Asynchronous Convolutional-Coded Physical-Layer Network Coding


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

PROJECT TITLE :Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation - 2018ABSTRACT:Stochastic network optimization problems entail finding resource allocation policies that are optimum on
PROJECT TITLE :Asynchronous Stochastic Approximation Based Learning Algorithms for As-You-Go Deployment of Wireless Relay Networks Along a Line - 2018ABSTRACT:We are motivated by the need, in emergency situations, for impromptu
PROJECT TITLE :Sense Amplifier Half-Buffer (SAHB): A Low-Power High-Performance Asynchronous Logic QDI Cell Template - 2017ABSTRACT:We tend to propose a completely unique asynchronous logic (async) quasi-delay-insensitive (QDI)
PROJECT TITLE :Research of Varying Frequency Driving Scheme for Asynchronous Induction Coil Launcher - 2017ABSTRACT:There are few of transient management models are tailored to asynchronous induction coil launcher (AICL) with
PROJECT TITLE : Data Center Server Provision: Distributed Asynchronous Control for Coupled Renewal Systems - 2017 ABSTRACT: This paper considers a price minimization downside for knowledge centers with N servers and randomly

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry