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Archived Projects

Contributors: Sumit Roy
This project aims to enhance the wireless capabilities of ns-3, positioning it as the primary research tool for simulating 5G wireless networks. It also aims to improve usability and create educational materials for easy adoption by the next generation of users. The project aligns with the National Science Foundation-funded Platforms for Advanced Wireless Research (PAWR) city-scale infrastructure testbeds and focuses on new wireless technology coexistence scenarios for heterogeneous networks and scaling challenges due to network densification. The project is a collaboration between the University of Washington and the Centre Technologic Telecomunicacions Catalunya (CTTC Barcelona).
Underwater Acoustic Networking
Contributors: Payman Arabshahi, Sumit Roy
Abstract: Underwater acoustics has been a topic of research for decades. However, the idea of deploying networked teams of underwater vehicles for both deep and shallow water ocean exploration is a more recent topic of interest. The Seaglider, developed at the University of Washington, is one such vehicle. FUNLab along with the Applied Physics Lab (APL) are exploring physical and MAC layer protocols to provide robust, low power, efficient networking solutions to the Seaglider.

The underwater acoustic channel has properties that make it a very difficult medium for communications. For instance, the long propagation delay of sound, multi-path spread of the medium, frequency selective attenuation, shadowing zones, and other factors make this channel extremely hard to characterize. A commonly used approach for determining the acoustic propagation of sound in the underwater channel is to use ray tracing techniques based on Snell’s Law. Members of the FUNLab are investigating ways to statistically characterize the underwater channel using techniques similar.

MAC protocols in the underwater environment must be designed with different considerations than those in the terrestrial environment. The long propagation delays of sound make carrier sensing and acknowledgment packets impractical. Additionally, autonomous underwater vehicles (AUVs) are extremely energy-constrained. These and other design considerations, including the lack of position information from GPS, necessitates new MAC design for AUV deployment, which is also an ongoing topic of research between the FUNLab and the APL.

For more information see the UAN Projects page
For more information on Ocean-TUNE project see the Ocean-TUNE Project page

Interference Modeling with CMU Emulator
Abstract:  This research used the CMU Wireless Emulator to improve the NS-3 network simulator interference model by examining different aspects of interference, determining the validity of the current NS-3 implementation, and suggesting alternative implementations that more closely match reality.
Software Defined Wireless Networks
Contributors: Farzad Hessar
CampusLink: A WS-based Campus Network

Abstract: A WS campus network reuses WS spectrum on campus and allows multiple hosts to communicate with others inside WS channels. To accomplish that, a MAC layer is needed to allow communication among multiple bladeRFs, and its objective is to catch most parts of 802.11 standard to allow either ad hoc or infrastructure network. In addition to that, a PAWS is required for information exchange between a WS database and a host, and its purpose is to give hosts a list of recommended channels which are selected by an algorithm to achieve the highest overall throughput.

Spectrum Observatory

Cityscape project

Abstract: A collaborative effort between University of Washington, Shared Spectrum Company and Daintree Technologies is resulting in the first metro-scale spectrum observatory – CityScape. In this work, we provide an overview of the system architecture (both hardware and software components), the novel features that distinguish this from others and the design and operational challenges encountered. For further details, refer to Cityscape Technical report.

UAS Networking

Abstract: The advances in UAS technology has opened up the opportunity for UAS networks that promise to be easily scalable and deployable in the absence of any infrastructure. This opportunity comes with challenges – mobility and going from a 2D space to 3D space, to name a few. This project aims to perform analytical studies to provide a better understanding and optimal values of the parameters involved. Simultaneously, a platform is in the works that uses an SDR to transmit packets from the ground to the SDR stationed on the UAV to test out different scenarios.

PHY network coding for coded caching in wireless networks
Abstract: Coded caching can achieve significant broadcast gain in the content distribution network. It contains two phases: placement phase and delivery phase. The placement phase is done at the off-peak time so that each user will cache some contents. In the peak time the server leverages the caching contents at each user to send coded packets to harvest the broadcast gain in the delivery phase. However, when coded caching is applied to the wireless networks, the non-identical link capacity and packet loss in wireless channels make it inefficient. To address the problems of coded caching in wireless networks, we consider to design a new PHY network coding scheme, which can achieve full rate of each wireless link and rateless transmission. Moreover, the relationship of caching and link capacity is explored to achieve better performance.
Spectrum Sharing
Affiliated Student:
Radar Wi-Fi Coexistence

Abstract: Over the last decade, the increasing demand for high-speed wireless connectivity has forced us to confront spectrum scarcity. In 2012, the president mandated that a large swathe of spectrum that was under government control be opened up for opportunistic access by commercial systems. In particular, much of the initial focus has been directed at the coexistence of radar systems with broadband wireless networks. Spectrum sharing of 802.11 wireless local area network (WLAN) and radars operating in co-/adjacent channel scenarios (notably 5 GHz) is a problem of considerable importance that requires new innovations. The spectrum sharing explored in this project is based on unilateral action by Wi-Fi networks to prevent unacceptable interference to incumbent radar and also mitigating the interference from radar to Wi-Fi. Specifically, the ability of a single Wi-Fi network inside the exclusion region is to speedily detect radar operation and to subsequently switch to a clear channel as a means of protecting them. Also, the Wi-Fi systems outside the exclusion region are modified to detect and mitigate the interference from a pulsed search radar such that the WLAN continues to operate with no noticeable performance degradation.

