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Summary: Cellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs) integrated. In addition to 5G, the user's device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent‐based application in heterogeneous wireless networks and proposed an enhanced particle optimisation (EPSO) algorithm to solve the load balancing problem in 5G‐Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with the Artificial Bee Colony and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed. [ABSTRACT FROM AUTHOR]

In order to provide solution to limited network resources in heterogeneous wireless networks supporting different applications with distinct quality of service (QoS) requirements, call admission control (CAC) schemes are implemented. This work is aimed at investigating three mostpopular CAC schemes employedin mobile worldwide interoperability for microwave access (WiMAX), namely dynamic CAC with bandwidth reservation (DCACBR), QoS-aware CAC (QoSACAC), and QoS guaranteed CAC (QoSGCAC) to identify their shortfalls which will form the focus of future research. A general platform is developed and simulated. The simulation was based on the following KPIs: blocking rate, dropping rate, and throughput for new and handoff connections. Simulation results for new connection shows that QoSGCAC outperforms scheme DCACBR and QoSACAC, having 26.9% and 8.56% improvements in throughput and 63.11% and 24.17% in blocking rate respectively. For handoff connection, QoSACAC showed the best performance having 13.25% and 47.84% improvements in throughput and 6.8% and 49.3% in blocking rate as compared to the DCACBR and QoSGCAC, respectively. Result analysis shows that QoSACAC has the best performance however, it admits new connections and degrade existing connections but failed to consider the delay-intolerant service classes. It is recommended that the QoSACAC be further improved. [ABSTRACT FROM AUTHOR]

Abstract Many network devices, such as a smartphones and tablets, and streaming services, such as YouTube and Netflix, have become widespread. This causes network‐bandwidth congestion, so users require stable and consistent communication quality. Call admission control (CAC) has been proposed to solve these bandwidth resource problems. Some CACs have been proposed in order to maintain QoS. However, these CAC does not assume user behaviour. If CAC assumes some user behaviour, optimal control parameter derived conventional CAC may change because traffic load change by considering user behaviour. This article assumes that arriving types of flows are of three types: narrowband flows, broadband flow without seek‐bar operation, and broadband flows with seek‐bar operation. Under this assumpution, two CAC methods with single threshold or two thresholds are proposed. With these methods, it is assumed that all arriving flows result in the same user satisfaction when accommodated in a network. Under this assumption, the maximum of each user satisfaction is the same as the maximum number of accommodated flows. Using the call loss probability characteristics of Method 1, the objective function in Method 2 is modified. By using the modified objective function, CAC can be realised while properly accommodating broadband users who have been excessively rejected.

Many network devices, such as a smartphones and tablets, and streaming services, such as YouTube and Netflix, have become widespread. This causes network‐bandwidth congestion, so users require stable and consistent communication quality. Call admission control (CAC) has been proposed to solve these bandwidth resource problems. Some CACs have been proposed in order to maintain QoS. However, these CAC does not assume user behaviour. If CAC assumes some user behaviour, optimal control parameter derived conventional CAC may change because traffic load change by considering user behaviour. This article assumes that arriving types of flows are of three types: narrowband flows, broadband flow without seek‐bar operation, and broadband flows with seek‐bar operation. Under this assumpution, two CAC methods with single threshold or two thresholds are proposed. With these methods, it is assumed that all arriving flows result in the same user satisfaction when accommodated in a network. Under this assumption, the maximum of each user satisfaction is the same as the maximum number of accommodated flows. Using the call loss probability characteristics of Method 1, the objective function in Method 2 is modified. By using the modified objective function, CAC can be realised while properly accommodating broadband users who have been excessively rejected. [ABSTRACT FROM AUTHOR]

This paper addresses the traffic’s grade of service indicators: call blocking and dropping rates as well as the optimization of their mutual relation, corresponding to the call admission control procedure configuration. In the presented results of simulations authors showed opportunities for the CAC load threshold adaptation according to the traffic volume and user mobility changes observed in the mobile radio network.

