1. Abstract
Resource Allocation in Emerging 4G Cellular Systems: LTE-Advanced
Hammadullah Muhammad Afaq Ahmad Muhammad Waqas
Supervisor: Dr. Guftaar Ahmad Sardar Sidhu
Department of Electrical Engineering, Comsats Institute of Information Technology Islamabad.
System Model
Simulation
Long Term Evolution (LTE) is an
advanced standard for wireless
communications technology. The
resource allocation in LTE has been
considered as a fruitful field for
enhancing the system performance.
In this research, we consider an
OFDM based dual hop device to
device (D2D) communication
network which can operate under
Amplify and Forward (AF) or Decode
and Forward (DF) relay transmission
mode.
Exploiting convex optimization
techniques, analytical solutions are
derived. Simulations are presented
to validate the proposed schemes.
Objective
1. K. Doppler, M. Rinne, C. Wijting, C. B. Ribeiro, and K. Hugl, “Device to-device communication as an underlay to LTE-Advanced
networks, IEEE Communications Magazine, vol. 47, no. 12, pp. 42–49, Dec. 2009.
2. G. A. S. Sidhu, F. Gao, W. Chen, and W. Wang, ''Resource allocation in relay-aided OFDM cognitive radio networks'' IEEE Trans. On
Vehicular Tech. (TVT), Vol. 62, No. 08, pp. 3700--3710, October 2013.
3. 3rd Generation Partnership Project (3GPP), Technical Specification Group (TSG) Radio Access Network:(RAN),2000, 3G TR25.833Vl
.
Problem Formulation
Using Decode and Forward Relay:
Conclusion
In this work a relay aided D2D
network is considered which works
under the cellular network.
The trivial solution from proposed
subcarrier pairing schemes
improves the sum throughput.
System Model
References
The main goals of this project are
to investigate the resource
allocation techniques in LTE-
Advanced cellular systems.
Design the optimal algorithms for
power allocation and the subcarrier
permutation schemes over two
hops.
Method
Duality Theory.
Subgradient Method.
Water filling Algorithm.
CC2CAF
n =
1
2
log2
Ã
1 +
qnjhnj2
pnjgnj2
qnjhnj2(w2
r + Rnj fMnj2) + (w2
d + SnjeTj2)(pnjgnj2 + ¾2
r + RjfMj2)
!
CD2DAF
n =
1
2
log2
Ã
1 +
SnjTnj2
RnjMnj2
SnjTnj2(w2
c + pnjegnj2) + (w2
e + qnjehj2)(RnjMnj2 + ¾2
r + pjegj2)
!
max
pn ;qn
NX
n=1
CC2CAF=DF
n +
NX
n=1
C(D2DAF=DF )
n
s.t.
NX
n=1
Pn · Pt
NX
n=1
Qn · Qt
CC2CDF
n = min
µ
log2
µ
1 +
Pnjgnj2
Rnj¹mj2 + ¾2
¶
;log2
µ
1 +
Qnjhnj2
Snj¹tj2 + ¾2
¶¶
CD2DDF
n = min
µ
log2
µ
1 +
Rnjmnj2
Pnj¹gj2 + ¾2
¶
;log2
µ
1 +
Snjtnj2
Qnj¹hj2 + ¾2
¶¶
min
¸
D(¸; ´)
s.t.¸; ´ ¸ 0
¸i+1 = ¸i + ±
Ã
pT ¡
NX
n=1
pn
!
Optimal Solution
Pn =
Ã
1
¸
¡
Rn
fMn
2
+ ¾2
g2
n
!
Pn =
Ã
1
¸nXn
¡
Rn
fMn
2
+ ¾2
g2
n
!