Cooperative Diversity for
Wireless Networks.
Dr. Noha Ossama El-Ganainy
Lecturer, Arab Academy of Science and Technology
Alexandria, Egypt.
Biography

PhD degree of Electrical Communications, Faculty
of Engineering, Alexandria University, Alexandria,
Egypt, 2010.

Worked for different institutions in Egypt.

More than 15 publications in international
journals and conferences.

Won the young scientist awards 2011 from URSI
GA 2011 “Union Radio Scientific Internationale”
Presentation Outlines.

Developments of cellular systems.
Next
generation systems requirements.

Cooperative diversity: the smart solution.

Discussions and conclusions.
Developments of Cellular Systems.
2G
2.5G
3G
2G
2.5G Services
4G
Services
3G and
Services:
Voice
MobileTV
Internet
Mobile
Messaging
Ultraon
Connectivity
Video
demand
Image
Transmission
Adaptive
and Smart systems
Video conferencing
Location-based services
4G.
Next Generation Systems
Requirements.

Next generation systems are challenged with the growing
demand for high-rate, high-quality wireless services.
 Advanced
algorithms are recommended to increase the
data rate and to guarantee the quality-of-service QOS
desired by each media class.
 It
is also essential to efficiently allocate the network
resources to improve the transmission rate and capacity.
 Advanced
signal processing, adaptive techniques, and using
various forms of diversity are highly recommended.
Spatial Diversity
 Provided
independently faded versions of the same signals
at the receiver which enhances the detection.
 It
combats the channel deteriorations and the deep fades
 Results
in more efficient performance compared to any
other signal processing tool.
MIMO Transmissions
 They
provided the spatial diversity but hard to implement
for single terminals .
 Widely
used and served in the development of a number
of communication systems.
Cooperative Communications

Allows single-antenna mobiles to share their antennas in a
manner that creates a virtual MIMO systems.

Gain the benefits of MIMO transmissions with no additional
cost to the network.

Numerous theoretical models of cooperative signaling were
proposed.

Can serve, in aware transmissions, to efficiently use the
available network resources.

We are concerned in wireless networks, of cellular or ad-hoc
variety, where the wireless terminal increase their quality of
service via cooperation.
Historical Background
 Is
a development of the classical concept of Relay
channels introduced by T. A.Cover and El-Gamal in 1979.
 Was
a model of a three-node networks consisting of a
source, a destination, and a relay.
 The
Relay unique role is to help the source. The capacity
was studied under AWGN channel.
 While
in a cooperative environment the users act as both
information sources as well as relays.
 The
studies are interested in transmission in a fading
channel.
Cooperative Communications
USER 1
USER 2
Destination
Independent fading
paths
Cooperative Communications
 Cooperative
communication provides independently
faded versions of the transmitted signal at the
ultimate receiver.
 Single-antenna
mobiles
in a multi-user
framework are allowed
to share their
antennas and generate
a virtual multipleantenna transmitter.
Cooperative Communications
Requirements
 The
base station ties-up a number of users as
user-partner, pairs are highlighted.
 The
base station must separately receive the
original and relayed data.


In cellular systems, hardware requirements
are essential at the terminals as they receive
down-link and up-link transmissions.
Half-Duplex and Full-Duplex.
Different Cooperative Signaling
 Amplify-and-Forward:
o Each user receives, amplifies, and retransmits a noisy
version of the partner’s signal.
o The destination combines the information sent by the
user and partner to make a final decision on the
transmitted bit.
o The destination must have efficient estimation process
to equalize the effect of the inter-user channel.
Amplify-and-Forward
Different Cooperative Signaling

Coded Cooperation:
o Integrates cooperation into channel coding, different
portions of each user’s codeword is sent via two
independent fading path (users).
o Requires efficient code design.
Different Cooperative Signaling
Decode-and-Forward:
o The partner is assigned to detect/estimate the user’s
signal and forward it to the destination after encoding
it.
o The destination must have access to the inter-user
channel coefficient to do optimal decoding.
o Adaptive signaling is possible, at low SNR the partner
can switch to non-cooperative mode.
Different Cooperative Signaling
Different Cooperative Signaling
Compress-and-Forward:
The partner is allowed to compress the user’s
signal and forward it to the destination without
decoding the signal.
Decode-and-Forward Algorithm.
 During
odd intervals,

During even
intervals,
all user’s the
transmitted
user and partner
signaltheir
is a
send
combinationtoof its
information
each
andthe
own other
data and
to
the
partner’s
information
destination.
estimate
Also,
they each
are spread
by the to
assigned
appropriate
detect/estimate
code.
the
partner’s
information.
Inter-User Channel
 The
value of Pe12 affects the estimation of the partner’s data
which has the potential to control the efficiency of the
cooperation process.
b1
User 1
PPe12
e12
bˆ1
User 2
Decode-and-Forward Algorithm.
User 1 Tx
b11
b12
b13
b 13
b14
b14
bˆ 24
b̂ 23
User 2 Tx
b21
b22
b 23
b
3
2
b24
b̂13
Period
1
2
Non-Cooperative
3
4
Cooperative Periods
b24
b̂14
5
6
Time
Odd Duration
 The
received signal at the destination during the odd
interval is
Y
odd
 K10 X
odd
1
 K 20 X
odd
2
Z
odd
 K10a12b1C1  K 20a22b2C2  Z
odd
 While the received signal at the partner is
Y2
odd
 K12 X
odd
1
Z
odd
 K12 a11b1C1  Z odd
Partner detector
During
the odd intervals the partner’s
estimate and the Pe of the transmitted bit
are
 1 T 
ˆ
b1  sign
c1 Y0   sign K12a11b1  n0 
 Nc


