Full Presentation of Mimo technology

1. By-
Joseph Y (09-801)
Vinayak B (09-804)
Rashmi D (09-809)
Alisha K (09-820)

2. Why MIMO?
 There is always a need for increase in performance in
wireless systems
 Significant increase in spectral efficiency and data
rates
 High Quality of Service (QoS)
 Wide coverage, etc.
 Wireless channel that we are using is very unfriendly
 Suffers from Co–channel interference and signal level
fading
 It provides a limited bandwidth
 power falls off with distance

3. Aspirations (Mathematical) of a
System Designer
High data rate
Quality
Achieve
“Channel Capacity (C)”
Minimize Probability of Error
(Pe)
Real-life Issues
Minimize complexity/cost of
implementation of proposed
System
Minimize transmission power
required (translates into SNR)
Minimize Bandwidth (frequency
spectrum) Used

4. MIMO System solutions
 By using Multiple Output Multiple Input (MIMO) systems
 Diversity gain mitigates the fading and increases
coverage and improves QoS
 Multiplexing gain increases capacity and spectral
efficiency with no additional power or bandwidth
expenditure
 Array gain results in an increase in average receive
SNR.
 Spatial Diversity and Spatial Multiplexing can be
conflicting goals

5. Antenna Configurations
 Single-Input-Single-Output (SISO) antenna system
 Theoretically, the 1Gbps barrier can be achieved using this
configuration if you are allowed to use much power and as
much BW as you so please!
 Extensive research has been done on SISO under power and
BW constraints. A combination a smart modulation, coding
and multiplexing techniques have yielded good results but far
from the 1Gbps barrier
channel
User data stream
User data stream

6. MIMO Antenna
Configuration
 Use multiple transmit and multiple receive antennas
for a single user
 are defined by Spatial Diversity and Spatial
Multiplexing
User data streamUser data stream
.
.
1
2
MT
.
.
.
1
2
MR
.
.
.
.
.
channel

7. Spatial Diversity and Spatial Multiplexing
 Spatial Diversity
 Signal copies are transferred from multiple antennas or
received at more than one antenna. No increase in the
data rate.
 Redundancy - employing an array of antennas, with a
minimum separation of λ/2 between neighbouring
antennas.
 Space-time coding.
 Spatial Multiplexing
 the system is able to carry more than one data stream
over one frequency, simultaneously.
 Increase in data rate.

8. Spatial Diversity
 Improves the signal quality and achieves a higher
SNR at the receiver-side.
 Principle of diversity relies on the transmission of
structured redundancy

9. Spatial Multiplexing
 MIMO channels can be decomposed into a number of R parallel
independent channels → Multiplexing Gain
 Principle: Transmit independent data signals from different antennas to
increase the throughput, capacity.

10. Fading Channels
 Fading refers to changes in signal amplitude and phase caused by
the channel as it makes its way to the receiver.
 A fading channel is a communication channel comprising fading.
 SNR decreases.
FADING
Multipath time delay
spread
Doppler shift
FLAT
FADIN
G
FREQUENCY SELECTIVE
FADING
FAST
FADING
SLOW
FADING

11. Fading Channels
 Define Tspread to be the time at which the last reflection arrives and
Tsym to be the symbol time period
Time-spread of signal
Frequency-selective Frequency-flat
Tsym
Tsprea
d
time
freq
1/Tsym
Occurs for wideband signals (small
Tsym)
TOUGH TO DEAL IT!
Tsym
Tsprea
d
time
freq
1/Tsym
Occurs for narrowband signals (large Tsym)
EASIER! Fading gain is complex Gaussian
Multipaths NOT resolvable

12. MIMO capacity on fading channels
The capacity increase can be seen by comparing MIMO systems with SISO, SIMO,
and MISO systems
SISO:capacity is given by Shannon’s classical formula:
Where B is the BW and h is the fading gain
SIMO (with M transmitting antennas), the capacity is given by
MISO (with M transmitting antennas), the capacity is given by
)
2
1(
2
log hsnrBC 
)
1
2
1(
2
log 


m
n
n
hsnrBC
)
1
2
1(
2
log 








N
n
n
h
N
snr
BC

13. MIMO capacity on fading channels
The capacity for MIMO systems can have the following forms (Assuming Tx
antennas = Rx antennas = N):
A) If the channel is not known at the transmitter:
Where Es is the total power, σ2 is noise level of AWGN
Hence the power is equally shared by each channel
The capacity grows linearly with the number of antennas
B) If the channel is known at the transmitter
)
2
2
1(
2
log
n
h
N
s
E
NC 










