Dense heterogeneous networks constitute the paradigm for the future networks. In fact, recent studies demonstrate that the data traffic demand increases exponentially and the traditional cellular networks are not able to provide enough capacity. For this reason operators and standardisation bodies are particularly eager to solve the problem, hence there is a lot of ongoing research on this direction. In this paper we focus on extremely dense networks, that could be found, e.g., in crowded public places or in offices. In such deployments, energy consumption must be kept proportional to the traffic dispatched, otherwise operational costs will render them unsustainable from an economic perspective. In this paper, we propose a network model for the estimation of the power consumption of an LTE dense network of small cells, which takes into account the backhaul network. Furthermore, we introduce a new mechanism for the association of the users to base stations, aiming at minimizing the energy consumption of the LTE access network. The achieved trade-off among capacity and power consumption is then evaluated by means of a classical association policy that connects each user to the base station which received signal is the strongest.

No abstract

Next generation wireless networks (5G) have to cope with significant traffic increase due to high quality video transmission and cloud-based applications. Such requirements create the need for a revolutionary change in architecture rather than a series of local and incremental technology updates. A dense heterogeneous deployment of small cells such as pico/femto cells in addition to high power macro cells is foreseen as one of the potential solutions to achieve these requirements. While there is significant amount of research in this area that relies on simulations at PHY, MAC and higher layers, it is still necessary to validate the algorithms for next generation systems in a real-time testbed. However, the ever increasing complexity in all layers of current and future generations of cellular wireless systems has made an end-to-end demonstration of the network limited to industrial research labs or large academic institutions. In this paper, we show a LabVIEW 1 based PXI platform in which LTElike SISO OFDM PHY Layer is integrated with an open source protocol stack to prototype PHY/MAC cross layer algorithms within CROWD 2 Software Defined Networking (SDN) framework as a solution to tame dense deployment of wireless networks.

The significant growth in mobile data traffic and the ever-increasing user's demand for high-speed, always connected networks continue challenging network providers and lead research towards solutions to enable faster, scalable and more flexible networks. In this paper we present the CROWD approach, a networking framework providing mechanisms to tackle the high densification and heterogeneity of wireless networks. The goal of CROWD is to design protocols and algorithms for very dense and heterogeneous wireless networks, which we call DenseNets. The mechanisms we propose include energy efficiency, MAC enhancements, connectivity management and backhaul configuration to contribute to the next generation of networks considering density as a resource instead of as an obstacle.

In this paper, we present initial results on how the ns-3 LTE LENA stack is used to build a LTE testbed in an indoor lab network. We have extended the ns-3 MAC/PHY layer architecture to interface with a LabVIEW implementation of the LTE Physical layer and also extended ns-3 core modules to enable real-time performance. We present how this testbed can be used for prototyping a novel Software Defined Networking (SDN) scheme for interference management within dense heterogeneous deployments of cellular wireless networks. We provide an example case study for a Distributed Mobility Management (DMM) implementation using this testbed, where we demonstrate mobility of a emulated User Equipment device between LTE and WiFi networks. We plan to use this testbed for validation and demonstration of various SDN-based algorithms proposed within the framework of the EU FP7 CROWD (Connectivity management for eneRgy Optimised Wireless Dense networks) Project. We believe the proposed testbed is especially valuable for studying the cross-layer performance of cellular PHY/MAC algorithms in a realistic environment and shows how ns-3 can be used as a unified prototyping and simulation framework for wireless networks.