Antonio Virdis

SimuLTE - A modular system-level simulator for LTE/LTE-A networks based on OMNeT++

This paper describes SimuLTE, an open-source system-level simulator for LTE and LTE-Advanced (LTE-A) networks. SimuLTE is based on OMNeT++, a well-known, widely-used modular simulation framework, which offers a high degree of experiment support. As such, it can be seamlessly integrated with all the networkoriented modules of the OMNeT++ family, such as INET, thus enabling - among other things - credible simulation of end-to-end real-life applications across heterogeneous technologies. We describe the modeling choices and general architecture of the SimuLTE software, with particular emphasis on the MAC and scheduling functions, and show performance evaluation results obtained using the simulator.

Simulating LTE/LTE-Advanced Networks with SimuLTE

In this work we present SimuLTE, an OMNeT++-based simulator for LTE and LTE-Advanced networks. Following well-established OMNeT++ programming practices, SimuLTE exhibits a fully modular structure, which makes it easy to be extended, verified, and integrated. Moreover, it inherits all the benefits of such a widely used and versatile simulation framework as OMNeT++, i.e., experiment support and seamless integration with the OMNeT++ network modules, such as INET. This allows SimuLTE users to build up mixed scenarios where LTE is only a part of a wider network. This paper describes the architecture of SimuLTE, with particular emphasis on the modeling choices at the MAC layer, where resource scheduling is located. Furthermore, we describe some of the verification and validation efforts and present an example of the performance analysis that can be carried out with SimuLTE.

A comprehensive simulation analysis of LTE Discontinuous Reception (DRX)

In an LTE cell, Discontinuous Reception (DRX) allows the central base station to configure User Equipments for periodic wake/sleep cycles, so as to save energy. DRX operations depend on several parameters, which can be tuned to achieve optimal performance with different traffic profiles (i.e., CBR vs. bursty, periodic vs. sporadic, etc.). This work investigates how to configure these parameters and explores the trade-off between power saving, on one side, and per-user QoS, on the other. Unlike previous work, chiefly based on analytical models neglecting key aspects of LTE, our evaluation is carried out via simulation. We use a fully-fledged packet simulator, which includes models of all the protocol stack, the applications and the relevant QoS metrics, and employ factorial analysis to assess the impact of the many simulation factors in a statistically rigorous way. This allows us to analyze a wider spectrum of scenarios, assessing the interplay of the LTE mechanisms and DRX, and to derive configuration guidelines.

Exploiting LTE D2D communications in M2M Fog platforms: Deployment and practical issues

Fog computing is envisaged as the evolution of the current centralized cloud to support the forthcoming Internet of Things revolution. Its distributed architecture aims at providing location awareness and low-latency interactions to Machine-to-Machine (M2M) applications. In this context, the LTE-Advanced technology and its evolutions are expected to play a major role as a communication infrastructure that guarantees low deployment costs, plug-and-play seamless configuration and embedded security. In this paper, we show how the LTE network can be configured to support future M2M Fog computing platforms. In particular it is shown how a network deployment that exploits Device-to-Device (D2D) communications, currently under definition within 3GPP, can be employed to support efficient communication between Fog nodes and smart objects, enabling low-latency interactions and locality-preserving multicast transmissions. The proposed deployment is presented highlighting the issues that its practical implementation raises. The advantages of the proposed approach against other alternatives are shown by means of simulation.

Resource allocation for network-controlled device-to-device communications in LTE-Advanced

Network-controlled device-to-device (D2D) communication allows cellular users to communicate directly, i.e., without passing through the eNodeB, while the latter retains control over resource allocation. This allows the same time–frequency resources to be allocated to spatially separated D2D flows simultaneously, thus increasing the cell throughput. This paper presents a framework for: (1) selecting which communications should use the D2D mode, and when, and (2) allocating resources to D2D and non-D2D users, exploiting reuse for the former. We show that the two problems, although apparently similar, should be kept separate and solved at different timescales in order to avoid problems, such as excessive packet loss. We model both as optimization problems, and propose a heuristic solution to the second, which must be solved at millisecond timescales. Simulation results show that our framework is practically viable, it avoids the problem of packet losses, increases throughput and reduces delays.