Nc

Pe1 2  Q K12a11

1





Even Duration
The
received signal at the destination
during the even interval is
Y even  K10 X 1even  K 20 X 2even  Z even


 K10a13b1C1  K10a13b2C2  K 20a23b2C2  K 20a23b1C1  Z even




1 2
a11  a122  a132  P1
L
1 2
2
2
a21  a22
 a23
 P2
L
The Receiver Model
 The
destination begins by calculating the soft
decision statistics for both intervals
yodd
 1 T odd 


1
T
even
 sign 
c1 Y0  , yeven  sign 
c1 Y0 

 Nc

 Nc

which results in
yodd  K10a12b1  nodd
yeven

 K10a13b1  K 20a23b1  neven
The Receiver Model
 The
destination combines the information extracted
during both intervals to obtain the transmitted bit
 yodd 
y

y
 even 
 The
NC
o
MAP detector is used to extract b1 given y
bˆ1  arg max p y b1
b1
 The
probability of detecting b1 given y is
1
p y b1 1


1
p y b1  1
The Optimal Detector
The
optimal detector is found to be
1  P A
1
1 v1T y
e12
e
 Pe12 Ae
v2T y


1  P A
e12
1
v1  K10a11
K10a12   K 20a22 T
v2  K10a11
K10a12   K 20a22 T
A  exp  2 3 
 2  K10a12
 3  K 20a22
NC
0
NC
0
1  v1T y
e
 Pe12 Ae
 v2T y
The Sub-Optimum Detector Model
 The
optimal detector is complex and doesn't have
a closed-form expression for the resulting
probability of bit error.
A
sub-optimal detector ‘modified λ-MRC’ is
proposed instead.
bˆ1  signK10a12  K10a13  K20a23 y 
 The
information received during the even duration
is waited by .
Optimum vs Sub-Optimal Detector
 For
perfect inter-user Pe12 , the optimal
detector reduces to the sub-optimal model.
-MRC is simple and computationally
undemanding.
 The
 It
has a closed form expression which
provides a simulation-free analysis.
-MRC may run in a blind mode, and 
is may be calculated blindly.
 The
Optimum vs Sub-Optimal Detector
As Pe12
increases, the equivalence
between the two models disappears.
For
some transmissions conditions, a
performance loss will take place.
The Sub-Optimum Detector Model
MRC
Channel
Estimation
~
Xodd
Y
Matched
Filter
Decision
~
Xeven

The Weighting Factor 
 Is
used to weight the information received
from the partner before the combining
stage.
 Is
a measure of the destination confidence of
the partner’s transmitted bit.
 Ranging
from 0 to 1 and is dependent on
the inter-user channel error Pe12 .
 Controls
the efficiency of cooperatrion.
The Weighting Factor 
 The
value of Pe12 affects the estimation of the partner’s data
which is reflected on the value of the proper .
b1
User 1
PPe12
e12
 0
1
bˆ1
User 2
The Probability of Error
The
Pe is given by;
 vT v 
 vT v 
Pe  1  Pe12 Q 1    Pe12Q 2  
 vT v 
 vT v 
  
  
v1  K10a12
K10a13   K 20a23 T
v2  K10a12
K10a13   K 20a23 T
v  K10a12
 K10a13  K 20a23 T
NC
0
NC
0
NC
0
The Probability of Error
destination wants to use the value of 
that minimizes Pe for given transmission
conditions.
 The
 The
destination may not have access to the
value of Pe12 , an adaptive estimation and
feedback from the users is essential.

For given transmission conditions, the
maximum possible performance is found by
making use of an “optimal” value of 
(found) numerically.
Pe vs Pe12
Theoritical Probability of Error Performance
-1
Probability of Error - Pe
10
-2
10
-3
10
Pe12=0.5- Theoritical Performance
Pe12=0.1
Pe12=0.05
Pe12=0.005
Pe12=0.0001
-4
10
-2
0
2
4

6
8
10
The performance analysis of the cooperative algorithm in terms of the
probability of error for different values of inter-user channel
To Cooperate or Not to Cooperate?
0
Pr of Outage
10
Coop
Non-Coop
-1
10
0
0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018
Threshold
0.02
To Cooperate or Not to Cooperate?
 Power Tradeoff
More power is may be needed to provide
cooperation?
The baseline power will be reduced due to diversity.
Smart power allocation is used to efficiently utilize the
power resources.
 Rate Tradeoff
Is cooperation causing losses of rate in the system?
Due to the spectral efficiency improvement, the
channel code rates is may be increased.
 Cost
Is positively approved by several studies.
Discussions and Conclusions
 The
cooperative communications concept
provides the benefits of MIMO transmission at
no additional cost to the network.

It provides higher capacity and enhanced
throughput compared to non-cooperative
transmissions.
 It
efficiently allocates the network resources
which improves the network capabilities and
enhances the overall performance.
Discussions and Conclusions
Decreased
sensitivity to channel variations.
Security
the user’s data has to be encrypted before
transmission, the partner can detect the user’s
data without understanding it.

Complexity of Mobile Receiver
Increased security, signal separation.
How
to decide the partnership?
 Partners assignments and reassignments
References
 A. Nosratinia,T. Hunter, and A. Hedayat,
“Cooperation Communication in Wireless Networks,”
IEEE Communication Magazine, October 2004,
pp. 74–80.

Noha O. El-Ganainy and Said E. El-Khamy,
“A New Practical Receiver for a Decode-and-Forward
Cooperative CDMA Systems based on a Blind λCombiner,”
Progress in Electromagnetic Research Letters PIERL,
Issue #28, page 23-36, 2012.
Thank You