Sergio Fortes

Management architecture for location-aware self-organizing LTE/LTE-a small cell networks

This article proposes a novel architecture for next-generation cellular networks in indoor scenarios. The objective of this model is to support SON mechanisms based on the knowledge of the user equipment location in a small cell network, the use of such information being a key enabler for advanced SON methods. The defined design is the basis for systems providing innovative location-aware SON techniques that make use of user localization in medium/large indoor areas (e.g., malls or corporate buildings). The functional and physical characteristics of this architecture and their technical implications are analyzed. Proposed innovations to generic mobile architecture are described as well as specific implementation for LTE/LTE-A standards. Interoperability with standard management systems and localization services, congestion avoidance, and data offloading are the key drivers of the design. Finally, the capabilities of the proposed architecture are demonstrated through the performance analysis of a simple key use case for location-aware self-optimization.

Location-aware self-organizing methods in femtocell networks

The evolution of cellular technologies has been followed by a continuous increase in their capacity and complexity. As a consequence, network management has become a challenge for network operators, especially at indoor environments. In these scenarios the percentage of calls and traffic is much higher than outdoors. Hence, intelligent and automatic mechanisms for network operation and maintenance are deemed necessary, leading to the so-called Self-Organizing Networks (SON). SON mechanisms analyze network indicators like counters, alarms, etc. in order to improve the network performance. Furthermore, in indoor scenarios, the recent advances in indoor positioning systems allow the integration of terminal position in the definition of novel SON techniques. The availability of this additional information provides knowledge about terminal distributions, mobility patterns, etc., which is useful data to enhance the efficiency and performance of SON techniques. In this sense, this paper proposes and develops location-aware SON techniques for indoor femtocell networks. In particular, novel self-optimization and self-healing algorithms are defined, which are supported by an indoor cellular-positioning system. Such mechanisms are evaluated in a real testbed environment.

Conflict Resolution Between Load Balancing and Handover Optimization in LTE Networks

Self-Organizing Networks (SONs) aim to raise the level of automated management in cellular technologies. In this field, Load Balancing (LB) and Handover Optimization (HOO) are two important functions to improve network performance. As these two functions can adjust the same parameters, a conflict may happen if LB and HOO tune them at the same time. In this paper, the conflict resolution of both functions in Long-Term Evolution (LTE) networks is addressed. Results show that the proposed coordination effectively provides better performance in those situations in which the adjusted mobility parameter is close to its saturation.

Context-Aware Self-Healing: User Equipment as the Main Source of Information for Small-Cell Indoor Networks

This article proposes the use of context information for automatic failure management, known as self-healing, in small-cell indoor scenarios. Self-healing is one of the main functions of self-organizing networks (SONs) aiming to automate the administration, operation, and management of mobile communications infrastructure. In current deployments, the increasing use of low-power base stations, known as small cells, introduces challenges in classic self-healing procedures. This article analyzes those issues and identifies the context of user equipment (UE) as the main source of information to overcome them. Subsequently, a novel framework for integrating context awareness and self-healing is proposed, and a detailed context-based detection/diagnosis mechanism is developed. Finally, the approach is evaluated in a real small-cell deployment, showing the feasibility and usefulness of the proposed context-aware self-healing system.

Contextualized indicators for online failure diagnosis in cellular networks

This paper presents a novel approach for self-healing in cellular networks based on the application of mobile terminals context information: time, service, activity, identity and, especially, location. Context information is therefore used to support root cause analysis, providing improved network fault diagnosis compared to classical non-context-aware approaches. The integration of context information is implemented by means of the newly defined contextualized indicators. These are used in order to integrate user equipment context information in pre-existent failure management schemes. The presented techniques are especially suitable for indoor small cell scenarios, whose particular conditions of dynamic user distribution, overlapping coverage, dynamic radio and service provisioning environment, etc., make previous diagnosis schemes especially unreliable. The algorithms and methodology for the proposed context-aware system are defined and its performance is assessed by means of an LTE system-level simulator.

Enhancing localization accuracy with multi-antenna UHF RFID fingerprinting

Accurate indoor positioning systems are still expensive in terms of hardware price or computing complexity. Cost reduction of wireless devices, reuse of already deployed infrastructures besides the non-intrusive features (compared to vision-based systems) of radiofrequency (RF) solutions, make these systems good candidates for cost effective indoor positioning systems. Here, the use of multi-antenna devices could help to improve location accuracy and to reduce the infrastructure costs. This paper presents a signal strength-based localization system using active UHF RFID. Different indoor positioning techniques are defined and analyzed, particularizing them for the multi-antenna case. The system performance is assessed for these methods and comparing one and two-antenna readers based on the field trial measurements. Finally, a trade-off of the number of tags and number of antennas is carried out in order to evaluate the capability of the presented system to reduce fixed infrastructure costs.

Context-Aware Self-Optimization: Evolution Based on the Use Case of Load Balancing in Small-Cell Networks

Self-organizing network (SON) mechanisms in cellular systems automate network management procedures to improve performance while reducing operational expenditure (OPEX) and capital expenditure (CAPEX). Within the area of SON research and development, self-optimization is an especially hot research topic, and key use cases have been defined by Third-Generation Partnership Project (3GPP) standards. This article proposes to apply the context-awareness concept to self-optimizing small-cell networks. Context information provides valuable additional data to enhance self-optimization mechanisms. In this context, a framework for context-aware (CA) self-optimization in smallcell environments is described, and a particular self-optimization use case, load balancing (LB), is used to evaluate the benefits of the proposed approach. The results show that the proposed CA-LB algorithms increase the users? satisfaction, while the optimization time is significantly reduced.

Coordinated location-based self-optimization for indoor femtocell networks

Current indoor femtocell networks pose many challenges that could end up into a congested or non-operative cellular communication. In this context, widespread Heterogeneous Cellular Networks (HCNs) and smart devices can provide information that, if well-processed, could support the operation, administration, management and provision (OAM&P) procedures to improve the indoor network performance. Thus, a proposal based on the Self-Organizing Networks (SON) paradigm and context information is described in this paper in order to overcome network degradations and failures. In particular, a coordinated self-optimization system is proposed to enhance extremely overloaded indoor femtocell networks and to reduce the energy consumption. This approach, which is supported by geo-located measurements, automates the network OAM&P procedures and provides the intelligence to network elements for a quick adaptation. Finally, the system performance is analyzed in a realistic simulated environment, where the improvement in network capacity, coverage as well as the efficient use of energy, are discussed.