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IEEE VTS UKRI Meeting – EW2013
Toward Energy Efficient 5G NetworksMehrdad Dianati
Centre for Communication Systems Research (CCSR) U i it f SUniversity of Surrey
Agendag
• Background/Motivations
• Key research areas that will affect energy efficiency of the future networks.efficiency of the future networks.
Energy efficiency research in CCSR• Energy efficiency research in CCSR
– Past and current projects– Highlights of the results
Growing Demand for PerformanceG g d
??
• Demand seems to be ever-increasing (exponentially) ….
Why energy efficiency is important?
Care for the planet and the “networkoperator’s wallet”operator s wallet
Electricity bill is a notable part of operational expenditure of mobile operators
Increasing energy cost trends
Dividing Energy Consumption of Access Networks
Gateway (PDG GGSN)
Base Station Network Server
(SGSN, HLR)Internet
Access NetworkMobile Core Network
(PDG, GGSN)
Media Server (IMS)
70-80% 2-10%10-20%Energy Consumption
(CO2-contribution)( 2 )
CCSR’s main focus
Energy and Spectrum Efficiency trade-offgy d Sp y d
Energy Effi iEfficiency
Spectral Efficiency?Efficiency?
The trade-off (point to point communication)
Technology Potential
communication)da
ta p
er Potential
M th
usef
ul d
ergy
)
Limit for Energy Efficiency
Move there
cien
cy (
uni
t of
en Limit for Energy Efficiency
Possible Improvement?
rgy
Effic un
Possible Improvement?
Ener
A desired performance metric (say
Current OperationBaseline
A desired performance metric (say Spectral Efficiency or QoE)
Towards Green Networks (1/4)
Deployment• Deployment scenarios:
optimum cell sizes
Deployment
optimum mix of cell sizeshierarchical deploymentsmulti-RAT deploymentsoverlay macro cell
smallcells
relays
EE topology
Towards Green Networks (2/4)
• Management algorithms:Management • Management algorithms:capacity managementmulti RAT coordination
Management
multi-RAT coordinationbase station sleep mode
t l d iprotocol designmulti-RAT
Zzz
EE adaptive cov./cap.p p
Towards Green Networks (3/4)
• RRM algorithms:RRM • RRM algorithms:cooperative schedulingi t f di tiinterference coordinationjoint power allocation and resource allocationresource allocation
EE j i t RRMEE joint RRM
Towards Green Networks (4/4)
• Disruptive approaches:New Architecture
• Disruptive approaches:multi-hop transmissiond h t kad-hoc networks
terminal-terminal-transmission (virtual MIMO)transmission (virtual-MIMO)cooperative multipoint arch.EE adaptive backhauling
Adaptivebackhaul
EE adaptive backhaulingcognitive/opportunistic radios & networksm lti hop radios & networksmulti-hop
Future EE architectures
Energy Efficiency Research in CCSR
• CCSR has been one of the pioneers of EE research:
– MVCE Green Radio
– EU-FP7 EARTH Projectj
– Huawei Green Comms. Projectj
Huawei Green Comms Project
• Funded by Huawei Technologies
• Work areas:– Fundamental aspects of energy efficiency inFundamental aspects of energy efficiency in
communication systems– Massive MIMO for energy efficient communicationsgy– Energy efficient RRM– CoMP techniques for energy efficiencyCoMP techniques for energy efficiency– Multi-RAT solutions
IEEE VTS UKRI Meeting – EW2013
Energy Efficient Adaptive CoMPClustering for LTE-A Systems
Efstathios Katranaras, M. A. Imran, M. Dianati
C t f C i ti S t R hCentre for Communication Systems Research University of Surrey
Background & Problem Overview
• The aim is to coordinate Inter-cell interference (ICI)( )
• The approach is Coordinated Multi Point Joint Transmission (CoMP-JT)
• In practice, only clustered CoMP deployments are feasible due to the signalling overheadsignalling overhead
• The existing studies mostly consider static clustering schemes
• We study adaptive clustering for LTE-A systems.
Basic Idea
Dynamically adjust the size and the configuration ofDynamically adjust the size and the configuration of the clusters. The clustering is adapted according to the network load and other propagation factors.
Main Results (1)Main Results (1)Comparing clustering schemes in terms of achieved average EE per UE for
various UEs-snapshots.p
Algorithms based on the proposed framework are robust to the changes of the
physical environmentphysical environment.
Main Results (2)Main Results (2)CDF of per-UE EE for various clustering schemes.
No significant EE degradation for all UEs = Minimising energy waste for UEs
th t i i ifi t i d t tithat experience no significant gain due to cooperation
Main Results (3)Main Results (3)Average EE per cell for various clustering schemes.