 

















N
n n
hn
E
C
1
)
2
2
1(
2
log


14. MIMO System Model
y = Hs + n
User data stream
.
.
User data stream
.
.
.
.
Channel
Matrix H
s1
s2
sM
s
y1
y2
yM
y
Transmitted vector Received vector
.
.
h11
h12
Where H =
h11 h21 ……..
hM1h12 h22 ……..
hM2
h1M h2M ……..
hMM
. . …….. .
MT
MR
hij is a Complex Gaussian
random variable that models
fading gain between the ith
transmit and jth receive
antenna

15. Channel Matrix H
 In addition, assume slow fading
 MIMO Channel Response
 Taking into account slow fading, the MIMO channel impulse response is constructed as,
Time-spread
Channel Time-variance
 Because of flat fading, it becomes,
a and b are transmit and
receive array factor vectors
respectively. S is the
complex gain that is
dependant on direction and
delay. g(t) is the transmit
and receive pulse shaping
impulse response
• With suitable choices of array geometry and antenna element patterns,
H( ) = H which is an MR x MT matrix with complex Gaussian i. i. d random variables
• Accurate for NLOS rich-scattering environments, with sufficient antenna spacing at
transmitter and receiver with all elements identically polarized

16. Capacity (contd)
The capacity of Receive or Transmit Diversity grows
logarithmically with the number of antennas
Capacity of MEMO increases linearly with the number
of antennas

17. MIMO Design Criterion
 MIMO Systems can provide two types of gain
Spatial Multiplexing Gain Diversity Gain
• Maximize transmission rate
(optimistic approach)
• Use rich scattering/fading to
your advantage
• Minimize Pe (conservative
approach)
• Go for Reliability / QoS etc
• Combat fading
 System designs are based on trying to achieve either goal or a
little of both
 If only I could have both! As expected, there is a tradeoff

18. Diversity
 Each pair of transmit-receive antennas provides a signal
path from transmitter to receiver. By sending the SAME
information through different paths, multiple
independently-faded replicas of the data symbol can be
obtained at the receiver end. Hence, more reliable
reception is achieved
 A diversity gain d implies that in the high SNR region,
my Pe decays at a rate of 1/SNRd as opposed to 1/SNR
for a SISO system
 The maximal diversity gain dmax is the total number of
independent signal paths that exist between the
transmitter and receiver
 For an (MR,MT) system, the total number of signal paths
is MRMT
1 ≤ d ≤ dmax= MRMT
 The higher my diversity gain, the lower my Pe

19. Orthogonal Frequency Division
Multiplexing (OFDM)
 As the data rate increases in a multipath
environment, the interference goes from flat fading
to frequency selective (last reflected component
arrives after symbol period). This results in heavy
degradation
 Most popular solution to compensate for ISI:
equalizers
 As we move to higher data rates (i.e.> 1 Mbps),
equalizer complexity grows to level of complexity
where the channel changes before you can
compensate for it!
 Alternate solution: Multi-carrier Modulation (MCM)
where channel is broken up into subbands such
that the fading over each subchannel becomes flat
thus eliminating the problem of ISI
Multi-carrier Modulation
FDMA OFDM

20. OFDM Spectral Efficiency
Rs symbols/s
Rs/ 3 symbols/s
• The spectral efficiency of an OFDM-
(PSK/ASK) system is same as compared
to using the (PSK/ASK) system alone
• Spec eff = log 2 M bits/s/Hz
• However, you have successfully
converted an ugly channel into a channel
that you can use
• easy to implement
• Used in IEEE 802.11A, .11G,
HiperLAN, IEEE 802.16

21. Summary/Conclusions
 MIMO Systems are getting us closer to
the 1Gbps landmark (aspiration 1)
 At the same time, they provide reliable
communications (aspiration 2)
 Different architectures available for use
 Developing efficient network protocols
for a MIMO PHY layer is an area of
open research