Aggelos Saatsakis

Distributed radio access technology selection for adaptive networks in high‐speed, B3G infrastructures

Wireless systems migrate towards the era of ‘Beyond the 3rd Generation’ (B3G). A fundamental facilitator of this vision is the evolution of high speed, adaptive networks, needed for better handling the offered demand and improving resource utilization. Adaptive networks dynamically select their configuration, in order to optimally adapt to the changing environment requirements and conditions. This paper presents optimization functionality that can be used to support network adaptability (cognition-reconfigurability) in a B3G context. The paper starts from the business case that justifies the need for placing research onto adaptive networks and then continues with the management functionality for (re)configuration decisions, which is targeted to the dynamic selection of the appropriate radio access technologies (RATs). RAT selection is modelled through an optimization problem called (RAT, Demand and QoS-Assignment problem—RDQ-A), the solution of which assigns in a distributed manner the available RATs to adaptive Base Station transceivers and the demand (users) to these transceivers and to QoS levels, respectively. The RDQ-A optimization problem is decoupled in several sub-problems and is implemented in phases corresponding to the aforementioned assignments, while efficient custom greedy algorithms are mobilized in each phase for obtaining the optimum assignment. Finally, indicative results from the application of the proposed functionality to a simulated network are presented. Copyright

Cognitive Radio Resource Management for Improving the Efficiency of LTE Network Segments in the Wireless B3G World

In this paper, we provide a framework for enhancing radio resource management (RRM) in 3G long term evolution (LTE) systems with cognitive features. By exploiting the capabilities of orthogonal frequency division multiplexing (OFDM) LTE access technology, network segments are capable of properly adapting to the environment conditions by applying RRM algorithms for optimized sub-carriers assignment, power allocation and adaptive modulation. On the other hand, cognitive features can be used to provide the system with knowledge that derives from past interactions with the environment. As a result, the system will be able to apply already known solutions in timely manner when identifying a problem that has been already addressed in the past. Framed within the above statements, we propose and validate a cognitive RRM scheme in the context of LTE network segments. Indicative examples and results showcase that the proposed scheme can result in significant efficiency improvement in terms of performance and network adaptation.

Context Matching for Realizing Cognitive Wireless Network Segments

Beyond 3rd Generation (B3G) wireless communication systems are comprised from different Radio Access Technologies (RATs) in order to satisfy all user needs in services. The coexistence of many RATs in the same environment needs advanced network management systems in order to ensure efficient resources utilization while achieving the best possible Quality of Service (QoS) levels. Management functionality in the B3G era will have to solve complex problems, due to the existence of versatile options for satisfying stringent requirements, under difficult environment conditions. The introduction of cognitive systems in the B3G world is a direction for addressing the complexity, as it will enable reaching decisions faster and more reliably, by considering also knowledge and experience derived from past interactions of the system with the network environment. Our work presents an approach for identifying whether a context, encountered by the network segment, has also been dealt in the past. In this case context knowledge can be exploited for fast and cost efficient network reconfiguration and adaptation to the environment conditions.

Optimisation of Radio Access Network Operation Introducing Self-x Functions: Use Cases, Algorithms, Expected Efficiency Gains

With the deployment of next generation (4G) mobile radio systems an additional radio access network is established. A variety of different Radio Access Technologies (RATs) will be operated in parallel. In this framework, the Long Term Evolution (LTE) system, specified by 3GPP, will have to co-exist with WiMAX, mobile 2G/3G networks and Wireless Local Area Networks (WLANs). To cope with this increasing diversity and complexity mechanisms for self-optimisation, self-organisation, self-healing, self-configuration (self-x) are essential to guarantee cost efficient and high quality network operation. Within the project E³ (1) self-x functionalities for different use cases and different elements of a mobile radio access network are developed. Aim of this paper is to give and overview about the interworking of different self-x functionalities and to present three exemplary use cases. I. INTRODUCTION Evolution of mobile radio networks is driven by the demand for new, high bit rate consuming applications and services. The technical answer is the development of new and more powerful radio technologies and integration into existing mobile radio networks. This leads to significantly higher complexity and heterogeneity while pressure for maintaining manageability and cost efficiency of the networks is continuously increasing. E³ answer is introduction of solutions for obtaining higher flexibility and efficiency in usage of radio, hardware and computational resources by cognition, self- organisation and self-optimisation. This paper presents the interworking of cognitive radio self-x functions in E³ environments and hereafter three exemplary self-x use cases namely Handover Parameter Optimisation, Protocol Stack Self- Configuration & Topology Self-Organisation and Knowledge- based Proactive Context Handling.