Practical large-scale coordinated scheduling in LTE-Advanced networks

In LTE-Advanced, the same spectrum can be re-used in neighboring cells, hence coordinated scheduling is employed to improve the overall network performance (cell throughput, fairness, and energy efficiency) by reducing inter-cell interference. In this paper, we advocate that large-scale coordination can be obtained through a layered solution: a cluster of few (i.e., three) cells is coordinated at the first level, and clusters of coordinated cells are then coordinated at a larger scale (e.g., tens of cells). We model both small-scale coordination and large-scale coordination as optimization problems, show that solving them at optimality is prohibitive, and propose two efficient heuristics that achieve good results, and yet are simple enough to be run at every transmission time interval. Detailed packet-level simulations show that our layered approach outperforms the existing ones, both static and dynamic.

Performance Analysis of OpenAirInterface System Emulation

With the rapid growth of mobile networks, the radio access network becomes more and more costly to deploy, operate, maintain and upgrade. The most effective answer to this problem lies in the centralization and virtualization of the eNodeBs. This solution is known as Cloud RAN and is one of the key topics in the development of fifth generation networks. Within this context Open Air Interface is a promising emulation tool that can be used for prototyping innovative scheduling algorithms, making the most of the new architecture. In this work we first describe the emulation environment of OpenAirInterface and its scheduling framework and we use it to implement two MAC schedulers. Moreover we validate the above schedulers and we perform a thorough profiling of Open Air Interface, in terms of both memory occupancy and execution time. Our results show that OpenAirInterface can be effectively used for prototyping scheduling algorithms in emulated LTE networks.

Mobile-Edge Computing Come Home Connecting things in future smart homes using LTE device-to-device communications.

Future 5G cellular networks are expected to play a major role in supporting the Internet of Things (IoT) due to their ubiquitous coverage, plug-and-play configuration, and embedded security. Besides connectivity, however, the IoT will need computation and storage in proximity of sensors and actuators to support timecritical and opportunistic applications. Mobile-edge computing (MEC) is currently under standardization as a novel paradigm expected to enrich future broadband communication networks [1], [2]. With MEC, traditional networks will be empowered by placing cloud-computing-like capabilities within the radio access network, in an MEC server located in close proximity to end users. Such distributed computing and storage infrastructure will enable the deployment of applications and services at the edge of the network, allowing operators to offer a virtualized environment to enterprise customers and industries to implement applications and services close to end users.

Modeling unicast device-to-device communications with simuLTE

In LTE-Advanced (LTE-A), device-to-device (D2D) transmissions allow two peering User Equipments to communicate directly without using the Evolved Node-B as relay. D2D is regarded as one of the enablers to bring LTE-A in the context of vehicular networks, smart cities, or M2M applications. Research on this topic is mostly carried out through link-level simulations. In this work, we describe instead the modeling of D2D into a system- level simulator, namely SimuLTE, which enables us to analyze the performance of applications and higher-layer protocols using D2D transmission. We first describe the modeling within the SimuLTE architecture, then we validate it and analyze the performance of D2D communications with frequency reuse.

A Fast and Reliable Broadcast Service for LTE-Advanced Exploiting Multihop Device-to-Device Transmissions

Several applications, from the Internet of Things for smart cities to those for vehicular networks, need fast and reliable proximity-based broadcast communications, i.e., the ability to reach all peers in a geographical neighborhood around the originator of a message, as well as ubiquitous connectivity. In this paper, we point out the inherent limitations of the LTE (Long-Term Evolution) cellular network, which make it difficult, if possible at all, to engineer such a service using traditional infrastructure-based communications. We argue, instead, that network-controlled device-to-device (D2D) communications, relayed in a multihop fashion, can efficiently support this service. To substantiate the above claim, we design a proximity-based broadcast service which exploits multihop D2D. We discuss the relevant issues both at the UE (User Equipment), which has to run applications, and within the network (i.e., at the eNodeBs), where suitable resource allocation schemes have to be enforced. We evaluate the performance of a multihop D2D broadcasting using system-level simulations, and demonstrate that it is fast, reliable and economical from a resource consumption standpoint.