Cellular networks have witnessed an unprecedented expansion represented by the number of subscribers in addition to the unlimited number of applications. In the era of IoT, connections may involve machines working side by side with humans on the same network. Tidal load is one of the key challenges in mobile networks, which represents a temporary phenomenon resulting from increasing traffic volumes at certain times of the day in particular places. This leads to the problem of overutilization of some base stations, particularly in fixed resources allocation systems such as 4G LTE architecture, which contains physically separated base stations. This results in increasing the dropping and blocking probability for the incoming calls in an overloaded area, while others suffer from underutilization or might be almost idle for a particular time. In this paper, an Elastic Call Admission Control (ECAC) approach is proposed to reduce the probability of blocking and dropping to improve the network performance in the tidal load scenario. This is achieved using the concept of gain multiplexing technique and cloud-based cellular architecture for utilizing the shared available recourses of the co-located virtual base stations in the cloud. A Fuzzy Type 2 (FT2) system is used to maintain the switching decision for resource sharing mode, the network load is predicted in advance using Gaussian Process Regression (GPR) model. Performance evaluation is carried out using the cloud-based Fog-Radio Access Network (F-RAN) platform. Compared to legacy LTE architecture, the results illustrate a noticeable enhancement in terms of minimizing blocking probability, enhancing overall network performance represented by network data throughput, and network utilization.

Voice transmission over wireless edge networks is a conventional, cost-effective technology to transmit voice calls over 802.11 edge networks. In this type of service, Session Initiating Protocol (SIP) is responsible for initiating sessions. Research has shown that the call control algorithm that controls SIP sessions can also guarantee the quality of the medium during audio data transmission. In spite of decision-making in wireless access points and changing the parameters of the medium access sublayer (MAC), the existing algorithms are complicated and cannot adequately ensure service quality and efficient use of system resources. Therefore, the purpose of this study is to propose a new algorithm that enables a SIP server to decide to admit or reject an incoming call, in concise time. This algorithm considers the dynamic parameters of the network such as the location of node, channel busyness rate and real-time traffic percentage of the channel without changing the settings of MAC sublayer. The location of each system depending on the access point that transmits the call has a great impact on how the required service is provided. Implementation of this location-aware method on a real network testbed is indicative of remarkable superiority over the recently proposed methods in terms of service quality as measured by parameters, such as response time, call duration, loss-rate, and delay in real-time packets. [ABSTRACT FROM AUTHOR]

Choosing an optimized Internet network by the users and providing a desired network by the internet service providers have always been big challenges in this field. Although there are different approaches for selecting the best set of networks such as Analytic Hierarchy Process, Analytic Network Process, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), choosing a unique optimal solution still remains an open challenge. The purpose of this paper is to use the decision-making techniques of Data Envelopment Analysis in order to evaluate the existing Internet networks so as to select the most desirable networks. Firstly, a specific Internet network called differentiated service network, that provides the quality of service to the user through the mechanism of Call Admission Control, is stimulated. A novel cross-efficiency model is proposed in order to provide a unique ranking of the Internet networks so as to select the optimal network. In particular, secondary goal model based on a satisfaction rate in cross-efficiency is proposed to evaluate and uniquely rank the Internet networks and to select the most desirable network. The present simulated results of 33 networks demonstrate that the proposed model is an effective method for unique ranking of the networks.

Long term evolution (LTE) is a user-friendly network in providing a user requested service, and the growth of LTE is reported exponentially due to the attractive applications. The existence of the huge number of users and a massive presence of user demands in the network raise a question on the Quality-of-Service (QoS). In order to assure the required QoS with the available resources in the network, the paper proposes a call admission control scheme using a fuzzy-based decisive approach. The proposed method works based on the available resources in the network and allocates extra resource blocks when there is a lag in the demanded QoS. The flexible and user-friendly service is assured to three groups of users, for which the users are categorized based on the requested service as soon the service is requested. The simulation environment is developed to perform the fuzzy-based call admission control in LTE such that the results prove that the proposed method outperformed the existing methods in terms of delay, throughput, cell power, and call drops. The delay, throughput, cell power, and call drops using the proposed method are 0.1103 s, 1,294,932 bps, 44.2071 dBm, and 328, respectively. Also, the proposed method has the minimum call blocking probability of 0.0527 and 0.2901 for handoff users and new users. It has the call dropping probability of 0.0528 and 0.3357 for handoff users and new users, respectively. [ABSTRACT FROM AUTHOR]

