717 research outputs found

    Efficient radio resource management in next generation wireless networks

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    The current decade has witnessed a phenomenal growth in mobile wireless communication networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity, ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and handoff calls) generation pattern to enhance the QoS (new call blocking and handoff call dropping probabilities) of the mobile users. The numbers of new and handoff calls in wireless communication networks are dynamic random processes that can be effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed

    Handover Parameter Optimisation of a Cellular Network The Kenyan Case

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    Handover, also known as Handoff is a key procedure that ensures that the cellular users move freely through the network while still being connected and being offered quality services. It is an event taking place whenever a mobile node moves from one wireless cell to another, abandoning the connection with the first base station and getting attached to the second one.  Since its success rate is a key indicator of user satisfaction, it is vital that this procedure happens as fast and as seamlessly as possible. This paper aims to optimize the handover decision process of a cellular radio network for an in-vehicle mobile station. This is first by determining the optimal handover parameters then developing an algorithm that determines the best time to handover using the fuzzy logic system

    Regressive Prediction Approach to Vertical Handover in Fourth Generation Wireless Networks

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    The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A) environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS)/Access Points (APs) in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM) where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities) were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency

    The Performance Evaluation of Adaptive Guard Channel Scheme in Wireless Network

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    Dynamic Guard Channels (DCG) reduces the dropping and blocking rates in a network. However, most of the existing DGC allocations are not quite efficient because there were consideration for only the Handoff (HO) calls while the New calls (NC) were not considered; this leads to poor Quality of Service (QoS) for NC. Although it is better to give priority to HO calls over NC since the breaking of the connection of an established communicationis more annoying than blocking a NC. Thus, there is need to provide an alternative approach that guarantees an acceptable QoS in terms of both the HC and the NC. This paper presents the performance evaluation of an adaptive guard channel allocation; the scheme made use of two different models (1) guard channel with fuzzy logic (2) guard channel without fuzzy logic. Priority is given to handoff call due to the scarcity of radio spectrum. When all the guard channels have been allocated and the arrival rate of handoff calls keeps on increasing, new set of threshold values would be estimated by fuzzy logic model. Performance metrics are; Call Blocking Rate (CBR), Call Dropping Rate (CDR) and Throughput. Results showed that guard channel with fuzzy logic has the CBR values range from 24.02% to 69.015 and CDR values range from 12.025 to 18.90% while guard channel without fuzzy logic has CBR values range from 28.22% to 75.65% and CDR values range from 19.06% to 36.50%. The scheme proved to be more efficient in congestion control in wireless network

    Final report on the evaluation of RRM/CRRM algorithms

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    Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

    An integrated wireless communication architecture for maritime sector

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    The rapid evolution of terrestrial wireless systems has brought mobile users more and more desired communication services. Maritime customers are asking for the same, such as the concepts of “Broadband at Sea” and “Maritime Internet”. Quite a lot of research work has focused on the development of new and better maritime communication technologies, but less attention has been paid on interworking of multiple maritime wireless networks or on satisfying service provisioning. To address this, an integrated wireless Communication Architecture for Maritime Sector (CAMS) has been introduced in this article. CAMS is aimed at 1) granting maritime customers uninterrupted connectivity through the best available network and 2) providing them with the best-provisioned communication services in terms of mobility, security and Quality of Experience (QoE). To address mobility challenge, the IEEE 802.21 standard is recommended to be used in CAMS in order to achieve seamless handover. CAMS provides application-level QoE support attending to the limited communication resources (e.g. bandwidth) at sea. Certain security considerations have also been proposed to supplement this architecture
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