Sell Your Projects | My Account | Careers | This email address is being protected from spambots. You need JavaScript enabled to view it. | Call: +91 9573777164

Asynchronous Convolutional-Coded Physical-Layer Network Coding

1 1 1 1 1 Rating 4.78 (46 Votes)

PROJECT TITLE :

Asynchronous Convolutional-Coded Physical-Layer Network Coding

ABSTRACT:

This paper investigates the decoding method of asynchronous convolutional-coded physical-layer network coding (PNC) systems. Specifically, we put forth a layered decoding framework for convolutional-coded PNC consisting of 3 layers: symbol realignment layer, codeword realignment layer, and joint channel-decoding network coding (Jt-CNC) decoding layer. Our framework can house section asynchrony (phase offset) and symbol arrival-time asynchrony (image misalignment) between the signals simultaneously transmitted by multiple sources. A salient feature of this framework is that it will handle each fractional and integral image misalignments. For the decoding layer, instead of Jt-CNC, previously proposed PNC decoding algorithms (e.g., XOR-CD and reduced-state Viterbi algorithms) will also be used with our framework to deal with general symbol misalignments. Our Jt-CNC algorithm, based mostly on belief propagation, is BER-optimal for synchronous PNC and close to optimal for asynchronous PNC. Extending beyond convolutional codes, we have a tendency to further generalize the Jt-CNC decoding algorithm for all cyclic codes. Our simulation shows that Jt-CNC outperforms the previously proposed XOR-CD algorithm and reduced-state Viterbi algorithm by a pair of dB for synchronous PNC. For each section-asynchronous and symbol-asynchronous PNC, Jt-CNC performs better than the other two algorithms. Importantly, for real wireless network experimentation, we tend to implemented our decoding algorithm during a PNC prototype built on the USRP software radio platform. Our experiment shows that the proposed Jt-CNC decoder works well in observe.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


Asynchronous Convolutional-Coded Physical-Layer Network Coding - 4.8 out of 5 based on 46 votes

Project EnquiryLatest Ready Available Academic Live Projects in affordable prices

Included complete project review wise documentation with project explanation videos and Much More...