Cellular networks have witnessed an unprecedented expansion represented by the number of subscribers in addition to the unlimited number of applications. In the era of IoT, connections may involve machines working side by side with humans on the same network. Tidal load is one of the key challenges in mobile networks, which represents a temporary phenomenon resulting from increasing traffic volumes at certain times of the day in particular places. This leads to the problem of overutilization of some base stations, particularly in fixed resources allocation systems such as 4G LTE architecture, which contains physically separated base stations. This results in increasing the dropping and blocking probability for the incoming calls in an overloaded area, while others suffer from underutilization or might be almost idle for a particular time. In this paper, an Elastic Call Admission Control (ECAC) approach is proposed to reduce the probability of blocking and dropping to improve the network performance in the tidal load scenario. This is achieved using the concept of gain multiplexing technique and cloud-based cellular architecture for utilizing the shared available recourses of the co-located virtual base stations in the cloud. A Fuzzy Type 2 (FT2) system is used to maintain the switching decision for resource sharing mode, the network load is predicted in advance using Gaussian Process Regression (GPR) model. Performance evaluation is carried out using the cloud-based Fog-Radio Access Network (F-RAN) platform. Compared to legacy LTE architecture, the results illustrate a noticeable enhancement in terms of minimizing blocking probability, enhancing overall network performance represented by network data throughput, and network utilization. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to use the decision making techniques of Data Envelopment Analysis (DEA) in order to evaluate the existing Internet networks to select the most desirable networks.To achieve this goal, we first begin by simulating a specific Internet network called Differentiated Service (DS) network that provides the quality of service to the user through the mechanism of Call Admission Control (CAC). We then evaluate and rank the networks by proposing a novel DEA model in the literature of undesirable outputs. Finally, by using the results of DEA model, we select the optimal Internet network. [ABSTRACT FROM AUTHOR]

Summary: The International Telecommunications Union defines in its IMT‐2020 recommendations three types of use of 5G services: mMTC (massive Machine‐type Communications), eMBB (enhanced Mobile Broadband), and uRLLC (ultra‐Reliable Low Latency Communications). The mMTC service allows a considerable number of machines and devices to communicate while guaranteeing a good quality of service. The eMBB service allows very high data throughput, even at the cell border. The uRLLC service is used for ultra‐reliable communication for critical needs requiring very low latency. These services are provided separately in a given cell. However, the number of connected objects is starting to increase rapidly as well as the bit rates and energy consumption. The 5G network must make it possible to provide access to a vast number of users of its different service categories. Call admission control (CAC) techniques focus more on availability in terms of bit rate and coverage. In this article, we suggest an algorithm for modeling CAC in an area served by the three categories of services in a 5G access network, mainly based on minimum energy consumption. This technique will allow connected objects that consume low energy to connect to the network with an adequate quality of service and enable the development of the Internet of Things. [ABSTRACT FROM AUTHOR]

Fifth generation (5G) cell frameworks are relied upon to encounter colossal traffic congestion from mobile devices. To decrease network congestion, the 5G cell systems need to be changed to accommodate the soaring traffic demands from these devices. In a 5G network, a cloud-based radio access network (C-RAN) has a significant role to increase the data rate. With the support of C-RAN, traffic congestion in the 5G network is handled by presenting the Call Admission Control (CAC) technique. Although this CAC technique improves the system efficiency, maximum of call blocking probability due to the traffic congestion is the main challenge. So, the solution to this challenge is introducing the optimal call admission decision maker. In this paper, Artificial Fish Swarm Algorithm based Fuzzy Inference System (FIS-AFSA) is proposed as a decision maker. Using AFSA algorithm, the fuzzy parameters are optimized in this strategy. In this approach, few delay tolerant connections are outsourced from private cloud to public cloud with certain price when congestion. The proposed FIS-AFSA based CAC scheme's performance outperforms that of the Fuzzy based CAC technique in the basis of call blocking probability, throughput and resource utilization as show in simulation results. [ABSTRACT FROM AUTHOR]

