Mobile Networks

The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

Resource management in QoS-aware wireless cellular networks

2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost

Mobility and resource management for 5G heterogeneous networks

The conventional topology of current cellular networks is a star structure, where central control points usually serve as base stations (BSs). This provides the advantage of simplicity while still providing quality of service (QoS). For next-generation networks, however, this topology is disadvantageous and difficult to use due to the insufficient availability of network access. The hybrid topology radio network will thus naturally be the future mobile access network that can help to overcome current and future challenges efficiently. Therefore, relay technology can play an important role in a hybrid cellular network topology. Today, with the recent long-term evolution-advanced (LTE-A) standards, the 3rd Generation Partnership Project (3GPP) supports a single-hop relay technology in which the radio access link between the BS and users is relayed by only one relay station (RS). With the help of multi-hop relay, however, the radio link between the BS and users can be extended to more than two hops to improve the coverage and network capacity. Multiple hops to transmit data to and from the corresponding BS results in the reduction of path loss. However, using a multi-hop relay system requires more radio resources to transmit data through different hops. More interference is also created due to a greater number of simultaneous transmissions in the network. New mobility and resource management schemes are thus important for achieving a high QoS while increasing the whole network capacity. In the first part, the problem of relay selection and radio resource allocation is studied, and choosing how the bandwidth should be shared between direct, backhaul, and access links in multi-hop relay networks is discussed. In such a network, resource allocation plays a critical role because it manages channel access in both time and frequency domains and determines how resources are allocated for different links. The proposed solution includes a nonlinear programming technique and a heuristic method. First, the problem formulation of resource allocation and relay selection is presented to provide an integrated framework for multi-hop relay networks. Second, an analytical solution to the problem is presented using a nonlinear programming technique. Finally, an iterative two-stage algorithm is presented to address the joint resource allocation and relay selection problem in multi-hop relay networks Under backhaul and capacity limitation constraints. In particular, the first stage proposed a fast approximation analytical solution for a resource allocation algorithm that takes into account the trade-off between the optimality and the complexity of the multi-hop relay architecture; the second stage presented a heuristic relay selection strategy that considers the RS load and helps to keep the relay from being overloaded is proposed. In the second part, the mobility problem in downlink multi-hop relay networks is addressed. In addition to the resource allocation issue, the relay selection problem is studied from a network layer perspective. Therefore, this part includes the issue of radio path selection. As an alternative to the heuristic algorithm developed in the previous part, the presented work describes the development and evaluation of a relay-selection scheme based on a Markov decision process (MDP) that considers the RS load and the existing radio-link path to improve handoff performance. First, the problem formulation of resource allocation and relay selection is presented. Second, an MDP mathematical model is developed to solve the relay selection problem in a decentralized way and to make the selection process simple. This relay selection scheme has the objective of maintaining the throughput and ensuring seamless mobility and service continuity to all mobile terminals while reducing the handoff frequency and improving handoff performance. In the third part, the admission and power control problem of a general heterogeneous network (HetNet) consisting of several small cells (SCs) is solved. Compared to the first two parts of this work, the system is expanded from a multi-hop RS to a general SC context. This part therefore focuses only on the access link problem, assuming the capacity of the SC backhaul links are large enough not to be bottlenecks. This part mainly deals with the problem of how to maximize the number of admitted users in an overloaded system while minimizing the transmit power given a certain QoS level. First, the problem is formulated to address concerns about QoS requirements in a better way. Second, a Voronoi-based user association scheme for maximizing the number of admitted users in the system under QoS and capacity limitation constraints is proposed to find near-optimal solutions. Finally, a twostage algorithm is presented to address the joint admission and power control problem in a downlink heterogeneous SC network. In particular, the first stage proposes a dynamic call admission control policy that considers the SC load and call-level QoS while also helping to keep the system from being overloaded. The second stage presents an adaptive power allocation strategy that considers both user distribution and the density of SCs in HetNets. Finally, the proposed solutions are evaluated using extensive numerical simulations, and the numerical results are presented to provide a comparison with related works found in the literature

An optimal admission control protocol for heterogeneous multicast streaming services

We investigate optimal call admission control (CAC) policy for multicast streaming services (MSS) in 3rd generation (3G) and beyond wireless mobile networks. Several MSS sessions are supported simultaneously in a bandwidth-limited network. Active sessions are those that are currently serving some users, and inactive sessions are those that are currently not serving any users. An admission decision in MSS is required only when an inactive session is requested, unlike in unicasting. For this reason, if a user request for an inactive MSS session arrives, we should make an admission decision in anticipation of (i) the possible reward earned based on users served during a session active time generated by accepting it, and (ii) the influence of the session active time upon the future status of network bandwidth and admission decisions. Our objective is to determine when to admit or block a user asking an inactive MSS session to achieve the optimality in rewards. We formulate this problem as a semi-Markov decision process (SMDP), and a value iteration algorithm is used to obtain an optimal stationary deterministic policy. We also derive the user blocking probability of the optimal policy by analyzing an embedded Markov chain induced by it.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=26hb201

Interference-based dynamic pricing for WCDMA networks using neurodynamic programming

Copyright © 2007 IEEEWe study the problem of optimal integrated dynamic pricing and radio resource management, in terms of resource allocation and call admission control, in a WCDMA network. In such interference-limited network, one's resource usage also degrades the utility of others. A new parameter noise rise factor, which indicates the amount of interference generated by a call, is suggested as a basis for setting price to make users accountable for the congestion externality of their usage. The methods of dynamic programming (DP) are unsuitable for problems with large state spaces due to the associated ldquocurse of dimensionality.rdquo To overcome this, we solve the problem using a simulation-based neurodynamic programming (NDP) method with an action-dependent approximation architecture. Our results show that the proposed optimal policy provides significant average reward and congestion improvement over conventional policies that charge users based on their load factor.Siew-Lee Hew and Langford B. Whit

