Enhancing cognitive radio systems with robust reasoning

Cognitive radio systems dynamically reconfigure the algorithms and parameters they use, in order to adapt to the changing environment conditions. However, reaching proper reconfiguration decisions presupposes a way of knowing, with high enough assurance, the capabilities of the alternate configurations, especially in terms of achievable transmission capacity and coverage. The present paper addresses this problem, firstly, by specifying a complete process for extracting estimations of the capabilities of candidate configurations, in terms of transmission capacity and coverage, and, secondly, by enhancing these estimations with the employment of a machine learning technique. The technique is based on the use of Bayesian Networks, in conjunction with an effective learning and adaptation strategy, and aims at extracting and exploiting knowledge and experience, in order to reach robust (i.e. stable and reliable) estimations of the configurations' capabilities. Comprehensive results of the proposed method are presented, in order to validate its functionality. Copyright © 2007 John Wiley & Sons, Ltd.     

Service configuration and user profiling in 4G terminals

This paper presents a middleware platform for managing devices that operate in heterogeneous environments. The proposed management framework supports terminal-controlled, preference-based access network selection. Two separate problems are identified in this domain: one involving the computation of optimal allocations of services to access networks and quality levels (service configuration), and one concerning the dynamic inference of the user’s preferences, according to the usage context (user profiling). This paper includes an approach to the definition, mathematical formulation and solution of both these problems. Indicative results of the proposed solution methods are presented in the context of a real-life scenario simulating a day in the life of an ordinary user.     

Intelligent discovery of the capabilities of reconfiguration options in a cognitive wireless B3G context

Beyond 3G (B3G) wireless connectivity can efficiently be realized by exploiting cognitive networking concepts. Cognitive systems dynamically reconfigure the radio access technologies and the spectrum they use, based on experience, in order to adapt to the changing environment conditions. However, dynamic reconfiguration decisions call for robust discovery, i.e., radio-scene analysis and channel identification schemes. This paper intends to contribute in the areas of radio-scene analysis and channel identification: first, by providing an overview of interference estimation methods, and explaining how capacity estimations can be derived based on the measured interference levels; second, by specifying the information flow for the radio-scene analysis process of a cognitive radio system; and third, by enhancing the above with a learning system, which is essential for obtaining a truly cognitive process. The proposed approach lies in the introduction of a robust probabilistic model for optimal prediction of the capabilities of alternative configurations, in terms of capacity.     

A Combination of Optimal Partitioning and Location Prediction to Assist Paging in Mobile Cellular Networks

The correlated both in space and time user mobility behavior can aid significantly in the localization of a moving terminal in the network coverage area. However, there is always some uncertainty in mobile user position and a network-wide search cannot be done. Therefore, a predictive paging scheme must always be combined with a location update strategy and a compatible algorithm to conduct the search. In this paper, we introduce a new strategy that combines an optimal partitioning of the location area (LA) with a model to predict user movements, based on the additional information of the cell where the last interaction between the network and the terminal took place. We study the performance of the strategy under delay bounds and different mobility and call arrival characteristics. It is found that the new scheme further minimizes signaling costs and enhances previous sequential paging algorithms.     

Towards Anonymous Mobile Community services

In the current market conditions, network operators are in search of novel value-added services that will increase their revenue. This paper introduces the innovative concept of Anonymous Mobile Community (AMC) services and thoroughly defines and describes a robust platform targeted for their deployment. AMC services take advantage of the terminals’ capabilities to collect information and deliver it to the network. In this context, terminals are enabled to form communities that serve as sources of information. In these communities, the anonymity and privacy of the end-users are respected and guarded. Several examples of promising AMC services are presented and categorized. An indicative example application is the provision of real-time information regarding road-traffic conditions, based on the location and speed of mobile terminals. A system aiming at the provision of diverse AMC services is proposed, and its requirements, architecture and functionality are described in detail. The related scalability issues and business models are carefully outlined, and a use case scenario as well as trial results are presented.     

Factoring and reductions for networks with imperfect vertices

Factoring and reductions are effective methods for computing the K-terminal reliability of undirected networks, but they have been applied mostly to networks with perfect vertices. However, in real problems, vertices may fail as well as edges. Imperfect vertices can be factored like edges, but the complexity then increases exponentially with their number. A technique has been developed to account for the failure of vertices with small additional cost, using a modified method of factoring and reductions. This technique is very easy to integrate into a factoring algorithm. It consists of factoring not on a single element (e.g., a single edge) but on a set of elements (e.g., an edge and its endpoints). The problem is that random variables associated with the elements of the network are no longer independent. This can be handled by choosing factoring edges that have at least one perfect endpoint. This technique leaves the factoring algorithm practically unchanged. The only difference is that some supplementary probability values are kept for the imperfect vertices of the original and the induced graphs. For algorithms using simple reductions, it has negligible computational cost     

Road to Next Generation Mobile Networks: An Evolutionary Dynamics Approach

One of the major challenges that mobile operators (MOs) are faced with nowadays is the transition to 4th Generation (4G) mobile communication technologies. The main reason for this lies on the reluctance of MOs to invest in a new technology without being sure about its success. The current paper investigates the decision-making procedures of a MO that wishes to migrate from its current technology type to 4G. Traditionally, the decision of deploying a new technology has been based on the analysis of similar implementations in other countries. However, such approaches can be inefficient and time consuming, as there are discrepancies concerning the technological progress among different countries. To this end, the authors employ evolutionary game theory to model the interactions of the MO’s decisions and the subscribers’ needs, and propose a practical and efficient qualitative model that identifies the circumstances under which the transition towards 4G networking can be facilitated. Specifically, the mathematical foundation of the decision making process is provided and the key role of the charging price and the quality of experience by the subscribers for using 4G connectivity is proven. With the process of 4G deployment still ongoing, this paper aims to present an analysis that can be used supplementary to the decision process of a MO that aims to evolve his network.     

Wireless beyond 3G: managing services and network resources

Wireless beyond 3G is a new concept that envisions cellular, BFWA, and DVB systems cooperating in a composite radio infrastructure. In this scheme, instead of rejecting users or degrading their quality of service levels, a network provider can direct them to an alternate radio technology that meets certain environmental, cost, and QoS criteria. To achieve such a system requires upgrading service and network resource management (SNRM). We present work areas for a new SNRM approach that comprises the Universal Mobile Telecommunications System (UMTS), high-performance wireless local area network (HiperLAN 2) technology, and terrestrial DVB (DVB-T) systems.     

A TQM-Based Approach to QoS Management

Total Quality Management (TQM) is one of the most interesting and effective concepts of management. Although, as of today, it has been extensively applied to manufacturing and industrial sectors, TQM principles have not received wide acceptance in the area of Telecommunications Network and Service Management. Application of those principles in Telecommunications can be facilitated by employing pertinent techniques and tools. This paper focuses on aspects of the performance management of Telecommunications Networks and Services. As basic quality control mechanisms, two versions of a Dynamic Scaling Service (DSS) are used to regulate the end-user perceived quality: a Crisp DSS and a Fuzzy Logic DSS. A quality-oriented user behavior model is built and a comparative study between the different quality control schemes is presented. Concluding, the paper delineates the scope of TQM with respect to QoS management in telecommunications.