Abstract In this paper, dynamic and anticipated resource leasing strategies to address the problem of leased resource availability are investigated. Then, network performance analysis is developed, and the performance evaluations of different leasing strategies (namely permanent, dynamic, and anticipated leasing strategies) are provided for some network scenarios. The developed mathematical model additionally considers non-homogeneous bandwidth requirement, where different primary users (PUs) and secondary users (SUs) may require a number of channels. The tradeoff between spectrum leasing cost and system Erlang capacity (defined as the maximum offered traffic for which all the QoS requirements are guaranteed) is also investigated. Specifically, the maximum Erlang capacity is obtained by optimizing the number of reserved channels for different traffic scenarios considering a maximum allowed number of simultaneously rented channels. Also, the minimum achievable cost per Erlang is obtained by considering a fractional number of leased channels. Additionally, the cost per Erlang of capacity as function of both the utilization factor of the primary resources and the maximum allowed number of simultaneously rented channels is evaluated. Numerical results demonstrate that system performance strongly depends on the value of the mean secondary service time relative to the mean primary service time. Also, numerical results show that the cost of leasing a spectrum band is drastically reduced (compared to the permanent leasing strategy) when dynamic spectrum leasing strategies are employed.

This paper deals with the problem of joint multicast routing, scheduling, and call admission control in multiradio multi-channel wireless mesh networks. To heuristically solve this problem, we propose a cross-layer algorithm named "extended MIMCR with scheduling and call admission control phases (EMSC)". Our model relies on the on-demand quality of service (QoS) multicast sessions, where each admitted session creates a unique tree with a required bandwidth. The proposed scheme extends the MIMCR algorithm to fairly schedule multiple non-interfering transmissions in the same time slot. It also exploits a call admission control mechanism to protect the QoS requirements of the multicast traffics. EMSC reduces the number of occupied time slots, with consideration of spatial reuse, both Intra-flow and Inter-flow interferences, and selecting the minimum-interference minimum-cost paths. This subsequently leads to better radio resource utilization and increases the network throughput. Simulation results show that the proposed algorithm outperforms the other algorithms and improves the network performance. [ABSTRACT FROM AUTHOR]

In this paper, we present an analytical framework for the performance evaluation of Radio Resource Allocation (RRA) in Orthogonal Frequency Division Multiple Access (OFDMA) networks. We focus on Quality of Service (QoS) guaranteed traffic whose capacity, in terms of the number of active user connections, depends on the users' QoS requirements and channel conditions, and the RRA algorithm. The required QoS is guaranteed by restricting the number of admitted calls, which in turn requires an accurate estimate of the QoS metrics and capacity supported by the RRA when a new call arrives. These estimates for OFDMA networks are variable and usually obtained through time-consuming offline computer simulations. Mathematical frameworks on the other hand yield timely and accurate results. However, earlier known works on analytical modelling of RRA either consider a single channel with random traffic arrivals or multiple channels with full buffer data traffic. In contrast, we develop a queueing theoretic framework considering randomly arriving QoS-guaranteed traffic in a variable-rate multi-channel multi-class OFDMA network. The framework can be used online leading to better dynamic Call Admission Control. We characterize the RRA algorithm using a scheduler control parameter which can regulate the call blocking probability while providing predefined QoS constraints. We model the RRA as a variable service rate, multi-server, multi-class, finite buffer queueing system and verify the derived QoS metrics using extensive Monte-Carlo discrete event simulations. [ABSTRACT FROM AUTHOR]

Abstract In this paper, teletraffic performance and channel holding time characterization in mobile cognitive radio cellular networks (CRCNs) under fixed-rate traffic with hard-delay constraints are investigated. To this end, a mathematical model to capture the effect of interruption of ongoing calls of secondary users (SUs) due to the arrival of primary users (PUs) is proposed. The proposed model relies on the use of an independent potential interruption time associated with the instant of possible interruption for each ongoing call in every visited cell. Then, a Poisson process is used to approximate the secondary users’ call interruption process due to the arrival of PUs. Based on this model and considering that unencumbered service time (UST) and cell dwell time (CDT) of SUs are independent generally distributed random variables, analytical formulae for both the probability distributions of channel holding times and inter-cell handoff attempts rate are derived. Also, a novel approximated closed-form mathematical expression for call forced termination probability of SUs is derived under the restriction that the UST is exponentially distributed. Additionally, by considering all the involved time variables exponentially distributed and employing fractional channel reservation to prioritize intra- and inter-cell handoff call attempts over new call requests, a queuing analysis to evaluate the call-level performance of CRCNs in terms of the maximum Erlang capacity is developed. The accuracy of our proposed mathematical models is extensively investigated under a variety of different evaluation scenarios for all the considered call-level performance metrics. Numerical results demonstrate that channel holding time statistics are highly sensitive to both interruption probability of ongoing secondary calls and type of probability distribution functions used to model CDT and UST. From the teletraffic perspective, numerical results reveal that the system Erlang capacity largely depends on the relative value of the mean secondary service time to the mean primary service time and the primary channels’ utilization factor. Also, the obtained results show that there exists a critical utilization factor of the primary resources from which it is no longer possible to guarantee the required quality of service of SUs and, therefore, services with hard-delay constraints cannot be even supported in CRCNs.

