We investigated how a 2-D image is sent over an OFDM channel and used LTE standard for better efficiency

1. DESIGNING AN LTE CHANNEL FOR
DATA TRANSMISSION
Proposal of final project EE571
Presented by – Mohammed Aljnoobi & Mohammed
Siddiqui

2. Agenda
 Introduction
 LTE technology overview.
 Sending image over the LTE simulated channel.
 (SVD) watermarking overview.
 What is digital watermarking?
 Features of watermarking
 What is SVD?
 Using channel for an embedded watermarked imaqe.

3. Introduction
 We will investigate 2-D
image processing by
sending an image over
a channel.
 And we will observe
how watermarked
image is effected when
passed through this
channel.

4. LTE
 LTE (Long Term Evolution) has flexible and expandable
spectrum bandwidth
 Simplified network architecture
 Time-frequency scheduling on shared-channel
 Support for multi-antenna scheme
 High data throughput
 Self-Organizing Network

5. Simulation
steps
 Sending the image:
 Choose any image.
 Choosing the type of channel (AWGN or Rayleigh distribution).
 Add modulation technique (QAM).
 Apply OFDM .
 Add Cyclic prefix.
 Receiving the image:
 Removing cyclic prefix.
 Demultiplexer (Filter).
 Demodulator.
 Receive the data.

6. OFDM
• Orthogonal Frequency-
Division
Multiplexing (OFDM) is a
method of encoding digital
data on multiple carrier
frequencies.
• Total bandwidth is divided
into smaller non-
overlapping frequency sub-
bands.
• Used in cable television
and satellite
communications.

7. Cyclic
prefix
• Cyclic prefix refers to the prefixing of a
symbol with a repetition of the end.
• Guard time between adjacent symbols is
inserted to eliminate ISI.
• Inserted to preserve orthogonality.
• Increases required transmission
bandwidth, hence lowers spectral
efficiency.
• Cyclic Prefixes are used in OFDM in order
to combat multipath by making channel
estimation easy.

8. Digital Watermarking
 Allows users to embed SPECIAL PATTERN or SOME DATA into digital
contents without changing its perceptual quality.
 When data is embedded, it is not written at HEADER PART but embedded
directly into digital media itself by changing media contents data.
 Watermarking is a key process for the PROTECTION of copyright ownership
of electronic data.

9. Classification Of WATERMARK
• According to Human Perception
 Invisible
 Visible
• According to types of Document
 Text
 Image
 Audio
 Video
• According to Robustness
 Fragile
 Semi fragile
 Robust

10. Features of Watermarking
 Invisible/Inaudible
 Information is embedded without digital content degradation, because of the level of
embedding operation is too small for human to notice the change.
 Inseparable
 The embedded information can survive after some processing, compression and format
transformation.
 Unchanging data file size
 Data size of the media is not changed before and after embedding operation because
information is embedded directly into the media.

11. Purpose of Watermarking
 Copyright Protection
 Fingerprinting
 Copy Protection
 Broadcasting Monitoring
 Data Authentication

12. SVD(Singular Value Decomposition)
 SVD for any image say A of size m*m is a factorization of the
form given by ,A = UΣV∗ Where U and V are orthogonal matrices
in which columns of U are left singular vectors and columns of V
are right singular vectors of image A.
 Suppose M is a m*n matrix whose entries come from the field K,
which is either the field of real numbers or the field of complex
number. Then there exists a factorization of the form
 where U is an m × m unary matrix over K (orthogonal matrix if K
= R), Σ is a m × n diagonal matrix with non-negative real numbers
on the diagonal, and the n × n unitary matrix V∗ denotes the
conjugate transpose of the n × n unitary matrix V. Such a
factorization is called a singular value decomposition of M

13. Embedding and extracting technique of
SVD

14. How To overcome the problems of SVD
 Measuring of performance of SVD should be easy.
 SVD should become fast from computational point of view .
 To find the technique to calculate the SVD easily.
 Less calculations should be made to measure the performance of SVD
 SVD characteristics which are not utilized in image processing should be utilized by finding the
techniques to utilize the unused SVD characteristics in image processing such as image capacity for
hiding information, roughness measure etc.

15. Result and analysis
Original image
The image after the
channel
• As shown in the image the received image there are some error which should be
corrected by error correction some techniques based on the channel specification.

16. Watermarking results

17. Watermarking results
Watermarked image
Watermarked image after a channel of
(ADWGN) & QAM

18. Extracted watermark
Extracted water mark without effect
of the channel Extracted water mark with channel effect

19. Comments about the Results
 The quality of extracted image has changed slightly from the
original watermark image, but still it has very good which
means that, the used SVD system works rightly.
 It is clear from the last image that the applied communication
has affected our watermarking system, but still we can
recognize the image the a lot of details. Thus, image
enhancement techniques and an error correction algorithm are
needed to improve the result of the watermarking system in this
case.
 And in the case of the image over LTE channel we observed
the image there are some error which should be corrected by

20. Conclusions
 The coding and error correction algorithms are very important
to increase the performance of any communication systems.
 The watermarking system used over communication channel
should should be robust to be able to extract that image.
 The image sent over a channel may contain errors at the
receiver end which can be corrected using error correcting
techniques.