IEEE VTS UKRI Meeting – EW2013
EE Analysis and Optimization of Virtual-MIMO Systems
Jing Jiang, M. Dianati, M. A. Imran
C t f C i ti S t R hCentre for Communication Systems Research University of Surrey
EE Analysis and Optimization of Virtual-MIMO Systemsy
• Main Contributions:– An upper bound for EE as a function of SE
– Optimal power allocation, bandwidth ll ti b f t it t dallocation, number of transmit antennas, and
cooperating nodes.
EE Analysis and Optimization of Virtual-MIMO Systems
0 45
0.5
0.45
0.5
Virtual MIMO Systems
0.35
0.4
0.45
oule
)
0.35
0.4
0.45
oule
)Bandwidth Senario II
BandwidthSenario I
0.25
0.3
ienc
y (
MB
its/J
o
0.25
0.3
cien
cy (
MB
its/J
0.15
0.2
Ene
rgy
Effi
c
MIMO (Upper Bound)
Virtual MIMO with CF(Upper Bound)
Virtual MIMO with CF
0.15
0.2
Ene
rgy
Effi
c
MIMO (Upper Bound)
MIMO (Simulations)
Virtual MIMO with CF(U B d)
0.05
0.1Virtual MIMO with CF(Simulations)
Virtual MIMO with AF(Upper Bound)
Virtual MIMO with AF(Simulations)
0.05
0.1(Upper Bound)
Virtual MIMO with CF(Simulations)
MISO (Upper Bound)
MISO (Simulations)
0 5 10 15 200
Spectral Efficiency (bits/s/Hz)
(b)
0 5 10 15 20
Spectral Efficiency (bits/s/Hz)
(a)EE performance of the 2-by-2 virtual-MIMO system with G=10dB (Bandwidth scenario I is considered in (a) and Bandwidth(Bandwidth scenario I is considered in (a) and Bandwidth scenario II is in (b) )
EE Analysis and Optimization of Virtual-MIMO Systemsy
• Main Conclusions:Th lt d t t th t h SE i l EE i– The results demonstrates that when SE is low, EE is dominated by the load-independent circuit power.
– As SE increases, transmit power contributes more to the EE performancethe EE performance.
Compared to the ideal MIMO system virtual MIMO– Compared to the ideal MIMO system, virtual-MIMO system requires more energy for the cooperation, but outperforms the non-cooperative MISO.p p
IEEE VTS UKRI Meeting – EW2013
B ff A d E Effi i tBuffer Aware and Energy Efficient Scheduling of Real Time Traffic for OFDMA
Systems
Inventors: M. Dianati, M. SabaghCo-Inventors: M. A. Imran, R. Tafazolli
Centre for Communication Systems Research University of SurreyUniversity of Surrey
Background & Prior Techniques
• The existing scheduling scheme are designed toThe existing scheduling scheme are designed to optimise spectral efficiency for operators and maintain QoS for users (see attached document).
• The aim is to propose energy efficient packet scheduling for real time traffic in OFDMA systems.
Page 25
System Model
Figure 1. System Model Figure 2. eNodeB Downlink Frame
Page 26
General Framework
Scheduling Framework Traffic Model
Page 27
Principle Schemes
Page 28
Results (1)
20 ti 150 ti20 active users 150 active users
Page 29
Results (2)
.
Page 30
Results (3)
Page 31
IEEE VTS UKRI Meeting – EW2013
I t f S ti l C l ti EE fImpacts of Spatial Correlation on EE of massive-MIMO Systemsy
Jing Jiang, M. Dianati, M. A. Imran
C t f C i ti S t R hCentre for Communication Systems Research University of Surrey
System Model
Page 33
Results and Discussion
EE simulations and UBs for Rayleigh-fading MIMO channels (Constant spatial correlation with φt = φr = 0.5 is considered in (a), and the results for i.i.d. fading channels are in (b).)
Page 34
Results and Discussion
The relation between EE and SE for exponentially correlated MIMO channels and φ = φ = 0 5 (The effects of loadMIMO channels and φt = φr = 0.5 (The effects of load-independent circuit power on EE are also shown.)
Page 35
Simulation Results and Discussion
The EE performance as a function of coefficient φ (where φt=φ =φ) for both constant and exponential correlated Rayleigh=φr=φ) for both constant and exponential correlated Rayleigh-fading MIMO channels at RM = 20 bits/s/Hz.
Page 36
Th k YThank YouDr Mehrdad DianatiDr. Mehrdad Dianatim.dianati@surrey.ac.uk
Acknowledgement: Dr. M. A. Imran, Dr. E. Katranars, Dr. J. Jiang, Mr. M. Sabagh, and Dr. Amir Akbari have contributed to the technical work and the preparation of the slidestechnical work and the preparation of the slides
CONFIDENTIAL, EARTH Project.
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