Registration Seminar on Green Communication
Green Communication
Department of Electronics & Communication
EngineeringNational Institute of Technology, RourkelaVarun Kumar
andProf . Sarat Kumar Patra
Outline:ObjectiveLiterature SurveyTechnical ChallengesOpen
Research Issues in Green CommunicationSimulation ResultFuture
Work
Introduction:Green communication is a growing research area in
wireless communication. To make an energy efficient wireless
communication without disturbing the other performance matrices
(Capacity, BER etc).
ObjectiveTo protect environment from harmful EM radiation
reducing green house gas Reducing operational cost for wireless
network.
Holistic Green Communication Research Vision:
Literature Survey
Continued--Year TitleAuthorContribution2013Energy Aware Power
Allocation in Cooperative Communication System with Imperfect
CSI,``IEEE Transaction on Communications Rajiv Devrajan, Anjana
Punchihewa, Vijay K BhargavaPower optimization and finding end to
end SNR in cooperative networks
2013Massive MIMO in the UL/DL of cellular Networks: How Many
Antenna Do We Need?,``IEEE Journal on Selected Area in
CommunicationJakob Hoydis, Stephan ten Brink, Merouane DebbahNumber
of Antenna optimization using different detection scheme2014An
overview of Massive MIMO: Benefits and Challenges, IEEE Journal of
Selected Topics in Signal ProcessingLu Lu, Geoffrey ye Li, Rui
zhangFundamental of Massive MIMO and its design challenge
2015Energy-Spectrum Efficiency trade off for a Massive SU-MIMO
System with Transceiver Power Consumption , in Proceeding
ICCSudarshan Mukherjee and Saif Khan MohammedRelation between
channel gain , number of antenna, EE and SE
Energy Consumption Survey
Continued- Some Guidelines
Wireless Resources Trading Model (Challenges):
Power Consumption Parameter in wireless domain:
Spectrum Utilization
RefNokia Research Centre
Complex vs Simple Wireless Model and Adaptive Modulation
Demodulation Approach:
Some Existing Solution for Energy Saving in Wireless Domain:
There are technique like MIMO HARQ (3G/4G)Beamformingwireless
mess networks Distributed equipment
Impact of Proper Channel Estimation for Energy Saving:
Detection and Estimation:
MF,ZF,MMSE, MLE,MAP, MVU
Emerging Area or Open Research Area for Green Communication:
MIMO (3G/4G) or Massive MIMO(5G)Co-Operative Communication (D2D
Communication)Space Time Wireless Communication (O-STBC, STTC)
Role of Multiple Antenna SystemTo increase diversityTo increase
multiplexing gainSNR improvement through beamforming
Massive MIMO Architecture:
1st Case Study
Massive SU-MIMO system with Transceiver Power Consumption
Simulation Result:
Observation and Scope in Above Analysis:Observation:EE
efficiency increase with increase in SE. (If SE is very small)If
the channel gain increases the EE gradually increases, but after
certain limit EE almost remain constant.If number of antenna
increases the spectrum efficiency increases taking channel gain
constant.At very low gain and high SE nearly 50% power is consumed
by power amplifier for fixed SE/fixed channel gain and rest of
power is utilised by other operation.
Note: Above analysis has been performed for Massive SU-MIMO when
perfect CSI is known and channel are uncorrelatedScope or Future
Works:Massive MU-MIMO with perfect CSI. (Same Analysis)Massive
SU/MU-MIMO with imperfect CSI or when the channel is correlated.
(Same Analysis)Low complexity precoder design for large number of
array processing.
2nd Case Study:Massive MU-MIMO in UL/DL of Cellular
Networks:
Mathematical Model for Wireless Channel
continued--
Massive MIMO Effect
Numerical Result:
Continued --
Continued--
Observation and Scope of the above analysis:Observation:Maximum
capacity depends on inter-cell interference and total no of
interfering cell.MMSE/RZF gives better performance in UL/DL
scenario in comparison to MF/(Eigen BF).If total number of active
antenna increases the ergodic achievable rate also gradually
increases.
Note: Large number of antenna is utilized in adaptive manner .
Two type of detector/precoder performance has been observed in non
cooperative multi cellular UL/DL scenario. All UT are equi-spaced
and equal in number with respective BS.Scope or Future Works:If UT
are not equi-spaced from respective BS and not equal in number
across each cell.Case study in cooperative; multi cellular Massive
MU-MIMO scenario.Other technique may be cross checked like,
MMSE-SIC, ZF-SIC, implementation of convex optimization for
performance improvement of eigen beamforming.
Energy-Aware Power Allocation in Co Operative Communication
System with Imperfect CSI
Channel Model and Transmission Scheme:
Total Transmit Power Minimization with Channel Estimation
Errors
Optimal transmit powers for the source and relay to maximize the
SNR when channel estimation errors are present
Simulation Result
Continued---
Observation and Scope of Above Analysis
References:
Thank You
