2,120 research outputs found
Capacity Improvement and Analysis of VoIP Service in a Cognitive Radio System
Abstract-We herein analyze the capacity of voice over IP (VoIP) and propose a new method for finding the minimum detection and false-alarm probabilities to ensure the quality-of-service (QoS) requirement of VoIP users in a cognitive radio system. We propose a model for the system supporting the VoIP service as a 2-D discrete-time Markov chain (DTMC). The VoIP traffic and wireless channels in the cognitive radio system are described as a Markov-modulated Poisson process (MMPP) model and a Markov channel model, respectively. In addition, we introduce a simple spectrum-sensing model based on energy detection. By means of the DTMC approach, we demonstrate various analytical and simulation results under the constraint of imperfect spectrum sensing, such as the packet dropping probability, average throughput, and VoIP capacity
Performance of LTE network for VoIP users
With the arrival of LTE standard, it is expected that the mobile voice services paradigm will shift from the circuit switched to fully packet switched mode supporting the VoIP services. VoIP services took quite a bit of time before they were accepted as the main stream telephony service in the fixed networks. To provide VoIP services over the LTE networks with appropriate QoS, it is necessary to analyse the performance of such services and optimise the network parameters. This paper analyses the performance of VoIP services on the LTE network using the FD and the SMP packet scheduling techniques. This work identifies and analyses the features of above LTE packet scheduling techniques to enhance the QoS of VoIP services. An OPNET-based simulation model is used to analyse the performance of VoIP services on the LTE network by incorporating G.711 and G.723 speech coders. The work also studied the performance of VoIP services in variable transmission channel conditions
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Radio network management in cognitive LTE-Femtocell Systems
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application
platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell
base stations, a large portion of the assigned spectrum is used
sporadically leading to underutilisation of valuable frequency resources.
Novel spectrum access techniques are necessary to solve these current spectrum
inefficiency problems. Therefore, spectrum management solutions should have
the features to improve spectrum access in both temporal and spatial manner.
Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered
to be the key technology in this research in order to increase the spectrum
efficiency. This is an effective solution to allow a group of Secondary Users
(SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at
no interference.
The core aim of this thesis is to develop new cognitive LTE-femtocell systems
that offer a 4G vision, to facilitate the radio network management in order to
increase the network capacity and further improve spectrum access probabilities.
In this thesis, a new spectrum management model for cognitive radio networks is
considered to enable a seamless integration of multi-access technology with
existing networks. This involves the design of efficient resource allocation
algorithms that are able to respond to the rapid changes in the dynamic wireless
environment and primary users activities. Throughout this thesis a variety of
network upgraded functions are developed using application simulation
scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system
models are not restricted in the considered networks, but rather have a wider
applicability to be used in other technologies.
This thesis mainly investigates three aspects of research issues relating to the
efficient management of cognitive networks: First, novel spectrum resource
management modules are proposed to maximise the spectrum access by rapidly
detecting the available transmission opportunities. Secondly, a developed pilot
power controlling algorithm is introduced to minimise the power consumption by
considering mobile position and application requirements. Also, there is
investigation on the impact of deploying different numbers of femtocell base
stations in LTE domain to identify the optimum cell size for future networks.
Finally, a novel call admission control mechanism for mobility management is
proposed to support seamless handover between LTE and femtocell domains.
This is performed by assigning high speed mobile users to the LTE system to
avoid unnecessary handovers.
The proposed solutions were examined by simulation and numerical analysis to
show the strength of cognitive femtocell deployment for the required
applications. The results show that the new system design based on cognitive
radio configuration enable an efficient resource management in terms of
spectrum allocation, adaptive pilot power control, and mobile handover. The
proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture.
Eventually, this research shows that certain architectures fulfilling spectrum
management requirements are implementable in practice and display good
performance in dynamic wireless environments which recommends the
consideration of CR systems in LTE and femtocell networks
Quality of Service Oriented Access Point Selection Framework for Large Wi-Fi Networks
This paper addresses the problem of Access Point (AP) selection in large Wi-Fi networks. Unlike current solutions that rely on Received Signal Strength (RSS) to determine the best AP that could serve a wireless user’s request, we propose a novel framework that considers the Quality of Service (QoS) requirements of the user’s data flow. The proposed framework relies on a function reflecting the suitability of a Wi-Fi AP to satisfy the QoS requirements of the data flow. The framework takes advantage of the flexibility and centralised nature of Software Defined Networking (SDN). A performance comparison of this algorithm developed through an SDN-based simulator shows significant achievements against other state of the art solutions in terms of provided QoS and improved wireless network capacity
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