An Extension of the ns-3 LTE Module to Simulate Fractional Frequency Reuse Algorithms

We developed an extension for the LTE module of the ns-3 simulator in order to allow the simulation of Fractional Frequency Reuse algorithms and the evaluation of their performance in an LTE scenario. In this paper, we describe the technical components of such extension, namely the new API for Fractional Frequency Reuse algorithms, the implementation of several state-of-the-art-algorithms based on such API, and the implementation of the LTE downlink and uplink power control functionality which are required by many of these algorithms. Additionally, we provide an overview of the test suites that are included with our extension in order to validate its correct functionality, and discuss some example scenarios illustrating how our extension can be used in an LTE simulation

A Flexible Transport Layer Protocol Architecture for Handover in a Vehicular VLC Network

Recent research works have focused on the feasibility of using the multipath-transmission control protocol (MPTCP) in order to optimize network throughput and latency. In this work, we propose a novel architecture using MPTCP for a vehicular visible light communications (VLC) network to improve the performance in terms of network outage duration and throughout. Two relevant MPTCP schedulers and an MPTCP tool are selected to analyze VLC performance during the handover. The results show that the proposed system offers low-outage duration handover of 24 ms and high data throughput of 125 Mbps using "Redundant"and "Default"schedulers, respectively

Analyzing Interface Bonding Schemes for VLC with Mobility and Shadowing

Node mobility and shadowing are the most common reasons requiring a handover in vehicular visible light communications (VVLC). In order to provide seamless mobility during the handover, it is required to decrease the network outage duration. This paper aims to improve the outage duration in handover caused by mobility and shadow for VLC networks. We analyze interface bonding schemes using two different primary interface reselection methods. The results show that using "failure"interface selection method instead of "always"method reduces the VLC handover outage duration by 62% and 44% in bonding schemes for transmission control protocol (TCP) and user datagram protocol (UDP) network traffic, respectively

Demo Abstract: Cross-technology communication between LTE-U/LAA and WiFi

Although modern wireless technologies like LTE and 802.11 WiFi provide very high peak data rates they suffer from performance degradation in dense heterogeneous deployments as they rely on rather primitive coexistence schemes. Hence, for efficient usage of the shared unlicensed spectrum a cross-technology communication (CTC) between co-located LTE unlicensed and WiFi devices is beneficial as it enables direct coordination between the co-located heterogeneous technologies. We present OfdmFi, the first system that enables to set-up a bidirectional CTC channel between co-located LTE unlicensed and WiFi networks for the purpose of cross-technology collaboration. We demonstrate a running prototype of OfdmFi. First, we present the performance of a bi-directional CTC channel between LTE unlicensed and WiFi. Second, we show that partial channel state information of the CTC channel can be obtained. Third, we demonstrate the possibility to transmit a cross-technology broadcast packet which is received simultaneously by the two heterogeneous technologies, WiFi and LTE. During the demo, we display all the relevant performance metrics in real-time

DeepTxFinder: Multiple Transmitter Localization by Deep Learning in Crowdsourced Spectrum Sensing

As the radio spectrum has become the bottleneck resource with increasing volume of mobile data and ultra-dense network deployments, it is crucial to use spectrum more flexibly in time, space, and frequency dimensions. However, higher efficiency in spectrum usage facilitated by flexible spectrum allocation comes with a cost, namely the increased complexity of spectrum monitoring and management. Identifying the transmitters is at the interest of particularly spectrum enforcement authorities to ensure that spectrum is used as intended by the legitimate users of the spectrum. For a scalable, efficient, and highly-accurate operation, we propose a crowd-sensing based solution where sensing devices report their measured receive power levels to a central entity which later fuses the collected information for localizing an unknown number of transmitters. Our solution, referred to as DeepTxFinder, leverages deep learning to handle many sources of uncertainty in the operation environment: namely number of transmitters, their transmission power levels, and channel conditions (shadowing). Using deep-learning, DeepTxFinder distinguishes itself from the prior state-of-the art which requires knowledge of the number and transmission power of transmitters or require the transmitters to be well separated in space by tens to hundreds of meters making them ill-suited for application in expected ultra-dense deployment of small-cells. Moreover, we propose a tiling-based approach to increase the scalability of our proposal by reducing the computational complexity. Our simulation studies show that DeepTxFinder can provide a high detection accuracy even only by collecting data from a very small number of sensors. More specifically, with 1 %-2 % sensor density DeepTxFinder can estimate the number of transmitters and their locations with high probability which proves that sparse sensing is feasible

Punched Cards over the Air: Cross-Technology Communication Between LTE-U/LAA and WiFi

Despite exhibiting very high theoretical data rates, in practice, the performance of LTE-U/LAA and WiFi networks is severely limited under cross-technology coexistence scenarios in the unlicensed 5GHz band. As a remedy, recent research shows the need for collaboration and coordination among colocated networks. However, enabling such collaboration requires an information exchange that is hard to realize due to completely incompatible network protocol stacks. We propose OfdmFi, the first cross-technology communication scheme that enables direct bidirectional over-the-air communication between LTE-U/LAA and WiFi with minimal overhead to their legacy transmissions. Requiring neither hardware nor firmware changes in commodity technologies, OfdmFi leverages the standard-compliant possibility of generating message-bearing power patterns, similar to punched cards from the early days of computers, in the time-frequency resource grid of an OFDM transmitter which can be cross-observed and decoded by a heterogeneous OFDM receiver. As a proof-of-concept, we have designed and implemented a prototype using commodity devices and SDR platforms. Our comprehensive evaluation reveals that OfdmFi achieves robust bidirectional CTC between both systems with a data rate of up to 84kbps, which is more than 125× faster than state-of-the-art