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Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access.

Wenjiao Xie1, Runhe Tian2, Huisheng Zhang1

  • 1School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China.

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|July 29, 2023
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Summary
This summary is machine-generated.

New algorithms improve unsourced massive random access (URA) by enhancing coded compressed sensing with patterned Reed-Muller (PRM) codes. These methods boost performance in both single-user and multi-user scenarios, supporting more active users and reducing energy consumption.

Keywords:
complex Reed-Muller codeserror correction codemachine-to-machine communicationsunsourced massive random access

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Area of Science:

  • Wireless communication
  • Information theory
  • Coding theory

Background:

  • Unsourced massive random access (URA) faces challenges with decoding performance due to geometric-based algorithms and message interference.
  • Existing protocols often struggle in multi-user scenarios, limiting the number of supported devices and increasing energy costs.

Purpose of the Study:

  • To propose novel algorithms for coded compressed sensing in URA systems.
  • To enhance the performance of patterned Reed-Muller (PRM) inner codebooks concatenated with outer error-correction codes.
  • To improve decoding accuracy and system efficiency in both single-user and multi-user environments.

Main Methods:

  • Introduction of a list PRM projection algorithm for single-user scenarios to mitigate error propagation.
  • Development of an iterative list PRM projection algorithm for multi-user scenarios, jointly detecting PRM code vectors and channel coefficients.
  • Mathematical analysis and verification of algorithm performance through theoretical and numerical simulations.

Main Results:

  • The proposed list PRM projection detection effectively handles single-user scenarios by maintaining multiple candidates.
  • The iterative list PRM projection algorithm demonstrates significant improvements in convergence rate for signal recovery in multi-user settings.
  • Concatenation with outer error-correction codes and iterative list detection shows superior performance compared to benchmarks.

Conclusions:

  • The packetized URA protocol with iterative list projection detection significantly enhances the number of supported active users per slot.
  • The proposed methods achieve a lower energy cost per bit for a given error probability.
  • The developed algorithms offer a more efficient and robust solution for massive random access systems.