finally, we will summarize the entire concepts covered in this thesis. LITERATURE REVIEW Overview The section covers some of the theories or proposed systems that had been presented by various researchers. Here, we will come to know what advancements have been presented by various researchers in the past or present. Let present the details as follows. Background Study 5G technology is now about to come and many researchers are still working on it for getting improved services. There is a load of devices such as IoT, Tablets, iPhone, Android, Wearable Devices, etc, with a lot of apps producing network requests in 5G. To avoid network congestion from such devices, the 5G network needs for coping with such greater requests of traffic. With shared baseband processing, requests from mobile devices are processed as C-RAN has been assumed as a paradigm shift for 5G. The technique of call admission control has been recently overlooked by the community, despite it being one of the radio RRM methods for avoiding congestion in the network. There are two aspects such as overall system efficiency as well as for individual connections the quality of service (QoS), etc on which the CAC method in 5G c-RAN has an influence directly on the quality of service (QoS). In the subsequent sections, we will present some of the theories related to the concept that had been presented in the past or present. Here are some of the literature reviews of various researchers as follows. Literature Review Here are some of the latest theories related to the topic presented by various researchers are as follows. (Al-Maitah et al., 2018) The researchers had described a hybrid approach in the 5G network for call admission control. There are several issues such as practical, technical, scientific issues, etc that may be solved by employing artificial intelligence. The techniques of AI such as evolutionary algorithms, genetic algorithms, fuzzy systems, or neural networks, etc that may be widely utilized for prediction, optimizations, or communication system management. In a cellular network, optimized results may be obtained with the aid of AI in the challenging task of traffic prediction, routing, handover, or call admission control, etc. In 5G, a significant need of it is accommodating the quality of service satisfaction as well as the great number of users as they are designed as heterogeneous networks. In offering the desired service quality, as well as call admission control plays a vital role. To optimize the cellular network, effective call admission control methods are required. Several methods of call admission control had proposed. In this thesis, the researcher had proposed a method for building a genetic neuro-fuzzy controller in 5G networks for call admission. With the aid of computer simulation, the performance of the proposed methods had been evaluated. (Sigwele et al., 2017) The researcher had explained the call admission control based on fuzzy logic in 5G networks cloud radio access with pre-emption. There are millions of devices (for instance – IoT, Tablets, iPhone, Android, Wearable Devices, etc.) that will be connected to 5G networks. And, such devices will also generate an immense apps network request. To avoid network congestion from such devices, the 5G network needs to cope with such greater requests of the traffic. With shared baseband processing, requests from mobile devices are processed as C-RAN has been assumed as a paradigm shift for 5G. The technique of call admission control has been recently overlooked by the community, despite it being one of the RRM methods for avoiding congestion in the network. There are two aspects such as overall system efficiency as well as for individual connections the quality of service (QoS), etc on which the CAC method in 5G C-RAN has an influence directly on the QoS. (Umoh et al., 2018) In this paper, the author had presented a method for controlling based on interval type-2 fuzzy logic of Mamdani fuzzy inference deployed for modeling connection admission control in 4G networks for improving quality of service. Based on major system parameters such as user mobility, signal strength, load, packet loss, or latency, etc, the researcher had assumed the suitable parameter selection for attaining connection admission control. In the proposed system, the author had also explored the utilization of approaches such as Wu-Mendel and Karnik0Mendal. In 4G networks for comparison purposes, the researcher had implemented a T1FLS connection admission control for guaranteed QoS. The author had utilized 4G network admission control synthetic datasets for the empirical comparison on the designed system. (X Yang et al., 2007) With multiple classes of traffic, the researcher had solved the CAC in the multimedia cellular network using a novel learning approach. A form of algorithm of neuro-evolution had utilized by the researcher for obtaining the near-optimal CAC policy. While retaining an acceptable CBP, the technique guarantees that the CDP remains under a pre-defined upper bound. Since the info of the scheme, internal working is never known as the scheme is a black box learning approach. (Mohammed et al., 2017) A call admission control algorithm along with a dynamic QoS-aware for mobile networks had explained by the researcher. In mobile broadband networks, one of the significant components of the scarce management of wireless network resources is the call admission control. In this paper, a method was proposed by the researcher for improving the resource utilization as well as ensuring QoS for all classes called QACAC-BR-BD). To find whether the number of resources attained from the degradation will be enough for employing DQACAC, a pre-bandwidth degradation method was employed by the DQACAC. When resources are insufficient, a dynamic BD mechanism by the algorithm for degrading distinct resources amount from existing connections. The proposed algorithm efficiency was assessed by conducting an extensive simulation demonstration. In terms of mitigating the new connections blocking probability, the proposed scheme outperforms what was indicated by the simulation results. Thus, observed an efficient utilization of resources. (Kumar et al., 2019) For next-generation mobile multimedia networks, as well as call admission control based on Neuro-fuzzy was proposed by the researcher. To attain extremely consistent data transmission as well as wireless communication over the networks, wireless networks still require advancement in terms of user mobility, efficient bandwidth utilization, link availability, reliable traffic performance, etc as the demands of the mobile users are enhancing day by day. A high-speed network, as well as a call admission control scheme, is needed owing to the evolving demand for services of multimedia that not only guarantee optimum utilization of resources but also offer the quality of services for new as well as handoff calls. In this paper, a decent resource allocation approach was utilized for improving QoS which was the main goal of this integrated neural CAC scheme based on the fuzzy system. The method proposed by the researcher had integrated the self-training capacity of a NN and the