Spectrum Observatory ThinkTank


The Microsoft Spectrum Observatory ThinkTank 2014 aims to create a forum where like-minded individuals come together to discuss and provide additional feedback so the platform can better serve the community’s research needs even more than today. During this ThinkTank we will be presenting the vision of Microsoft Spectrum Observatory, demo of current version (which is being actively developed), describe its architecture and provide an opportunity for you to provide suggestions and feedback to make the Microsoft Spectrum Observatory a success. It is also an opportunity for the Spectrum Observatory development team to describe their future plans, look at research currently being done in this space, and how you can become part of this exciting project.

What is Microsoft Spectrum Observatory?
Researchers who participate in spectrum monitoring and associated technologies often want to conduct large-scale field studies to collect data, but conducting such studies today is quite challenging. Considerable custom engineering is required to ensure hardware and software prototypes work robustly, and recruiting and managing more than a handful of locations can be difficult and cost-prohibitive. To lower the barrier for field studies, data collection and developing and evaluating new technologies for wireless spectrum research, Microsoft has developed a shared infrastructure, called Microsoft Spectrum Observatory. The vision of the Microsoft Spectrum Observatory includes a large number of geographically distributed measurement stations, each running a common, flexible framework in which measurements are collected and then centrally stored. The use of a common framework and shared dataset will enable engineering effort, along with experience and expertise, to be shared among many research groups.

More information

Website: http://observatory.microsoftspectrum.com/

E-mail: mailto:spectrum_obs@microsoft.com


US Federal Government Spectrum Monitoring by Mr. Michael Cotton

Tutorial of the Spectrum Observatory and a Walkthrough of the Technology by Mr. Anoop Gupta

Beyond Sensing: Multi-GHz Realtime Spectrum Analytics by Mr. Lixin Shi, MIT


Spectrum sensing has been an active research area for the past two decades. Nonetheless, current spectrum sensing systems provide only coarse occupancy data. They lack information about the detailed signal patterns in each band and can easily miss fleeting signals like radar.

We present SpecInsight, a system for acquiring a detailed view of 4 GHz of spectrum in real-time. SpecInsight’s design addresses the intrinsic conflict between the need to quickly scan a wide spectrum and the desire for obtaining very detailed information about each band. Its key enabler is a learned database of signal patterns and a new scheduling algorithm that leverages these patterns to identify when to sample each band to maximize the probability of sensing active signals.

SpecInsight is implemented using off-the-shelf USRP radios with only tens of MHz of instant bandwidth, but is able to span 4 GHz of spectrum, and capture very low duty-cycle signals in the radar band. Using SpecInsight, we perform a large-scale study of the spectrum in 6 locations in the US that span major cities and suburban areas, and build a first-of-its-kind database of spectrum usage patterns.

Integrated Sensing and Database Architecture for White Space Networking by Dr. Sumit Roy, University of Washington


The evolution of cognitive (secondary) networks to enable more efficient spectrum usage will rely on fast and accurate spectrum sensing/mapping, supported by a suitable architecture for data integration and model building. In the first part of the talk, fundamental aspects of the wide-area RF mapping problem as a grand challenge will be highlighted; and some recent work at UW that underpin sub-system level trade-offs (between scan latency and channel status estimation accuracy) for channel sensing described. Next, the role of centralized databases in RF map creation for enabling primary-to-secondary and secondary-to-secondary coexistence is explored and a hybrid architecture proposed – that involves both distributed (crowd-sourced) local sensing as well as it’s integration into databases. Finally, some ongoing work regarding a fundamental question: how much white space capacity is actually available – will be described.

TxMiner: Identifying Transmitters in Real-World Spectrum Measurements


How should regulators re-assign spectrum optimally? How do licensees identify spectrum usage in order to provision for future needs? How do Dynamic Spectrum Access devices determine on which frequency to operate? All these questions require knowledge about active transmitters, which is not straight-forward to obtain with currently-existing techniques. In this talk I am going to present TxMiner: a system that automatically identifies transmitters without prior knowledge of their characteristics. TxMiner makes use of machine learning methods in order to tease apart transmitters from raw spectrum measurements. I will start by outlining several key insights that enable TxMiner; I will then show results from transmitter identification using traces collected by Microsoft’s Spectrum Observatory.

Towards Commoditized Real-time Spectrum Monitoring


We are facing an increasing difficult challenge in spectrum management: how to perform real-time spectrum monitoring with strong coverage of deployed regions. Today’s solutions use dedicated hardware that is bulky and expensive, making the monitoring task extremely difficult and cost prohibitive. We propose a practical alternative by leveraging the power of the masses, i.e. millions of wireless users, using low- cost, commoditized spectrum monitoring hardware. We envision an ecosystem where crowd sourced smartphone users perform automated and continuous spectrum measurements using their mobile devices, and report the results to a monitoring agency in real-time.

In this talk, we will introduce our initial feasibility study to verify the efficacy of the mobile monitoring platform compared to that of conventional monitoring devices. Our results indicate that commoditized real-time spectrum monitoring is indeed feasible in the near future. We conclude by discussing a set of open challenges and potential directions for follow-up research.

An Overview of the Global Policy and Regulatory Landscape – Opportunities and Risks for Alternative Forms of Spectrum Access


It has been three decades since the United States Federal Communications Commission (“FCC”) created the first unlicensed spectrum access. Although only available commercially in the last fifteen years, it is hard to imagine consumers doing without technologies now used in the unlicensed spectrum bands – Wi-Fi, Bluetooth, RFID. There are now many more wireless devices reliant on unlicensed access to spectrum than wireless devices reliant on licensed access to spectrum. Driven by growing demand that risks outstripping the current allocations of spectrum for wireless broadband applications, governments and regulators around the world are now looking at making more spectrum available on an exclusive-use licensed basis for 4G LTE, as well as make more spectrum available on an unlicensed (or licensed-exempt) basis for Wi-Fi and other technologies. Governments and regulators are likewise now looking at alternative forms of spectrum access which will not require incumbent licensees to be cleared and reallocated, such as spectrum sharing opportunities in the TV white spaces, 2.3 GHz, 3.5 GHz, and 5 GHz either on an unlicensed, licensed, or lightly-licensed basis. This presentation will provide an overview of efforts by governments and regulators around the world to address these issues – with a particular focus on alternative forms of spectrum access. This presentation will also discuss how spectrum observatories, standardization, technology trials, commercial pilots, partnerships, and industry and academic coalitions can and are being used to support these efforts.


Dr. Ranveer Chandra  Microsoft

Dr. Victor Bahl  Microsoft

Mr. Paul Garnett  Microsoft
Mr. Anoop Gupta  Microsoft

Mr. Paul Mitchell  Microsoft

Dr. Elizabeth Belding  UCSB
Dr. Joseph Camp SMU
Dr. Minghua Chen  CUHK
Mr. Michael Cotton  ITS
Dr. Joseph Evans  University of Kansas
Dr. Kyle Jameison  UCL
Dr. Giovanni Pau   UCLA
Dr. Sumit Roy  UW
Mr. Lixin Shi  MIT
Dr. Michael Souryal   NIST
Dr. Kannan Srinivasan Ohio State
Dr. Rouzbeh Yassini UNH
Dr. Mariya Zheleva SUNY
Dr. Heather Zheng UCSB