This document discusses OFDM-MIMO wireless broadcasting systems. It first introduces the need for high data rate and bandwidth efficient wireless communication systems using multiple transmitters and receivers. It then describes different wireless systems including SISO, SIMO, MISO and MIMO. OFDM and its advantages for multicarrier transmission are also discussed. Finally, the document reviews literature on adaptive filtering, channel estimation, equalization and modeling for OFDM-MIMO systems and sets the objective to develop a channel model for such wireless broadcasting systems.

1. 1
Survey on Ofdm-Mimo wireless broadcasting
system
Guided By-
Debasis Surya N.Das

2. Content
 Introduction
 Wireless broadcasting System
OFDM
 Literature Survey
 Objective
References
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3. 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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4. 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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5. 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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6. 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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7. 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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8. 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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9. 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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10. 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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11. 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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12. 12

13. 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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14. 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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15. Literature Survey
AREA AUTHOR METHODOLOGY
1)Adaptive filter
i)Gyorgy Oros,Laszlo
Sujbert,Gabor Pecl
ii) Herbert Buncher,Jacob
Benety,Walter kellerman [2]
i)Multiple Adaptive filtering
ii) FX-LMS
2)Channel Estimation i)Eleftherios Kofidis
,DimitriosKatselis ,
AthanasiosRontogiannis , Sergios
Theodoridis [1]
ii)Ashwani Sharmaa, Swades Deb, Hari
M. 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, Hamidreza
Bakhshi
i)Artificial Neural Network
by channel equalization
ii) Blind per tone equalization
of multilevel signals
4)Channel Modeling
Robert c.danies,robert w.heath jr[4]
i)Inverse marginal cdf
approximation through
subcarrier ordering 15

16. Objective
 By the above literature survey ,we set our project
objective as
“CHANNEL MODEL FOR OFDM-MIMO WIRELESS
BROADCATING SYSTEM”
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17. 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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18. THANK YOU
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