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Information Coding

Information Coding. By Vikram Karri . Overview. Introduction Collaboration Diagram Superposition Coding Principle Design and Implementation Platform For SC System Transmitter Operation Receiver Operation Conclusion Reference. Introduction.

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Information Coding

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  1. Information Coding By Vikram Karri

  2. Overview • Introduction • Collaboration Diagram • Superposition Coding • Principle • Design and Implementation • Platform For SC System • Transmitter Operation • Receiver Operation • Conclusion • Reference

  3. Introduction • Information coding is a rule for converting a piece of information into another form or representation not necessarily of the same type. • In communications and information processing, encoding is the process by which information from a source is converted into symbols to be communicated. • Decoding is the reverse process, converting these code symbols back into information understandable by a receiver.

  4. All C++ blocks that can be used in GR graphs are listed here or in the subcategories below. • Collaboration diagram for GNU Radio C++ Signal Processing Blocks:

  5. Collaboration Diagram • Collaboration diagram for Information Coding and Decoding: • Information Coding is to convert the message into some signals & Information Decoding is to convert it into the original form.

  6. Superposition Coding • Superposition coding is a well-known capacity achieving coding scheme for stochastically degraded broadcast channels. • A software-radio based design of a superposition coding system on the GNU Radio platform with the Universal Software Radio Peripheral acting as the transceiver frontend. • The packet error performance and discuss some issues that arise in this implementation.

  7. Principle • A single transmitter to communicate with multiple receivers is Superposition Coding (SC), which is known to be the optimal communication strategy for stochastically degraded1 broadcast channels. • SC works by exploiting the relative disparities in channel quality to different receivers to optimally allocate transmit power among them, while using the entire bandwidth for each receiver. • Receivers decode the messages meant for all those receivers whose channel quality is poorer than theirs, before decoding their own message.

  8. The SC system design and implementation has the following benefits. • The SD procedure is also beneficial in other scenarios. For example, it is the optimal decoding scheme for the multiple-access channel and has been shown to improve link throughput in ad hoc scenarios. • SC sets the foundation to experiment with more sophisticated medium access schemes that are point-to multipoint, or even multipoint-to-multipoint. Design and Implementation

  9. Platform For SC System • All the signal processing algorithms at the baseband are implemented digitally using GNU Radio on a general-purpose computer. • This approach use several built-in libraries that come with the GNU Radio package, including the USRP interface. • OFDM offers a high degree of bandwidth scalability and implementation flexibility, especially given its relative ease of time- and frequency-synchronization, channel estimation and equalizer design

  10. The figure shows that our SC system gives very good performance (Packet Error Rate achieves 10−2). Clearly, the far user has a lower PER than the near user (for the same SNR).

  11. Transmitter Operation • The payloads are provided to the physical layer by the link layer. Each user’s payload is assigned a modulation type, code rate, and the fraction of the transmit power. • In time domain, the signals are weighted by the fraction of power allocation factors (√ 1 − αfor the near user signal, and √α for the far user signal), added and transmitted.

  12. Receiver Operation • The receiver front end is implemented in hardware using the USRP, while the physical layer is implemented using a single GNU Radio signal processing block. • The USRP downconverts and digitizes signals in the frequency band of operation.

  13. Conclusion • I have presented a design that leverages the flexibility of the GNU Radio/USRP platform to implement physical layer of a communication system that uses superposition coding. • The performance of the implementation was measured using packet error rates for each of the streams. • I found that the limitations of the USRP hardware have implications for the design of training sequences, and the software environment imposes constraints on the degree of modularity allowed in the system implementation.

  14. Reference • Ganti, R.K.; Gong, Z.; Haenggi, M.; Lee, C.; Srinivasa, S.; Tisza, D.; Vanka, S.; Vizi, P.; , "Implementation and Experimental Results of Superposition Coding on Software Radio," Communications (ICC), 2010 IEEE International Conference on , vol., no., pp.1-5, 23-27 May 2010doi: 10.1109/ICC.2010.5502330URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5502330&isnumber=5501741 • http://gnuradio.org/doc/doxygen/group__coding__blk.html • Seeger, A.; , "Information theoretic based design of hierarchical channel coding and modulation on mobile radio channels," Wireless Image/Video Communications, 1996., First International Workshop on , vol., no., pp.85-90, 4-5 Sep 1996doi: 10.1109/WIVC.1996.624658URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=624658&isnumber=13577

  15. Thank You

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