1,033 research outputs found

    Integration of Carrier Aggregation and Dual Connectivity for the ns-3 mmWave Module

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    Thanks to the wide availability of bandwidth, the millimeter wave (mmWave) frequencies will provide very high data rates to mobile users in next generation 5G cellular networks. However, mmWave links suffer from high isotropic pathloss and blockage from common materials, and are subject to an intermittent channel quality. Therefore, protocols and solutions at different layers in the cellular network and the TCP/IP protocol stack have been proposed and studied. A valuable tool for the end-to-end performance analysis of mmWave cellular networks is the ns-3 mmWave module, which already models in detail the channel, Physical (PHY) and Medium Access Control (MAC) layers, and extends the Long Term Evolution (LTE) stack for the higher layers. In this paper we present an implementation for the ns-3 mmWave module of multi connectivity techniques for 3GPP New Radio (NR) at mmWave frequencies, namely Carrier Aggregation (CA) and Dual Connectivity (DC), and discuss how they can be integrated to increase the functionalities offered by the ns-3 mmWave module.Comment: 9 pages, 7 figures, submitted to the Workshop on ns-3 (WNS3) 201

    The edge cloud: A holistic view of communication, computation and caching

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    The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201

    End-to-End Simulation of 5G mmWave Networks

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    Due to its potential for multi-gigabit and low latency wireless links, millimeter wave (mmWave) technology is expected to play a central role in 5th generation cellular systems. While there has been considerable progress in understanding the mmWave physical layer, innovations will be required at all layers of the protocol stack, in both the access and the core network. Discrete-event network simulation is essential for end-to-end, cross-layer research and development. This paper provides a tutorial on a recently developed full-stack mmWave module integrated into the widely used open-source ns--3 simulator. The module includes a number of detailed statistical channel models as well as the ability to incorporate real measurements or ray-tracing data. The Physical (PHY) and Medium Access Control (MAC) layers are modular and highly customizable, making it easy to integrate algorithms or compare Orthogonal Frequency Division Multiplexing (OFDM) numerologies, for example. The module is interfaced with the core network of the ns--3 Long Term Evolution (LTE) module for full-stack simulations of end-to-end connectivity, and advanced architectural features, such as dual-connectivity, are also available. To facilitate the understanding of the module, and verify its correct functioning, we provide several examples that show the performance of the custom mmWave stack as well as custom congestion control algorithms designed specifically for efficient utilization of the mmWave channel.Comment: 25 pages, 16 figures, submitted to IEEE Communications Surveys and Tutorials (revised Jan. 2018
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