In recent years, consumers of 4G cellular networks have increased exponentially as they discover that the service is user-friendly. Due to the large users and their frequent demands, it is necessary to use the limited network resources that guarantee the eminent standard quality of service (QoS). Call admission control (CAC) scheme has a major impact in assuring QoS for different users with various QoS requirements in 4G networks. Recently, the reservation-based scheme and bandwidth degradation schemes were proposed with the aim to provide effective use of network resources and assure QoS requirements to admitted calls. However, in spite of these several objectives, these schemes are not efficient as a result of the modeling and approximation method that starve the best effort (BE) traffic. The dynamic threshold value approach adjusts handoff call and new call based on time-varying conditions resulted in a waste of network resources, where bandwidth are reserved for handoff call, but at the network environment, there is little or no handoff calls. In this paper, we propose a novel CAC scheme to provide effective use of network resources and avoid the starvation of BE traffic. The scheme introduces an adaptive threshold value, which adjusts the network resources under heavy traffic intensity. In addition, we proposed reservation and degradation approach to admit many users when there is a limited number of bandwidth, which also achieved effective utilization of network resources. Simulation results show that the proposed scheme significantly outperforms the reservation-based scheme and bandwidth degradation schemes in terms of admitting many calls and guaranteeing QoS to all the traffic types in the network. Numerical results imitate to experimental results with insignificant differences.

The high flexibility of the wireless mesh networks (WMNs) physical infrastructure can be exploited to provide communication with different technologies and support for a variety of different services and scenarios. Context information may trigger the need to build different logical networks on top of physical networks, where users can be grouped according to similarity of their context, and can be assigned to the logical networks matching their context. When building logical networks, network virtualization can be a very useful technique allowing a flexible utilization of a physical network infrastructure. Moreover, dynamic resource management using multiple channels and interfaces, directional antennas and power control, is able to provide a higher degree of flexibility in terms of resource allocation among the available virtual networks, to enable isolated and non-interfering communications while maximizing the network efficiency. In this paper we propose a resource management approach that uses transmit power control algorithm with both omnidirectional and directional antennas, to determine the resources of each virtual network while minimizing interference between virtual networks, considering the support of multiple services and users. Each virtual network can be extended to include the nodes of the WMN required by new users. The results of the proposed approach show that the support of multiple virtual networks for multiple services highly improves the network performance when compared to the support of the services in only one virtual network, with no interference minimization nor dynamic resource control. [ABSTRACT FROM AUTHOR]

In Fractional frequency reuse (FFR) technique, the available physical resource blocks are reused among different cells in a manner that co-channel interference and/or inter-cell interference effect is reduced. However, when the resources are highly utilized, the sharing of these resources becomes exhausted and/or limited, and this leads to a high interference and hence high call blocking probability. Therefore, this paper proposes a call admission control in FFR to improve the performance of the FFR-based cellular system. The results of the two quality of service (QoS) constraints, the call blocking probabilities and the resource utilizations for users are used for some design criteria of the cell inner/outer area to maximize the throughput and hence for the evaluation of the system power efficiency. [ABSTRACT FROM AUTHOR]

DESYNC-TDMA is a self-organizing algorithm based on bio-inspired features used to implement a collision-free MAC. It does not require a global clock or other infrastructures, and it automatically adjusts to the number of participating nodes to ensure that the available bandwidth is always fully utilized. In DESYNC-TDMA the time slots assigned to each node are equally allocated according to the number of nodes, and its slots are allocated one over the number of nodes. It is hard to guarantee the certain level of QoS for certain types of traffic. In this paper, we propose Distributed Call Admission Control (D-CAC) for DESYNC protocol, which is able for nodes to control joining the network with distributed manner. Our scheme needs to add only small amount of bit/flag information to the fire messages of DESYNC protocol. Simulation results showed that D-CAC is able to guarantee a certain amount of allocated slots to send its traffic by control not to join the network if congested.