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

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

ns-3 Implementation of the 3GPP MIMO Channel Model for Frequency Spectrum above 6 GHz

Communications at mmWave frequencies will be a key enabler of the next generation of cellular networks, due to the multi-Gbps rate that can be achieved. However, there are still several problems that must be solved before this technology can be widely adopted, primarily associated with the interplay between the variability of mmWave links and the complexity of mobile networks. An end-to-end network simulator represents a great tool to assess the performance of any proposed solution to meet the stringent 5G requirements. Given the criticality of channel propagation characteristics at higher frequencies, we present our implementation of the 3GPP channel model for the 6-100 GHz band for the ns-3 end-to-end 5G mmWave module, and detail its associated MIMO beamforming architecture

Dealing with Interference in Distributed Large-scale MIMO Systems: A Statistical Approach

This paper considers the problem of interference control through the use of second-order statistics in massive MIMO multi-cell networks. We consider both the cases of co-located massive arrays and large-scale distributed antenna settings. We are interested in characterizing the low-rankness of users' channel covariance matrices, as such a property can be exploited towards improved channel estimation (so-called pilot decontamination) as well as interference rejection via spatial filtering. In previous work, it was shown that massive MIMO channel covariance matrices exhibit a useful finite rank property that can be modeled via the angular spread of multipath at a MIMO uniform linear array. This paper extends this result to more general settings including certain non-uniform arrays, and more surprisingly, to two dimensional distributed large scale arrays. In particular our model exhibits the dependence of the signal subspace's richness on the scattering radius around the user terminal, through a closed form expression. The applications of the low-rankness covariance property to channel estimation's denoising and low-complexity interference filtering are highlighted.Comment: 12 pages, 11 figures, to appear in IEEE Journal of Selected Topics in Signal Processin

Fog-supported delay-constrained energy-saving live migration of VMs over multiPath TCP/IP 5G connections

The incoming era of the fifth-generation fog computing-supported radio access networks (shortly, 5G FOGRANs) aims at exploiting computing/networking resource virtualization, in order to augment the limited resources of wireless devices through the seamless live migration of virtual machines (VMs) toward nearby fog data centers. For this purpose, the bandwidths of the multiple wireless network interface cards of the wireless devices may be aggregated under the control of the emerging MultiPathTCP (MPTCP) protocol. However, due to the fading and mobility-induced phenomena, the energy consumptions of the current state-of-the-art VM migration techniques may still offset their expected benefits. Motivated by these considerations, in this paper, we analytically characterize and implement in software and numerically test the optimal minimum-energy settable-complexity bandwidth manager (SCBM) for the live migration of VMs over 5G FOGRAN MPTCP connections. The key features of the proposed SCBM are that: 1) its implementation complexity is settable on-line on the basis of the target energy consumption versus implementation complexity tradeoff; 2) it minimizes the network energy consumed by the wireless device for sustaining the migration process under hard constraints on the tolerated migration times and downtimes; and 3) by leveraging a suitably designed adaptive mechanism, it is capable to quickly react to (possibly, unpredicted) fading and/or mobility-induced abrupt changes of the wireless environment without requiring forecasting. The actual effectiveness of the proposed SCBM is supported by extensive energy versus delay performance comparisons that cover: 1) a number of heterogeneous 3G/4G/WiFi FOGRAN scenarios; 2) synthetic and real-world workloads; and, 3) MPTCP and wireless connections

Hybrid 3D Localization for Visible Light Communication Systems

In this study, we investigate hybrid utilization of angle-of-arrival (AOA) and received signal strength (RSS) information in visible light communication (VLC) systems for 3D localization. We show that AOA-based localization method allows the receiver to locate itself via a least squares estimator by exploiting the directionality of light-emitting diodes (LEDs). We then prove that when the RSS information is taken into account, the positioning accuracy of AOA-based localization can be improved further using a weighted least squares solution. On the other hand, when the radiation patterns of LEDs are explicitly considered in the estimation, RSS-based localization yields highly accurate results. In order to deal with the system of nonlinear equations for RSS-based localization, we develop an analytical learning rule based on the Newton-Raphson method. The non-convex structure is addressed by initializing the learning rule based on 1) location estimates, and 2) a newly developed method, which we refer as random report and cluster algorithm. As a benchmark, we also derive analytical expression of the Cramer-Rao lower bound (CRLB) for RSS-based localization, which captures any deployment scenario positioning in 3D geometry. Finally, we demonstrate the effectiveness of the proposed solutions for a wide range of LED characteristics and orientations through extensive computer simulations.Comment: Submitted to IEEE/OSA Journal of Lightwave Technology (10 pages, 14 figures