Andrea Goldsmith
Department of Electrical Engineering
Stanford University
IT Innovation Workshop
March 5, 2015
Washington DC
Future Wireless Networks
Ubiquitous Communication Among People and Devices
Next-gen Cellular/WiFi
Sensor Networks
Smart Homes/Spaces
Automated Highways
Smart Grid
Body-Area Networks
Internet of Things
All this and more …
“Sorry America, your airwaves are full*”
On the Horizon:
“The Internet of Things”
50 billion devices by 2020
Source: FCC
*CNN MoneyTech – Feb. 2012
3
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?
We don’t know the Shannon
capacity of most wireless channels
— Time-varying channels.
— Channels with interference or relays.
— Cellular systems
— Ad-hoc and sensor networks
— Channels with delay/energy/$$$ constraints.
Shannon theory provides design insights
and system performance upper bounds
Next wave in wireless research
— Open problems in wireless network capacity and design
—
—
—
—
—
Channels and networks with feedback
Rethinking cellular system capacity and design
mmWave networks with large antenna arrays (massive MIMO)
Ad-hoc and sensor network capacity and design
Software-defined wireless networks
— Back from infinity
— Delay, complexity, and energy constraints
— Expanding our horizons
— Applying our analysis tools and methodologies to new
disciplines
— To obtain fundamental results
Rethinking Cellular System Design
Small
Cell
CoMP
How should cellular
systems be designed?
Relay
DAS
Will gains be big or
incremental; in capacity,
coverage or energy?
— Traditional cellular design assumes system is “interference-limited”
— No longer the case with recent technology advances:
— MIMO, multiuser detection, cooperating BSs (CoMP) and relays
— Raises interesting questions such as “what is a cell?”
— Energy efficiency via distributed antennas, small cells, MIMO, and relays
— Dynamic self-organization (SoN) needed for deployment and optimization
mmWave Massive MIMO
ç10s of GHz of Spectrumè
Dozens of devices
Hundreds
of antennas
— mmWaves have large attenuation and path loss
— For asymptotically large arrays with channel estimation,
no attenuation, fading, interference or noise
— mmWave antenna arrays are small
— Bottlenecks: channel estimation and system complexity
— Requires a complete rethinking of system design
Wireless Sensor Networks
•
•
•
•
•
•
§
§
§
§
Smart structures
Smart roadways
Search and rescue
Homeland security
Event detection
Battlefield surveillance
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
Wireless networks are everywhere, yet…
White Space &
Cognitive Radio
Ad-hoc/Sensor networks
- Connectivity is fragmented
- Capacity is limited (spectrum crunch
and interference)
- Roaming between networks is ad hoc
Software-Defined Network Architecture
Video
Freq.
Allocation
Vehicular
Networks
Security
Power
Control
Self
Healing
ICIC
M2M
QoS
Opt.
App layer
SW layer
Health
CS
Threshold
UNIFIED CONTROL PLANE
Commodity HW
WiFi
Cellular
mmWave
Cognitive
Radio
Wireless and Health, Biomedicine and Neuroscience
Body-Area
And In-Body
Networks
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
Why I did a startup
• Not to make $$$$
• To build something (again)
Silicon Valley 1986
20 Years
Lots of Theory
• To build state-of-the-art products grounded in deep
theory, and see how they worked
• To bring back new knowledge to my research and teaching
Lessons Learned
— Academics have a great job
— Info./Comm. Theory heavily influence wireless
system design (mainly at the PHY & MAC layers)
— A chip with 30 years worth of Info./Comm theory costs $5.
— Wireless systems grounded in deep theory work better
— Complexity drives cost, size, and energy consumption
— Many aspects of wireless systems poorly understood
Communications research
has had a lot of impact on IT
—
—
—
—
—
Converting the analog world to bits (A/Ds, sampling, quantization)
Compression and storage (voice, images, video, data)
Data processing (“Big Data”)
Wireless/wired networks (WiFi, Cellular, BT, Cable, DSL, satellite)
The “Cloud”: Communications, storage, and data processing
Summary
— Much research needed to realize the wireless vision
— This vision will enable new applications that will
change people’s lives worldwide
— Research has a profound impact on technology
development, and vice versa.
Thanks to NSF, ONR, DARPA, AFOSR, & DTRA for research support