semantic rule ability of fuzzy logic. As contrasted to fuzzy logic-based CAC as well as existing schemes of CAC, a neural fuzzy-based CAC may attain maximum resource utilization as well as minimal call dropping probabilities as concluded by the simulation results. (Mamman et al., 2020) In this paper, the author had discussed an efficient dynamic call admission control for 4G Or 5G networks. As the 5G network is a flexible, reliable, efficient, or faster network, but the present 4G network does not allow the variety of services for the future need. The best certainties that describe the elementary principles of the smart cities of the upcoming 5G technology are the call admission control and the 5G network. Communication will be granted based on cost, speed, or latency through substantial CAC in the smart cities environment. Since the adaptive threshold value utilized for determining the network strength, so the present CAC algorithm suffers from performance deteriorates under the 4G network. For addressing performance deterioration, a novel CAC algorithm that utilizes dynamic threshold values in the 5G network for smart cities was proposed. The proposed algorithm efficacy was evaluated using the simulation and performed better as indicated through the simulation results. (Aguodoh et al., 2018) The researcher had utilized the intelligent agent for improving an optimized call admission control in the 3G network. As a result of high bit error rate, inefficient, inference, or congestion to control the situations such as issues of not having free network had arisen. In this paper, the author had improved optimized call admission control using the intelligent agent. Using the following aspects such as designing a model for improving an optimized call admission, designing a membership function for improved call admission control, determining queueing priority scheme, determining channel allocation by reducing the bit error rate, determining the channel capacity, etc in the 3G network using the intelligent agent. (Ojieabu et al., 2017) Based on the higher-order Markov model, the researcher had explained call admission utilizing probability techniques and constraints optimization. Distinct radio access technologies will operate together in the next-generation wireless network. One prime challenge in NGWN is RRM. One RRM method is the call admission control that plays an instrumental role to ensure the desired QoS working on distinct apps. In the prevailing circumstance, one of the big challenges to be addressed is the available channel capacity distribution amongst the multiple traffic with distinct bandwidth needs to guarantee the QoS needs of the traffic. In this study, the researchers had assumed three classes of traffic having distinct QoS needs. From the performance model, optimistic yields were attained. (Roy et al., 2020) In this paper, the researcher had utilized call admission control for studying system resource management as well as the dynamicity of call management. In wireless or cellular networks, the key element in the guaranteed QoS provision is the call admission control. The author had presented a CAC scheme based on factors such as adaptively to traffic conditions or distributed control and with a focus on dynamic reservation schemes by considering handoff prioritization. For providing guaranteed QoS and better system resource utilization, the author had solved the basic drawback of the bandwidth reservation approach for a distinct type of call. (Dewanand et al., 2017) In this paper, the author had proposed a system using call admission control for voice-over LTE. 4G technology is also called LTE (Long Term Evolution). Voice data may be transmitted over the LTE network with the aid of a new protocol called voice over LTE. Using call admission control in the voice-over LTE is an extension to the existing VoLTE protocol. When the total bandwidth amount of a system is reserved for high-priority calls then VoLTE CAC is utilized in cellular networks. The call admission control system assumes an ongoing call if a new call request arrives in a cell. During the handoff calls, the research yields the clarification for major call drops in communication, by decreasing call blocking probability as well as call dropping probability. In this thesis, the author had improved the CBP considerably over a large range of handoff rates the traffic model irrespective as well as a pattern of the mobility. Using call admission control, QoS needs in the network are dealt also with within the voice-over LTE. Summary A few highlights of the researches that have been explained in this section are as follows. The author had improved the CBP considerably over a greater range of handoff rates in the traffic model irrespective as well as mobility pattern. Using call admission control, QoS needs in the network are dealt also with within the voice-over LTE. To optimize the cellular network system, effective call admission control methods are required. Several methods of call admission control are proposed. The researcher had proposed a method for building a genetic neuro-fuzzy controller for call admission in 5G networks. To avoid network congestion from such devices, the 5G network needs to cope with such greater requests of the traffic. With shared baseband processing, requests are processed from mobile devices as C-RAN has been assumed as a paradigm shift for 5G. The researcher had utilized the intelligent agent for improving an optimized call admission control in the 3G network. The author had presented a CAC scheme based on factors such as adaptively to traffic conditions or distributed control and with a focus on dynamic reservation schemes by considering handoff prioritization. METHODOLOGY Overview The section covers the methodology part. It will explain what methodologies will be followed for attaining the goals. Under the methodology section, three techniques will be covered including Cloud Bursting For Pre-Empted Connections, Fuzzy Logic Controller Structure, And Queueing System For Preempted Connections, etc. Lets get into details of each technique which is as follows. Methods Cloud Bursting Technique For Pre-empted Connections With the aid of the method of cloud bursting, the operators are allowed to extend their infrastructure dynamically by renting 3rd party sources. Figure 1 exhibits the model of cloud bursting. When the cloud is congested and a high priority RT connection arrives during the C-RAN infrastructure congestion of the operator, two things occur: a) If no NRT connections for pre-empting in the C-RAN of the operator, then the RT connection is dropped. b) If NRT connections with low priority are pre-empted from the C-RAN of the operator, then it burst into the public infrastructure of C-RAN for accommodating the RT connections with greater priority. Since the RT connections are delay-sensitive, so they are never outsourced to the public cloud. But, the NRT connections may be outsourced to the public cloud. For some NRT connections outsourcing, an agreement is done between the public cloud operator as well as the operator as well as charged some price as well. The NRT connection is forwarded for the public cloud along with …