Resource Allocation and Mobility Prediction Algorithms for Multimedia Wireless Cellular Networks

Among the issues the telecommunication industry is the demand for multimedia applications with Quality of Service (QoS) in wireless/mobile networks. In the face of this increasingly complex traffic mix, where each service imposes different requirements, QoS provisioning and guarantee for multimedia services have become increasingly important. This is partially due to the users' requirements and poses a difficult challenge for network service providers. The tasks are more challenging than those in the wired networks due to the shortage of resources and the mobility present in wireless networks. The mobility factor causes severe fluctuations of resource usage. In this research, the QoS provisioning and resource utilization for multimedia services in wireless/mobile networks aspects are addressed. The first proposed scheme is called Adaptive Multi-Class Services Controller scheme (AMCSC). This scheme harnesses the combinations of Call Admission Control (CAC), an Adaptive Bandwidth Allocation (ABA) algorithm with micro-Acceptable Bandwidth Level (micro-ABL) and the Connection Management Table (CMT). The specific objective in designing the AMCSC Scheme is to reduce the New Connection Blocking Probability (NCBP) and the Handoff Connection Dropping Probability (HCDP) by managing resource allocation to address. The insufficient resource problem is experienced by the MTs. This scheme supports multiple classes of non-adaptive and adaptive multimedia services with diverse QoS requirements. The second proposed scheme is a bandwidth reservation scheme based on Mobility Prediction Scheme (MPS). Two proposed MPSs are deployed to predict the mobility movement of mobiles. The first MPS obtains the user mobility information by Received Signal Strength (RSS) which also includes the direction of the MT. This is enhanced based also on the position of the MT within a sector and zones of the cell. The second MPS obtains the user mobility information using the road map information of the cell and the integrated RSS and Global Position System (GPS) measurements. The simulation results show that the proposed scheme enhances the estimation of the target cell. This shown by the reduction of the signalling traffic in wireless cellular networks, reduction of the number of terminated ongoing calls of non-real time traffic and reduction of the number of cancelled reservation due to false reservation. The third proposed framework is an integration of the AMCSC scheme and the bandwidth reservation done based on the MPS. This integration is used to achieve the ideal balance between the users' QoS guarantee of multiple classes of wireless multimedia and maximizing the bandwidth utilization. The performance result of the proposed framework has proven to improve the achieved performance metrics. The performances analysis in this research is discrete simulation. The proposed schemes have proven to enhance the performance in terms of NCBP and HCDP for each type of traffic, management the resource for multiple traffics with diverse requirement, bandwidth utilization and predicting the target cell in the right time and place

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

A Decision-Theoretic Approach to Resource Allocation in Wireless Multimedia Networks

The allocation of scarce spectral resources to support as many user applications as possible while maintaining reasonable quality of service is a fundamental problem in wireless communication. We argue that the problem is best formulated in terms of decision theory. We propose a scheme that takes decision-theoretic concerns (like preferences) into account and discuss the difficulties and subtleties involved in applying standard techniques from the theory of Markov Decision Processes (MDPs) in constructing an algorithm that is decision-theoretically optimal. As an example of the proposed framework, we construct such an algorithm under some simplifying assumptions. Additionally, we present analysis and simulation results that show that our algorithm meets its design goals. Finally, we investigate how far from optimal one well-known heuristic is. The main contribution of our results is in providing insight and guidance for the design of near-optimal admission-control policies.Comment: To appear, Dial M for Mobility, 200

Final report on the evaluation of RRM/CRRM algorithms

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

Admission Control for Multiuser Communication Systems

During the last few years, broadband wireless communication has experienced very rapid growth in telecommunications industry. Hence, the performance analysis of such systems is one of the most important topics. However, accurate systems’ analysis requires first good modeling of the network traffic. Moreover, broadband wireless communication should achieve certain performance in order to satisfy the customers as well as the operators. Therefore, some call admission control techniques should be integrated with wireless networks in order to deny new users/services if accepting them will lead to degrade the network performance to less than the allowed threshold. This thesis mainly discusses the above two issues which can be summarized as follows. First issue is the traffic modeling of wireless communication. The performance analysis is discussed in terms of the quality of services (QoS) and also the grade of services (GoS). Different scenarios have been studies such as enhancing the GoS of handover users. The second issue is the admission control algorithms. Admission Control is part of radio resource management. The performance of admission control is affected by channel characteristics such as fading and interference. Hence, some wireless channel characteristics are introduced briefly. Seven different channel allocation schemes have been discussed and analyzed. Moreover, different admission control algorithms are analyzed such as power-based and multi-classes fuzzy-logic based. Some simulations analyses are given as well to show the system performance of different algorithms and scenarios.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format