Two-Dimensional Markov Chain Model for Performance Analysis of Call Admission Control Algorithm in Heterogeneous Wireless Networks

Long Term Evolution (LTE) users with high mobility often experience poor communication issues, such as call dropping and call blocking effects. These issues, which are resulted from the frequent handover, can be mitigated by a call admission control (CAC) algorithm. Located inside the base station (eNB), CAC algorithm is responsible for determining whether to accept or to reject incoming calls. In this paper, a CAC algorithm is proposed to reduce call dropping rate for LTE users who need to handover their calls frequently. The proposed algorithm can also be designed to make the overall system more efficient by accepting more calls with higher priority, specifically, calls with higher quality of service (QoS) requirement and calls with good channel quality.

Elastic threshold-based admission control for QoS satisfaction with reward optimization for servicing multiple priority classes in wireless networks

¿Pseudo congestion¿ phenomenon may happen in heterogeneous networks due to the asymmetry of service resource requirements. A new Call Admission Control (CAC) algorithm based on Inter-Link Load Balance (ILLB) is proposed to avoid the pseudo congestion as well as to improve the network performance. This algorithm aims to balance the Uplink (UL) load and Downlink (DL) load of the heterogeneous networks. Simulation results show that the presented new CAC can decrease the blocking rate effectively compared with the traditional load balance (LB) algorithms.

In this paper, we present a new Call Admission Control (CAC) for IEEE 802.16 broadband wireless networks considering Quality of Service (QoS) constraint. With the assumption that there is a scheduling algorithm to allocate total bandwidths, our proposed CAC algorithm accepts new request for some slot times temporary. In this algorithm, during certain time slots, departure rate for ongoing connections will be decreased and for new connection will increase. After this period, if QoS for ongoing connections and new request is satisfied, new request will be accepted permanently and otherwise it will be rejected. We study the results in two phases, first we show that our algorithm works well with some routine scheduling algorithms and second we show the performance of our algorithm in comparison to some other CAC algorithms. We simulate our algorithm with Matlab tools, and the results show proposed algorithm is quite efficient.

The multimedia stream traffic in a broadband mobile network has the ability of adapting its bandwidth request, which makes the capacity of the network elastic. The call admission control (CAC) algorithm of an adaptive service should keep the user's bandwidth degradation period below a certain upper limit, at the same time, admit as many of the call requests as possible. A new CAC algorithm based on a sliding window is introduced. The simulation result shows that this algorithm can improve the system capacity effectively and can protect the QoS of the adaptive service.

The increasing demand for stringent quality of service (QoS) guarantees and low latency in mission and time‐critical 6G internet of things (IoT) applications necessitates advanced call admission control (CAC) mechanisms. Although 6G networks offer enhanced capabilities, resource limitations like bandwidth and processing power persist. Consequently, efficient resource allocation strategies are crucial to balancing the needs of diverse services, particularly for real‐time streaming applications. This paper introduces a novel Analytics & Fuzzy Call Admission Control (AF‐CAC) algorithm combined with an Adaptive Leaky Bucket (ALB) scheduling mechanism. The AF‐CAC algorithm integrates predictive analytics and fuzzy logic to make informed, intelligent admission decisions, ensuring reliable communication and optimal resource utilization. It prioritizes critical data transmission and prevents network overloading by controlling the number of admitted calls. Concurrently, the ALB mechanism dynamically adapts to changing network conditions, user mobility, and traffic patterns, efficiently allocating resources to meet diverse QoS requirements. The proactive resource allocation is enhanced with a convolutional neural network (CNN) and reinforcement learning (RL) agents, enabling dynamic and efficient resource management to ensure high‐quality multimedia streaming, support mission‐critical applications, and maintain uninterrupted service during mobility. The average throughput for the AF‐CAC technique is 1350 packets/slot, and the average delay over the range of 300 simulated devices is 840 ms. Hence, it exhibits significant enhancements in admitting connections and overall QoS compared to existing approaches for managing multimedia traffic in 6G networks.

Next generation wireless networks will support a diverse set of access technologies. And the demanding breed of multimedia applications will even more considerably require Quality of Service (QoS) support. This paper proposes an optimal prority-based Call Admission Control (CAC) scheme in heterogeneous wireless networks, i.e., the generalized semi-Markov Decision Process based CAC (GCAC). Considering the limitations of the traditional Markov decision process for optimal CAC policy, we characterize the CAC problem through a GSMDP formulation that characterize s the network behaviors in the heterogeneous system more exactly. And the proposed scheme can guarantee the QoS constrains both in the physical and network layer. Numerical examples illustrate that the performance in the GCAC scheme is significantly better than that in the conventioinal GC scheme and an optimal CAC schme based on MDP.