Femtocell and Flexible Base Station cognitive management

In this paper we discuss on the cognitive management of wireless infrastructures that encompass Flexible Base Stations (FBSs) and Femtocells investigated by the Integrated Project E3 (End-to-End-Efficiency) funded within FP7. FBSs are equipped with Software Defined Radio (SDR) transceivers capable of operating the appropriate Radio Access Technologies (RATs) while Femtocells are capable of changing their operating parameters, including the way to manage the Mobile Terminals (MTs). The necessary reconfiguration actions are provided by the network decision entity called Dynamic Self-organizing Network Planning and Management (DSNPM). DSNPM is enhanced with optimization procedures as well as cognitive functionalities that will provide the means for proper network adaptation to the environment changes in timely manner. Our work presents an approach for the overall optimization procedure, exploiting FBSs and Femtocells software and hardware capabilities as well as knowledge and experience gained from past interactions of DSNPM with the network environment. High level system architecture will be presented describing the problem statement and the solution approach in which the above aspects will be addressed. Finally, an indicative scenario will exhibit the efficiency of FBSs and Femtocells functionalities as well as the associated cognitive management functionalities of DSNPM.

Exploiting context, profiles, and policies in dynamic sub-carrier assignment algorithms for efficient radio resource management in OFDMA networks

Dynamic sub-carrier assignment (DSA) is considered as one of the most important aspects for achieving efficient spectrum utilization in orthogonal frequency division multiple access (OFDMA) based networks. Most of well-known DSA algorithms operate in a best effort manner, where the full set of sub-carriers is used in order to achieve the maximum possible quality of service level per user. However, in a real network environment, there are several management aspects to be considered such as context information (users, services, and radio environment conditions), user profiles, and network operator policies. In the context of OFDMA networks management, DSA algorithms should be extended incorporating such aspects in order to introduce fairness in the assignment of sub-carriers as well as to improve the overall system performance. In this paper, an efficient radio resource management scheme that incorporates a new DSA algorithm which exploits context profiles and policies information is presented. Results showcase the benefits that the proposed approach brings in terms of fairness on sub-carriers assignment and overall system performance.

An approach for realizing Future Internet with cognitive technologies

Telecommunications and information technology will be parts of the Future Internet infrastructures. It will be characterized by powerful and complex network infrastructures, advanced applications, services and content, efficient power management as well as extensions in the business model. These characteristics entail that the management of the Future Internet world will be more complex, compared to today. The introduction of cognitive systems is believed to be an efficient response to the complexity. In this respect, the aims and contribution of this paper is to provide an approach for realizing the Future Internet era by means of cognitive systems. The basis and foundation will be work conducted in the area of cognitive wireless networks. This work constitutes a solid basis, on which the Future Internet era can be realized, through suitable expansions.

Advanced planning strategies for wireless in a B3G reconfigurable radio context

Wireless communications migrate towards the beyond the 3rd generation (B3G) era. A fundamental concept for B3G is reconfigurability, which enables a true seamless mobility experience thanks to the dynamic adaptation, of network segments and terminals, to the set of radio access technologies (RATs) that are most appropriate for handling the offered demand. Reconfigurability affects the way wireless infrastructures should be designed. This paper presents optimization functionality that can be used for the design of wireless infrastructures in a reconfigurable radio context. More specifically the paper aims at optimally assign the available RATs to reconfigurable transceivers, the service demand to RATs and the services to QoS levels (RAT, demand and QoS-assignment problem - RDQ-A). The RDQ-A problem is described and mathematically formulated. Finally, a greedy solution algorithm is proposed and results are presented.

Introducing cognitive systems in the B3G world: The E 3 approach to the "invisible" network of the future

One of the most recent trends in the area of B3G communications are reconfigurable, cognitive systems. Cognitive systems encompass self-management and self-optimization capabilities: awareness of user, device and context information, policies derivation, decision making, reconfiguration and learning. Mechanisms for perception and learning of user and context information are one of the most important features of cognitive systems. Based on the knowledge and experience obtained through learning, cognitive systems can determine and configure their operation not only in a reactive manner, i.e. responding to the detection of problematic situations, but also proactively, so as to prevent issues undermining the optimal system function. This paper presents the approach of the European Union funded project End-to-End Efficiency (E3), aiming at integrating cognitive wireless systems in the Beyond the Third Generation (B3G) world.

Emerging, Self-Management Functionality for Introducing Cognition in the Wireless, B3G World

The unparalleled evolution of wireless communications is reflected in the tremendous investments on research and development, targeted at the continuous introduction of innovations that could serve the information society. This has led to the coexistence and complementary exploitation of versatile, legacy and also emerging Radio Access Technologies (RATs). At the same time, the continuously varying environment/users requirements impose the adaptation of those technologies to external stimuli, through reconfiguration (reconsideration) of their infrastructure and/or operating parameters. One feasible option to tackle the increased complexity of such environments, is to design wireless infrastructures with learning capabilities, thus forming cognitive networks. Cognitive networks are able to retain information from their interactions with the environment and intelligently adapt to any requirements. A prerequisite to facilitate operability of cognitive networks is the development of novel management mechanisms, which need to, distributively (centralized approaches would get even more complex), evaluate changes in external conditions and determine the way in which the network will properly respond to them. To this effect, this paper presents a complete framework under which Cognitive Access Points (CgAPs) could be managed and analyzes the functionality of its entities. Moreover, it also provides an approach for managing Cognitive Wireless Network Segments (CgWNSs).