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Designing an lte channel for data transmission

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

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Designing an lte channel for data transmission

  1. 1. DESIGNING AN LTE CHANNEL FOR DATA TRANSMISSION Proposal of final project EE571 Presented by – Mohammed Aljnoobi & Mohammed Siddiqui
  2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 11. Purpose of Watermarking  Copyright Protection  Fingerprinting  Copy Protection  Broadcasting Monitoring  Data Authentication
  12. 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. 13. Embedding and extracting technique of SVD
  14. 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. 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. 16. Watermarking results
  17. 17. Watermarking results Watermarked image Watermarked image after a channel of (ADWGN) & QAM
  18. 18. Extracted watermark Extracted water mark without effect of the channel Extracted water mark with channel effect
  19. 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. 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.

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