Call admission control plays a crucial role in providing quality of service to the different services in mobile broadband networks (WiMAX, LTE). A new connection is admitted only when the network can support the QoS needs of the connection without degrading the QoS for existing connections. An efficient call admission control algorithm ensures higher throughput and fewer delays for the admitted connections. In this paper a graded priority-based call admission control algorithm is proposed for LTE and WiMAX networks. The number of permissible connections shall be segregated into two classes. The new connection shall be graded, prioritized, and admitted based on the device requesting the connection. Simulation results show that graded priority-based admission control algorithm improves the connection admission rate from 3% to as high as 30% for select users. This results in higher throughput for priority users.

Next generation wireless communication systems target to provide guaranteed quality of service (QoS) for multimedia applications. In this paper, a multiple-threshold bandwidth reservation scheme combined with a call admission control algorithm is proposed and analyzed. The objective of our work is to be able to achieve better QoS provisioning for mobile users while achieving efficient utilization of the available limited bandwidth. The proposed scheme is modelled as M/M/C/C queueing system and the performance measures, call blocking probability and call dropping probability are computed. The performance of our scheme is compared to the complete sharing (CS) policy. Simulation results show that our scheme surpasses the CS policy in terms of call blocking probability, call dropping probability and bandwidth utilization.

We propose a routing mechanism with distributed Call Admission Control (CAC) algorithms for Mobile Ad hoc Networks (MANET) based on IEEE 802.11e EDCA MAC protocol. A new flow can be admitted by the network only if it can find a path to sustain its traffic. Bloom filter is used here to detect the flows via each node, and the CAC routing decisions are made according to the number of flows of each node. Simulation results show that with our distributed CAC algorithm, the existing flows can be well protected in multi-hop MANET; the new added flows can make good use of the bandwidth resources without affecting the neighbor flows. Due to the space-efficient character of Bloom filter, it can be properly used in MANET, whose nodes have limited storage space and computational ability.

Mobility model and call admission control (CAC) algorithm are important for wireless mobility networks. This paper firstly sets a practical mobility model, and then presents a novel measurement-based CAC algorithm utilizing time series analysis under the random model. The algorithm updates the reservation threshold by directly forecasting the next possible number of handoff dropping calls, using ARMA (auto regressive moving average) model. The simulation results suggest that the approach achieves a higher resource utilization than existing approaches while reliably meeting the target handoff-call-dropping probability. Also, the algorithm provides lower new-call-blocking probability.

Decision making is the hot topic in business management. Recently, there have been investigations in Call Admission Control (CAC) to handle the handover events in wireless network environments. Wireless networks have been seen to support different handoff mechanisms, in which the user can switch from one wireless network to another such as from IEEE 802.11 to IEEE 802.16. Many wireless standards, such as IEEE 802.16e and IEEE 802.11, have been proposed to satisfy diverse requirements for mobile users.. Several strategies have been proposed to realize seamless handoff in the heterogeneous networks; in this paper, we analyze the performance of some novel intelligent handoff mechanisms with multiple attributes. The mobile set dynamically selects the optimal network and provides the user with high throughput of Quality of Service (QoS) as to minimize the blocking probability of the system in heterogeneous networks. We evaluate some intelligent handoff mechanisms such as Technique for Order Preference by Similarity to Ideal Solutions (TOPOSIS), Simple Additive Weight (SAW), Analytic Hierarchy Process (AHP) and Fuzzy Logic and Grey Relational Analysis (GRA). From the results, blocking probability and dropping rate can be referenced to support better QoS.

Call admission control for reducing dropped calls in CDMA cellular systems

Dynamic guard margin CAC algorithm with ensured QoS and low CDP in heterogeneous wireless networks

In a heterogeneous wireless network, where many different wireless networks interwork together, call admission control is an important issue to distribute user traffic among different access networks in order to provide quality of service (QoS). In this paper, we present and analyze the performance of a call admission control (CAC) policy for voice and data calls, which is based on one-hop cooperation among the mobile nodes, in a cellular-WLAN interworking scenario. For call-level queueing analysis of the CAC scheme, we use a more general phase-type distribution to model the characteristics of the system. Based on the analytical model, we illustrate the effect of one-hop cooperation on call-level QoS performance (e.g., call blocking probability, call dropping probability).