LTE WiFi Coexistence

The two most common broadband wireless access networks are cellular and Wi-Fi. Traditionally, these have operated in very different spectrum regulatory domains: cellular over licensed spectrum (i.e. exclusive use, requiring large sums of money for this privilege) whereas Wi-Fi has been designed for the unlicensed bands where there is no interference protection by rule. This difference has led to fundamentally different system architectures: cellular systems are centrally controlled where users are allocated resources in frequency and/or time in a way so as to minimize intra-cell and inter-cell interference. Wi-Fi (IEEE 802.11) on the other hand, has been designed to operate in an environment where interference between like (other Wi-Fi) and unlike (non Wi-Fi) systems must be tolerated. Of late, driven by the maturation of Small Cell technologies, there has been increasing interest in deploying systems originally intended for licensed, cellular bands in the unlicensed bands (currently primarily used by Wi-Fi) with minimal changes. This creates a new and largely under-explored heterogeneous interference scenario: a scheduled system (cellular) coexisting with a collision avoidance protocol (Wi-Fi).

The initial ns-3 version of Wi-Fi with LTE-DC coexistence uses the waveform based LTE-DC model for modeling the LTE-DC behavior. The example scenario can be found here:

For subsequent LTE-DC performance evaluation, we used the LTE-DC capability that was developed under a WiFi Alliance funded project involving collaboration CTTC and UW and updated by Muhammad Iqbal in the 2018 Google Summer of Code; this updates previous LTE/Wi-Fi coexistence code to the latest ns-3.29 release. This LTE-DC model uses the LTE DutyCycleAccessManager to generate duty-cycled LTE transmissions in ns-3 code. The example scenario can be found here:

For LTE-U duty cycle manuscripts as of February 2019, the ns-3 coexistence code can be found on the branch “lte-dc-analysis” of the Bitbucket repository:

RFI in Radio Astronomy
Contributors: Lvtianyang Zhang
Radio Astronomy arrays – such as the Murchison Widefield Array (MWA) in the West Australian desert – seek to detect extremely faint radiation (the desired signal) in the presence of other ‘Sky Noise’ (other undesired signals emanating from the galaxy) and terrestrial (man-made) radio frequency interference (RFI). The received signal processing chain must detect and flag these anomalies so they are excised from the database used for astronomy research. The  MWA system currently implements AOflagger algorithm that is known to perform sub-optimally under certain RFI (e.g. terrestrial TV). In this project, we seek to improve RFI flagging by enhancing the AOflagger with new algorithmic capabilities tuned to known RFI source characteristics.
Wireless Network Coding
Random Access with Physical Layer Network Coding

Abstract: Compute-and-forward (C&F) is a promising new physical-layer technique which allows a receiver to recover multiple linear combinations of simultaneous transmitted packets. Prior work on C&F mainly focuses on its information-theoretic performance as well as its practical code constructions. However, its potential in improving networking performance, such as throughput and delay, is less well understood.

In particular, it is unclear what is the benefit of C&F in the presence of bursty data traffic and decentralized network operations. To understand the networking performance of C&F, we consider the application of C&F to random access protocols such as Slotted ALOHA and variants of CSMA.

Scenarios and Implementations of NC

Abstract: Network Coding (NC), a technique to increase the spectral efficiency of communication networks by combining multiple packets of data destined for different sink nodes at every node, has drawn much research attention in the past decade. In a single-source multicast network, it is shown that the networks capacity is achievable by utilizing Linear Network Coding (LNC). Also in simple two-way relay channel, it’s shown that NC can increase the throughput of the network by %33 at most. A new ground for exploring network coding techniques is the rapidly growing dense cellular networks, in which a user entity can lie within the overlapping area of two or more cells and hence is able to communicate with multiple Base Stations (BS) simultaneously. These situations can evidently be modeled as Distributed Antenna Systems (DAS) or Distributed Multi-Input-Multi-Output (DMIMO) systems. The research ongoing is to identify and exploit the potentials of such techniques to increase the spectral efficiency and hence the throughput of wireless communication networks.

Center on Satellite Multimedia and Connected Vehicles
CMMB Vision-UWEE Center is dedicated to advancement of satellite networking, multimedia, smart connected vehicles and artificial intelligence/machine learning technologies. Our mission is to develop cutting-edge solutions that enable delivery of information to people around the world anytime/anywhere at unprecedented speed, scale, and (low) cost. The goal of the center is to conduct fundamental systems-oriented research and design prototyping in related areas (wireless communications, multimedia processing, artificial intelligence/machine learning, mmWave solutions for connected vehicles etc.) that are potentially disruptive for the satellite and automotive industry segments.