Marginal productivity index policies for dynamic priority allocation in restless bandit models

Esta tesis estudia tres complejos problemas dinámicos y estocásticos de asignación de recursos: (i) Enrutamiento y control de admisión con información retrasada, (ii) Promoción dinámica de productos y el Problema de la mochila para artículos perecederos, y (iii) Control de congestión en “routers” con información del recorrido futuro. Debido a que la solución óptima de estos problemas no es asequible computacionalmente a gran y mediana escala, nos concentramos en cambio en diseñar políticas heurísticas de prioridad que sean computacionalmente tratables y cuyo rendimiento sea cuasi-óptimo. Modelizamos los problemas arriba mencionados como problemas de “multi-armed restless bandit” en el marco de procesos de decisión Markovianos con estructura especial. Empleamos y enriquecemos resultados existentes en la literatura, que constituyen un principio unificador para el diseño de políticas de índices de prioridad basadas en la relajación Lagrangiana y la descomposición de dichos problemas. Esta descomposición permite considerar subproblemas de optimización paramétrica, y en ciertos casos “indexables”, resolverlos de manera óptima mediante el índice de productividad marginal (MP). El índice MP es usado como medida de prioridad dinámica para definir reglas heurísticas de prioridad para los problemas originales intratables. Para cada uno de los problemas bajo consideración realizamos tal descomposición, identificamos las condiciones de indexabilidad, y obtenemos fórmulas para los índices MP o algoritmos computacionalmente tratables para su cálculo. Los índices MP correspondientes a cada uno de estos tres problemas pueden ser interpretados en términos de prioridades como el nivel de: (i) la penalización de dirigir un trabajo a una cola particular, (ii) la necesidad de promocionar un cierto artículo perecedero, y (iii) la utilidad de una transmisión de flujo particular. Además de la contribución práctica de la obtención de reglas heurísticas de prioridad para los tres problemas analizados, las principales contribuciones teóricas son las siguientes: (i) un algoritmo lineal en el tiempo para el cómputo de los índices MP en el problema de control de admisión con información retrasada, igualando, por lo tanto, la complejidad del mejor algoritmo existente para el caso sin retrasos, (ii) un nuevo tipo de política de índice de prioridad basada en la resolución de un problema (determinista) de la mochila, y (iii) una nueva extensión del modelo existente de “multi-armed restless bandit” a través de la incorporación de las llegadas aleatorias de los “restless bandits”.This dissertation addresses three complex stochastic and dynamic resource allocation problems: (i) Admission Control and Routing with Delayed Information, (ii) Dynamic Product Promotion and Knapsack Problem for Perishable Items, and (iii) Congestion Control in Routers with Future-Path Information. Since these problems are intractable for finding an optimal solution at middle and large scale, we instead focus on designing tractable and well-performing heuristic priority rules. We model the above problems as the multi-armed restless bandit problems in the framework of Markov decision processes with special structure. We employ and enrich existing results in the literature, which identified a unifying principle to design dynamic priority index policies based on the Lagrangian relaxation and decomposition of such problems. This decomposition allows one to consider parametric-optimization subproblems and, in certain “indexable” cases, to solve them optimally via the marginal productivity (MP) index. The MP index is then used as a dynamic priority measure to define heuristic priority rules for the original intractable problems. For each of the problems considered we perform such a decomposition, identify indexability conditions, and obtain formulae for the MP indices or tractable algorithms for their computation. The MP indices admit the following priority interpretations in the three respective problems: (i) undesirability for routing a job to a particular queue, (ii) promotion necessity of a particular perishable product, and (iii) usefulness of a particular flow transmission. Apart from the practical contribution of deriving the heuristic priority rules for the three intractable problems considered, our main theoretical contributions are the following: (i) a linear-time algorithm for computing MP indices in the admission control problem with delayed information, matching thus the complexity of the best existing algorithm under no delays, (ii) a new type of priority index policy based on solving a (deterministic) knapsack problem, and (iii) a new extension of the existing multi-armed restless bandit model by incorporating random arrivals of restless bandits

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Multi-Dimensional-Personalization in mobile contexts

During the dot com era the word "personalisation” was a hot buzzword. With the fall of the dot com companies the topic has lost momentum. As the killer application for UMTS or the mobile internet has yet to be identified, the concept of Multi-Dimensional-Personalisation (MDP) could be a candidate. Using this approach, a recommendation of mobile advertisement or marketing (i.e., recommendations or notifications), online content, as well as offline events, can be offered to the user based on their known interests and current location. Instead of having to request or pull this information, the new service concept would proactively provide the information and services – with the consequence that the right information or service could therefore be offered at the right place, at the right time. The growing availability of "Location-based Services“ for mobile phones is a new target for the use of personalisation. "Location-based Services“ are information, for example, about restaurants, hotels or shopping malls with offers which are in close range / short distance to the user. The lack of acceptance for such services in the past is based on the fact that early implementations required the user to pull the information from the service provider. A more promising approach is to actively push information to the user. This information must be from interest to the user and has to reach the user at the right time and at the right place. This raises new requirements on personalisation which will go far beyond present requirements. It will reach out from personalisation based only on the interest of the user. Besides the interest, the enhanced personalisation has to cover the location and movement patterns, the usage and the past, present and future schedule of the user. This new personalisation paradigm has to protect the user’s privacy so that an approach supporting anonymous recommendations through an extended "Chinese Wall“ will be described