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MIMO OFDM IN CELLULAR SYSTEM
131011,131039B.Tech (ICT) Semester-V,IET-Ahmedabad University
Under the guidance of
Dr. Dhaval Patel
October 17, 2015
Devanshi, Rajvi and IET-Ahmedabad University MIMO-OFDM Mobile Multimedia Communication Systems 1/12
Outline
Background
Motivation
System ModelSystem ModelSpecification and AssumptionSpecification and Assumption
Result InterpretationEEOPA and APA algorithm energy efficiency comparisonEEOPA and APA algorithm capacity comparison
Further work
Conclusion
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Background
In MIMO wireless channel there are some model proposed:Energy efficiency model in Posisson Voronol tessellationcellular networkA relay cooperation schemeRelay aided multi cell MIMO cellular systemMultiuser cellular virtual MIMO system with decode andforward type protocol
To overcome from above mention models trade off EEOPAmethod is proposed.To improve spectral efficiency and system capacity withoutincreasing the bandwidth MIMO technology create theindependent parallel channels to transmit the data stream.And OFDM technology will convert the frequency-selectivechannels into flat channel.
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Motivation
To reduce the scarcity of energy resources in industries,current technology is motivated to improve the energyefficiency in mobile multimedia communication system.
Like in, ICT industry over load of energy consumption makeburden for network engineers by high electrical bills.
This algorithm is focused on: The energy efficiencyoptimization under given QoS constraints
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System Model- System Model
Figure : OFDM System Model
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System Model- Specification and Asumption
The MIMO-OFDM mobile multimedia communication system:
yk [i ] = Hk [i ]xk [i ] + n
Where, Hk = Channel Matrix of Mr ×Mt
Assume Discrete-Time Block Fading ChannelsHk = Uk
√4k(Vk)H
Taking, Mr ≥ Mt
yk [i ] = CMr (Received Symbol of kth subcarrier of ith OFDMsymbol)where, (k ∈ [1,N] and i ∈ [1, S ])xk [i ] = CMt (Transmitted symbol of kth subcarrier of ithOFDM symbol)n = CMr (Additive noise vector)Assume E (nnH) = IMr×Mt
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System Model- Specification and Asumption
Tf = frame duration and B= System BandwidthAssume Tf < Tc
MIMO channel can be decomposed using SVD method into Mparallel SISO channel.
Assume that at the transmitter side CSI is know via receiverfeedback channels.
W = HHH= Wishart channel matrix
The marginal probability distribution of a Wishart matrix isused for deriving Sub channel gains.
The system capacity < Shannon capacity
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Result InterpretationComparision of EEOPA and APA algorithm: Energy efficiency versus QoS
Figure : Graph of Energy efficiency versus QoS
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Result InterpretationComparision of EEOPA and APA algorithm: Capacity versus QoS
Figure : Graph of Capacity versus QoS
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Future Work
Key technologies combined with Massive MIMO-OFDMSystem with acute estimation about CSI:
Device to device supportHeterogeneous networksBase centric architecture for millimeter wave
Higher QoS provide on same cost as per provide in wirelinechannel.Massive MIMO System has more energy efficiency withdirective antennas.Proposed the channel model which can achieve automaticgain control and optimize system parameters like modulationand channel estimation filters.Radio frequency equipment cost should be lowerImprovement of 5G in excess of 4G is that it is Non- bulky inspace Coherent angle spread of the propagation.
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Conclusion
An EEOPA algorithm is centered on the Channeldecomposition using SVD method to convert complexmultichannel optimization into a multi target single-channeloptimization.
Get a closed-form solution for MIMO-OFDM mobilemultimedia communication systems.
EEOPA algorithm deliver higher energy efficiency and effectivecapacity compared to traditional APA algorithm
But, we have to compromise either by effective energy or QoS
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Thank you
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