Andrea GoldsmithDepartment of Electrical Engineering

Stanford University

IT Innovation WorkshopMarch 5, 2015Washington DC

Future Wireless NetworksUbiquitous Communication Among People and Devices

Next-gen Cellular/WiFiSensor Networks Smart Homes/SpacesAutomated HighwaysSmart GridBody-Area NetworksInternet of ThingsAll this and more …

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On the Horizon: “The Internet of Things”

50 billion devices by 2020 Source: FCC

“Sorry America, your airwaves are full*”

*CNN MoneyTech – Feb. 2012

IoT is not (completely) hype

Number of Connected Objects Expected to Reach 50bn by 2020

Are we at the Shannon limit of the Physical Layer?

óTime-varying channels.

We don’t know the Shannon capacity of most wireless channels

óChannels with interference or relays.óCellular systems

óChannels with delay/energy/$$$ constraints.óAd-hoc and sensor networks

Shannon theory provides design insights and system performance upper bounds

Next wave in wireless researchó Open problems in wireless network capacity and designó Channels and networks with feedbackó Rethinking cellular system capacity and designó mmWave networks with large antenna arrays (massive MIMO)ó Ad-hoc and sensor network capacity and designó Software-defined wireless networks

ó Back from infinityó Delay, complexity, and energy constraints

ó Expanding our horizonsó Applying our analysis tools and methodologies to new

disciplinesó To obtain fundamental results

Rethinking Cellular System Design

ó Traditional cellular design assumes system is “interference-limited”ó No longer the case with recent technology advances:ó MIMO, multiuser detection, cooperating BSs (CoMP) and relays

ó Raises interesting questions such as “what is a cell?”ó Energy efficiency via distributed antennas, small cells, MIMO, and relaysó Dynamic self-organization (SoN) needed for deployment and optimization

SmallCell

Relay

DAS

CoMPHow should cellularsystems be designed?

Will gains be big or incremental; in capacity,coverage or energy?

mmWave Massive MIMO

ó mmWaves have large attenuation and path lossó For asymptotically large arrays with channel estimation,

no attenuation, fading, interference or noiseó mmWave antenna arrays are smalló Bottlenecks: channel estimation and system complexityó Requires a complete rethinking of system design

Hundredsof antennas

Dozens of devicesç10s of GHz of Spectrumè

Wireless Sensor Networks

§ Energy (transmit and processing) is the driving constraint§ Data flows to centralized location (joint compression)§ Low per-node rates but tens to thousands of nodes§ Intelligence is in the network rather than in the devices

• Smart structures• Smart roadways• Search and rescue• Homeland security• Event detection• Battlefield surveillance

Wireless networks are everywhere, yet…

- Connectivity is fragmented- Capacity is limited (spectrum crunch and interference)- Roaming between networks is ad hoc

White Space &Cognitive Radio

Ad-hoc/Sensor networks

Software-Defined Network Architecture

WiFi Cellular mmWave Cognitive Radio

Freq.Allocation

PowerControl

SelfHealing ICIC QoS

Opt.CS

Threshold

UNIFIED CONTROL PLANE

Commodity HW

SW layer

App layerVideo Security VehicularNetworks HealthM2M

Wireless and Health, Biomedicine and Neuroscience

Doctor-on-a-chip-Cell phone info repository-Monitoring, remote intervention and services

Cloud

The brain as a network- EKG signal reception/modeling- Implants to monitor/generate signals- In-brain sensor networks- Signal injection as medical intervention- Signal encoding and decoding- Neural connectivity modeling

Body-AreaAnd In-Body

Networks

• To bring back new knowledge to my research and teaching

• Not to make $$$$

• To build state-of-the-art products grounded in deep theory, and see how they worked

Why I did a startup

• To build something (again)Silicon Valley 1986

20 Years

Lots of Theory

Lessons Learnedó Academics have a great job

ó A chip with 30 years worth of Info./Comm theory costs $5.

óWireless systems grounded in deep theory work better

ó Info./Comm. Theory heavily influence wireless system design (mainly at the PHY & MAC layers)

ó Complexity drives cost, size, and energy consumption

óMany aspects of wireless systems poorly understood

Communications research has had a lot of impact on IT

ó Converting the analog world to bits (A/Ds, sampling, quantization)ó Compression and storage (voice, images, video, data)ó Data processing (“Big Data”)ó Wireless/wired networks (WiFi, Cellular, BT, Cable, DSL, satellite)ó The “Cloud”: Communications, storage, and data processing

SummaryóMuch research needed to realize the wireless vision

ó This vision will enable new applications that will change people’s lives worldwide

ó Research has a profound impact on technology development, and vice versa.

Thanks to NSF, ONR, DARPA, AFOSR, & DTRA for research support