Transcript 3TU course on MIMO Wireless Communication

MIMO for a mass market
3TU course on
MIMO Wireless Communication
Jean-Paul Linnartz
September 2006
MIMO for a mass market
About the contents of the course
• MIMO is an important trend that shapes the
future of wireless communication systems
• MIMO is a multidisciplinary topic
• MIMO is being addressed in Delft, Eindhoven
and Twente.
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MIMO for a mass market
Capita Selecta in Wireless Communication
This course covers selected topics in Wireless Communications, including RF,
information theory and software radio architectures. Yet the topics are not a random
collection of faculty hobby horses, but are seen as important factors that push the
limits of future systems:
• One-chip radio, i.e., combining RF and BB into one chip solution, requires an new
multi disciplinary approach to mitigating the imperfections of analog (CMOS) circuits
by digital signal processing.
• To achieve an adequate link budget for high frequency, multi gigabit, adaptive
combination of multiple antenna signals is required.
• There are power-consumption limits to pushing to A/D Converter further to the
antenna. High-rate MIMO signals would pose unacceptably high demands on power
hungry A/D converters, unless signals are optimally preconditioned before
digitization.
• The ever increasing density of using the radio spectrum call for signal separation,
interference cancellation and beam-steering. DSP algorithms can push performance
and the insights from information theory increasing set the stage for innovation.
• More intelligent spectrum access techniques (“cognitive radio”) require flexible
processor platforms, adaptive front-ends, and new adaptive algorithm
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MIMO for a mass market
Multiple antenna’s have the future
• Standardizing committees see the tremendous BB
DSP opportunities from multiple antennas
• Spectrum scarcity pushes this for < 5 GHz (signal
separation)
• Bit rate (link budget Eb/N0) pushes this for > 60
GHz (beamsteering)
Diversity
RX
Beam
forming
RX
SDMA
R
X
Interference
Collaborative
cancellation
Spatial
MUX
RX
RX
RX
R
X
radio
RR
TX
TX
TX
T
X
T
X
TX
TX
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MIMO for a mass market
Organisation
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Offered in the context of 3TU
Centered around IOP project MIMO for a Mass Market
Contributions from the 3TUs and Philips Research
Open for
– PhD students of 3TU
– People involved in the MIMO4aMM project
– Others (masters) students, 3TU and Philips employees:
admission required
– External people: admission and possibly participation fee
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MIMO for a mass market
3TU Grad Course in Wireless Systems
• Venue: rotating between Eindhoven, Twente, Delft
• Once every other week, 6 times(12 weeks)
• Tentative dates: March 29-30, April 12-13, April 26-27 (CRE at
HTC), May 10-11 (may vacation?), May 14-15, June 7-8, June 2122
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6 lecture hours per day
discussions to apply knowledge in a MIMO4aMM project focus
Credit points: tbd with EE Dept. at E,T,D
Thursday and Friday
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MIMO for a mass market
3TU Grad Course in Wireless Systems
Outline
• Radio Propagation (1 Day, Jean-Paul Linnartz)
• RF Design (1 Day, Peter Baltus)
• RF imperfections, Adaptive and Dirty RF (1 day, Peter Baltus and
Tim Schenk)
• Adaptive systems (2 days, Jan Bergmans)
• Signal Processing for Communications (2 days, Allejan van der
Veen)
• Modulation and ECC for MIMO channels (Harm Cronie)
• Software Defined Radio (1 day, Kees Slump)
• Information theory for fading channels (Frans willems)
• MIMO testbed event, papers by AIOs
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Radio Wave propagation
MIMO for a mass market
1 Day by Jean-Paul Linnartz
• Deterministic propagation models
• Statistical models and fading
channels
– Rayleigh and ricean fading
– Correlation of amplitudes in time and
frequency
– The MIMO channel
• How do wireless systems handle
channel imperfections?
