Transcript Wireless Data Services for Cellular Telephony

Cooperative Wireless Networks
Hamid Jafarkhani
Director
Center for Pervasive Communications
and Computing
www.cpcc.uci.edu
Center’s Focus and Goal
• CPCC was established in 2000
– To facilitate research in emerging communications technologies
– To dramatically change the way people access and use
information
• Need for ubiquitous communications to anywhere at
anytime results in many challenges in
– Circuits/Systems
– Communications/Signal processing
– Networking
Goal: Higher throughput and better connectivity
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Focus and Goal
• Need for ubiquitous communications to
anywhere and any device at anytime
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to the internet
to the cloud
to home
to PC, tablet
to TV
to car
to your body
Goal: Internet of things through wireless access
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Characteristics of
Machine-to-Machine Net
• Very large number of nodes (Trillion ?)
– Sensor networks are used more often
– Body area networks are gaining more attention
• Self organized and autonomously operated
• Operating through different domains
(wireless and wired) seamlessly
• Low latency
• Low power
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Mobile Video Traffic
• The number of mobile devices exceeded the world’s
population in 2012
• Machine-to-machine (M2M) modules will exceed the
world’s population in 2016 (7.3 billions)
• Mobile video traffic was 52% of the mobile traffic in
2011 (70% in 2016)
• Mobile video traffic in 2016 will be 13 times the
entire mobile traffic in 2011
• The top 1% of mobile data subscribers generated
24% mobile data traffic in 2011 (35% in 2016)
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Landscape in 2025
• Billions of (trillion?) devices
– Today: more than a billion wireless subscribers
• 100 times growth in mobile traffic
– more users & more traffic per user
• 10 times increase in device density
• 10 times less power consumption (Bits/Joule)
– Today, Internet/Telecom infrastructure consumes 3%
of the world’s energy
• Same connectivity everywhere (edge vs center)
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Need for a
Paradigm Shift
• Current wireless networks include many users
and many data transmitted simultaneously, but
we allocate independent resources through
routing, scheduling, … to send A’s message to
B without interference
• What if we “literally” allow simultaneous
transmission?
Point-to-Point  Many-to-Many
Competition  Cooperation
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Many-to-Many
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Many-to-Many
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Technologies
• Interference Management
– Interference cancellation
– Interference alignment
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Cognitive Communications
Massive MIMO
Context-Aware Networking
Cooperative Communications
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Multiple base station transmission/reception
Relay networks
Virtual MIMO
Network coding
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Relay Networks
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Cooperative
Strategies
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Amplify and forward
Decode and forward
Coded cooperation
Compress/estimate and forward
Distributed space-time coding
Distributed beamforming
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Comparing MIMO and
Distributed Beamforming
• Differences:
– Antennas can share power in MIMO
(total power constraint).
– Antennas know the transmitted signals
perfectly in MIMO.
• Consequences:
– Individual (separate) power constraints and a
non-convex optimization problem.
– Distributed solutions.
An analytical closed-form solution exists despite the
non-convex nature of the problem.
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Relay Networks with
Quantized Feedback
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Distributed Beamforming
with Limited Feedback
• The problem can be modeled as a
source coding problem.
• The solution is a vector quantizer.
• We need to design the optimal
codebook for the vector quantizer.
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Simulation Results
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Beamforming in RelayInterference Networks
• So far, the main goal of cooperation
has been the delivery of a point-topoint message.
• What if we want to shift the paradigm
to a many-to-many scenario?
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Beamforming in RelayInterference Networks
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CSI Knowledge
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Summary
• Traditional diversity definitions are not good enough
to compare the asymptotic reliability of different
cooperative communication systems.
• Despite interference, multi-user relay networks can
provide the same diversity as single-user networks.
• In terms of diversity, relay selection is an optimal
codebook using quantized feedback information.
• Very low-rate CSI quantizers exist that achieve full
diversity asymptotically with zero feedback rate.
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Conclusions
• There is still need for ubiquitous
communications to anywhere and any
device at anytime
• There is a paradigm shift from point-topoint communication to many-to-many
communication
• There is a paradigm shift from
competition to cooperation
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