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1
Survey on Ofdm-Mimo wireless broadcasting system
Guided By-Debasis Surya N.Das
Content Introduction
Wireless broadcasting System
OFDM
Literature Survey
Objective
References
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Introduction Increasing growth of data traffic we have to rely on
multiple transmitter and multiple receiver of antenna for better transmission.
Due to limitation of spectrum bandwidth efficiency ,we have to search for a communication design with high data rate(bandwidth-efficiency) and small error rate(power-efficiency)
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Wireless broadcasting System
Wireless communication is the transfer of information between two or more points that are not connected by an electrical conductor.
Wireless systems can be divided into 4 forms:
> SISO
> SIMO
> MISO
> MIMO
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SISO SISO (single input, single output) refers to a wireless
communications system in which one antenna is used at the source(transmitter) and one antenna is used at the destination (receiver).
It uses simple antenna technology.
Interference and fading will have more effect in this system.
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SIMO
SIMO (single input, multiple output) is an antenna technology for wireless communications in which multiple antennas are used at the destination (receiver).
The source (transmitter) has only one antenna.
The antennas are combined to minimize errors and optimize data speed.
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MISO MISO (multiple input, single output) is also termed
transmit diversity.
The advantage of using MISO is that the multiple antennas and the redundancy coding / processing is moved from the receiver to the transmitter.
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MIMO Multiple-Input Multiple-Output (MIMO) technology
is a wireless technology that uses multiple transmitters and receivers to transfer more data at the same time.
MIMO makes antennas work smarter by enabling them to combine data streams arriving from different paths.
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Advantages of MIMO
It offers significant increase in data throughput and link range without additional bandwidth or increased transmit power.
MIMO technology takes advantage of a natural radio-wave phenomenon called multipath.
MIMO makes antennas work smarter.
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Application of MIMO• WLAN – WiFi 802.11n
• Mesh Networks (e.g., Wireless)
• WMAN – WiMAX 802.16e
• 4G
• RFID(Radio Frequency Identification)
• Digital Home
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OFDM Orthogonal frequency-division multiplexing (OFDM) is a
method of digital modulation in which a signal is split into several narrowband channels at different frequencies.
OFDM is similar to conventional frequency-division multiplexing (FDM).
OFDM is a frequency-division multiplexing(FDM) scheme used as a digital multicarrier modulation method.
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Advantage of OFDM
Allows simultaneous high-data-rate transmission from several users.
Pulsed carrier can be avoided.
Resilience to interference
Immunity to selective fading
Spectrum Efficiency
Resilient to ISI
Resilient to narrow band effects
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Application of OFDM
Digital Audio Broadcasting (DAB)
Digital television
Wireless LAN Network
Broadband Wireless Access System
ADSL (Asymmetric digital subscriber line)
The LTE and LTE Advanced 4G mobile phone standards.
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Literature SurveyAREA AUTHOR METHODOLOGY
1)Adaptive filter
i)Gyorgy Oros,LaszloSujbert,Gabor Pecl
ii) Herbert Buncher,JacobBenety,Walter kellerman [2]
i)Multiple Adaptive filtering
ii) FX-LMS
2)Channel Estimation i)Eleftherios Kofidis,DimitriosKatselis , AthanasiosRontogiannis , SergiosTheodoridis [1]
ii)Ashwani Sharmaa, Swades Deb, HariM. Guptab, Ranjan Gangopadhyayd
i)Preamble-based channel estimation methods
ii)Distortion analysis of MDTC–OFDM system
3)Channel equalization i)Gyanesh Das a, Prasant Kumar Pattnaik b, Sasmita Kumari Padhy [3]
ii) Babak HajiBagher Naeenia, Hamidreza Amindavarb, HamidrezaBakhshi
i)Artificial Neural Network by channel equalization
ii) Blind per tone equalizationof multilevel signals
4)Channel ModelingRobert c.danies,robert w.heath jr[4]
i)Inverse marginal cdfapproximation through subcarrier ordering 15
Objective By the above literature survey ,we set our project
objective as
“CHANNEL MODEL FOR OFDM-MIMO WIRELESS BROADCATING SYSTEM”
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References[1] E. Kofidis ,et al., “Channel estimation in OFDM/OQAM systems”, ‘‘ Elsevier /23january,2013”
[2] H.Buncher ,et al., “Adaptive filtering with bandwidth constraint in feedback path”, “ Elsevier /25june,2011”
[3] G. Das ,et al .,“Artificial Neural Network trained by Particle Swarm Optimization for non-linear channel equalization”,/Elsevier /12 july,2013”
[4] Robert c.danies,et al., “modeling order subcarrier SNR in mimo OFDM”,/Elsevier/1ooctober,2011
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THANK YOU
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