In the LTE systems, battery lifetime and network traffic overhead on control plane may be largely affected by the Discontinuous reception (DRX) configuration and the Radio Resource Control (RRC) Inactivity Timer. In this scenario, the paper proposes an analysis aimed at defining how to properly set the RRC Inactivity Timer to achieve a trade-off between energy savings and traffic overhead on the control plane. The analysis is based on an energy consumption model, whose key parameters are inferred directly from passive measurements carried out by monitoring a commercial eNodeB of one of the Italian Mobile Operators. The results suggest that taking into account the network traffic characteristics is possible to find the RRC inactivity timer value that permits to save energy of user's device while the increase of the signalling load is limited

In LTE and LTE-Advanced systems the rate of requests on the Random Access CHannel (RACH) can be high. Indeed, the Machine Type Communication (MTC) implies to have a high number of devices that need to request radio resources for transmitting small amount of data. Furthermore, reducing the time in which radio resources are allocated to Human Type Communications (HTC) for energy savings purposes, may lead to radio access network overload as well. In this framework, this paper aims at providing a set of guidelines for the resource allocation task in the RACH. In particular, the study investigates the impact of both the backoff indicator scheme and the maximum number of retransmissions on the RACH performance parameters. The rate of RACH requests associated with the HTC traffic is modelled by inferring their statistical properties starting from a dataset acquired in an operational eNodeB. The estimation of the average delay and the average number of maximum retransmissions gives insights on how many preambles should be reserved for HTC in order to meet the target performance, and provides suggestions on the configuration of the backoff indicator

Monitoring operations in today's mobile networks is becoming a more and more challenging task due to the higher bandwidth and technological complexity brought by LTE. The paper summarizes some relevant problems that arose in the tests of LTE equipment carried out at Telecom Italia Lab (TILAB, the R&D center of Telecom Italia), and presents an ongoing project that aims at realizing a flexible hardware/software platform to cope with these problems at reasonable costs. The ultimate goal of this research is to develop a Software Defined Networking (SDN) measurements platform, which permits to easily and dynamically configure the measurement devices involved in the test and monitoring functions according to the requirements defined by the operator. Furthermore, the paper proposes the integration of the designed framework in a realistic lab environment, and discusses the improvements introduced to the actual architecture

The deployment of LTE and the explosion of smart-phones and tablet market increase the requirements of mobile connectivity, together with a change in the users expectations in terms of bandwidth, access speed, reliability and QoS man-agement. In this new network scenario, traffic characterization and monitoring is of paramount relevance in order to prevent possible pitfalls during the deployment of new services. Hence, the paper presents the traffic analysis of a deployed eNodeB in a commercial network. The analysis is aimed at detecting traffic features at call and frame level, also accounting for the handset types

In the latest years, we have seen a fast evolution of Internet systems and a remarkable increase of the number and variety of services required. The need of new architectural solutions has led to the creation of new tools that allow to develop more flexible and dynamic networks. Software Defined Networking (SDN) goes in this direction, offering a new way to manage networks, based on programmability, virtualization of the network and centralization of decision processes. In this article we will analyse how it is possible to deploy these new tools to realize some fundamental network functions also for monitoring systems. We will also show a real testbed where we implemented the functions we describe, and we will show the experimental results obtained with it