shedding light on future wireless communications · c,b
TRANSCRIPT
November 9, 2011
Professor Harald Haas
with acknowledgements to:
Research Fellows and PhD Students I had the pleasure to work with in the past few years
Public funding bodies and industry who have been supporting my research
Shedding Light on Future Wireless Communications
School of EngineeringInstitute of Digital Communications
What is wireless communications?
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© The University of Edinburgh2
http://stara-sofia.blogspot.com/2009/11/chusseau-flaviens_30.html
Wireless communications –An essential utility
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© The University of Edinburgh3
> 5 billion(7 billion people)> 1.4 million
Cooper, et al., "Radio Telephone System", US Patent number 3,906,166; Filing date: Oct 17, 1973; Issue date: September 1975; Assignee Motorola
Mobile Data Usage per Month
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© The University of Edinburgh4
Year
Exa
byte
spe
r Mon
th
6.3
3.8
2.2
1.20.6
0.24
Network Capacity per Device vs. Forecast Traffic per Device
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© The University of Edinburgh6
Forecast Traffic per Device
Network Capacity per Device
Year
Net
wor
k ca
paci
ty /
Fore
cast
traf
fic (M
B/M
onth
)
Shor
tfall
97.2
%
Basic questions
1. Are we using the existing radio frequency spectrum most efficiently for wireless communications?
2. Do we know what “most efficiently” is?
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© The University of Edinburgh7
Do we know what “most efficiently” is?Claude E. Shannon helps, but ...
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© The University of Edinburgh8
Capacity in bits/second Bandwidth Noise power
Path gain (<< 1)Transmit power
When should be reuse...?
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© The University of Edinburgh10
Do we better give each link half the bandwidth(each one having half the maximum capacity) andhave no interference, or should both links transmit using the full bandwidth, but allowinterference?
„Simple“ frequency reuse concept
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© The University of Edinburgh12
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Full frequency reuse
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Self-organised interference coordination through busy bursts
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© The University of Edinburgh15
B D
timeData – A Tx
B Tx
Mini Slot
Data – C Tx
Ib
IC,B<Ithr!
Data – A Tx
A C C
Concept of reuse taken further…Single-input single-output (SISO)
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© The University of Edinburgh17
Concept of reuse taken further…multiple-input multiple-output (MIMO)
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Concept of reuse taken further…multiple-input multiple-output (MIMO)
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© The University of Edinburgh22
Successive Interference Cancellation
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© The University of Edinburgh23
ABCD
A+B+C+D
A+B+C+D
A+B+C+D
A+B+C+D
Detect the relatively strongest symbol and subtract from all other streams
A+B+C+D
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© The University of Edinburgh24
ABCD
AB+C+D
B+C+D
B+C+D
B+C+D
Successive Interference Cancellation
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© The University of Edinburgh25
ABCD
AB+D
CB+D
B+D
Successive Interference Cancellation
Barriers / Disadvantages
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© The University of Edinburgh27
Spatial multiplexing MIMO significantly improves spectral efficiency, but:
Suffers from inter-channel interferenceresulting in high computational complex algorithms (e.g., Vertical – Bell Labs Layered Space Time (V-BLAST) algorithm)Requires inter-antenna synchronisation (IAS)Requires multiple RF-chains (→ expensive)Suffers from error propagation
Spatial Modulation: How does it work?
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A(A)
B(A)
C(A)D(A)
A(D)
B(D)
C(D)D(D)
A (Tx1)
B (Tx2)
C (Tx3)
D (Tx4)
Signal Constellation
Spatial Constellation
Re
Im
Im
Im
Re
Re
© The University of Edinburgh
SM Principle
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A(C)
B(C)
C(C)D(C)
A (Tx1)
B (Tx2)
C (Tx3)
D (Tx4)
Spatial Constellation
Re
Im
Im
Re
t1
Signal Constellation Diagram
C B D A B CSpatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
t1 t2 t3
© The University of Edinburgh
SM Principle
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A(D)
B(D)
C(D)D(D)
A (Tx1)
B (Tx2)
C (Tx3)
D (Tx4)
Spatial Constellation
Re
Im
Im
Re t2
Signal Constellation Diagram
© The University of Edinburgh
C B D A B CSpatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
t1 t2 t3
SM Principle
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A(B)
B(B)
C(B)D(B)
A (Tx1)
B (Tx2)
C (Tx3)
D (Tx4)
Spatial Constellation
Re
Im
Im
Re
t3
Signal Constellation Diagram
© The University of Edinburgh
C B D A B CSpatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
Spatialsymbol
Signalsymbol
t1 t2 t3
Key question
Does MIMO and smart interference management in cellular networks solve the future capacity problem?
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35 © The University of Edinburgh
The electromagnetic spectrum
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© The University of Edinburgh37
Radio-waves
Infra-red Visible Ultra-
violet X-rays Gammarays
Frequencyx 10 000 =
.
Drivers for visible lightcommunication (VLC)
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© The University of Edinburgh39
“Looming spectrum crises“: FCCEnergy efficiencySecurityAvailabilityAdvancements in Solid-State LightingCostThe Internet of Things
Forecast 7 trillion wireless devices in 2020 – 1000 per person on earth – source: World Wide Research Forum (WWRF)
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What is different?
System
Radiofrequency
Incoherent light
Information
carried on electric field
carried on optical intensity
Signal
bipolar
unipolarnon-negative
complex valued
real valued
© The University of Edinburgh
Traditional digital modulationtechniques
Pulsed modulation such as on-off keying
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© The University of Edinburgh41
Time
Intensity
1 1 1 10 0 00 0
On
Off
Thres.
Finite slope limits achievable data rates
Im
ReOff On
Overcoming data rate limitation ofOOK - Transmitter
November 9, 2011© The University of Edinburgh
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Orthogonal Frequency
Division Multiplexing
(OFDM)
AG
ETime
Frequency
Re
Im
G H
DCBA
E
LKJI
PONM
One symbol encodes log2(16) = 4 bits in this example
… 1 0 1 1 …
… 0 0 1 1 …
… 0 0 0 1 …
F
1 0 1 1
-fold increase in capacity
DC biased optical (DCO) OFDM
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© The University of Edinburgh43
124 Mbps real-time andfrom off-the-shelf LED
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Data rates in aircraft cabin
wavelength reuse of 2
wavelength reuse of 3
© The University of Edinburgh
wavelength reuse of 3
09/11/201153
Image credits (via Flickr)
“iPhone” by Vincent Huang “Ooievaarsnest in aanbouw” by Vincent Teeuwen“Luces Nubladas” by David Cabrera “Charing Cross” by Jenny Koske“expl1196” by NOAA Photo Library “ILM: Industrial Lighting and Magic” by Photogism Group “easyJet A321 Cabin” by WebDub‘s“Unloved Box, Bentley, Hampshire” by Mike Cattell