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Software Defined Radio
MIMO for a mass market
1 day by Kees Slump
• software defined radio
• Radio system design
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Analog design
AD conversion
digital processor architecture
Mapping of algorithms
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RF design (RF for dummies )
MIMO for a mass market
1 day by Peter Baltus
How to design a state-of-art MIMO RF frontend
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TX and RX architectures
RF specifications and system design (I)
RF specifications and system design (II)
LNA circuit topologies and design
Mixer circuit topologies and design
Oscillator circuit topologies and design
RF and IF filter topologies and design
Transceiver implementation examples
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RF imperfections
MIMO for a mass market
1 Day by Peter Baltus & Tim Schenk)
• Why the design by
dummy does not work 
• DSP compensation
techniques, dirty RF
Transmitter
Upconversion
Phase noise
Tx antenna
Power amplifier
Nonlinear PA
Rx antenna
Low noise amplifier
Nonlinear LNA
Receiver
Downconversion
Phase noise
IQ Imbalance
Sampling
Clock jitter
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MIMO for a mass market
Adaptive systems
2 Days by Jan Bergmans
1. Introduction. Examples of adaptive systems.
2. Design of adaptive signal processing
systems.
- Structure of adaptation schemes
- Adaptive circuits, misadjustment
estimators,
adjustment circuits.
3. Maximum-likelihood parameter estimation
and adaptation:
- Maximum-likelihood parameter estimation,
- Gradient-based least-squares estimation
and
compensation,
- Worked examples: adaptive linear and
table look-up
filters, phase-locked loops, timing recovery.
4. Tracking behavior of adaptation
loops.
- Parameter-domain loop models,
- Behavior of first-order loops,
- Behavior of second-order loops,
- Multi-parameter adaptation,
simple regularization techniques.
5. Implementation of adaptation
loops:
algorithmic simplifications, impact
of loop delays
and analog artifacts.
6. Adaptive equalization and
detection:
a. Asynchronous adaptation;
b. near-minimum-BER adaptation.
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Signal Processing for Communications
MIMO for a mass market
2 Days by Allejan van der Veen
Techniques for signal separation and
parameter estimation, using arrays of
sensors, and applied to wireless
communications.
We start by deriving a signal processing model
of the wireless channel. We then recall
useful tools from linear algebra: QR, SVD,
eigenvalue decompositions, projections.
This gives us tools to discuss some more
elementary receivers: the matched filter,
the Wiener filter.
Finally we discuss important applications:
estimation of angles and delays using
ESPRIT, adaptive space-time filters, the
constant modulus algorithm.
Day 1:
1. Introduction to wireless
communication and array processing
2. Wireless channel model (Jakes
model translated to matrices)
3. Linear algebra background (QR,
SVD, eigenvalue decomposition)
4. OFDM and CDMA data models
Day 2:
5. Channel equalization and spatial
processing techniques
(matched filters, Wiener filters)
6. Parameter estimation (MVDR,
MUSIC, direction estimation,
delay estimation, ESPRIT)
7. Adaptive filtering (LMS, RLS,
CMA)
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Information theory of fading channels
MIMO for a mass market
1 day by Frans Willems
• A)
Multi-user Informatietheorie (total 4 uur)
• B)
Capacity of Wireless Channels (4 uur)
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Typical sequences
– b) Shannon’s Channel Coding Thm., Source Coding Thm.,
Rate-Distortion Thm.
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Slepian-Wolf coding
– d) Superposition Coding and the Broadcast Channel
– e)
Multiple-access Channel
– f)
Relay Channel
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a)
b)
c)
d)
e)
f)
Capacity SISO AWGN Channel
Waterfilling, freq. selective channels
Channel state information at transmitter and/or receiver
Rayleigh Fading, Average and Outage capacity
Capacity MIMO AWGN Channel
Writing on Dirty paper.
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Modulation and ECC for MIMO channels
MIMO for a mass market
1 or ½ day by Harm Cronie
• Signaling techniques and detection for MIMO:
– Uncoded transmission with ML detection, ZF filtering, MMSE filtering.
– VBLAST, DBLAST.
– The Alamouti Space-Time code.
• Error-control coding for MIMO:
– In general: bit-interleaved coded modulation and multi-level coding.
– Sparse graph codes (simple intro to turbo codes and ldpc codes)
– Iterative MIMO receivers (iterate between detector, channel estimator,
synchronizer and code)
– Analysis and Design with EXIT charts/Density evolution.
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MIMO for a mass market
Experimenting with a MIMO test bed
• Experiments
• AIO presentations
Antenna
Switch
BPF
Antenna
Switch
BPF
LNA
AGC
LO
Sample
Clock
Mixer
ADC
Control
Interface
Baseband
Processor
LNA
AGC
Mixer
ADC
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MIMO for a mass market
• END
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