CeRA-eSP: Code-Expanded Random Access to Enhance Success Probability of Massive MTC.

Area of Science:

• Wireless communication networks
• Internet of Things (IoT) technologies

Background:

• Massive machine-type communication (mMTC) services in cellular networks face resource limitations during initial access for numerous devices.
• High collision rates during random access are a significant challenge for mMTC services.
• Existing efficient preamble transmission studies struggle to support a large number of simultaneous devices.

Purpose of the Study:

• To address the challenges of resource scarcity and high collision rates in mMTC initial access.
• To investigate and improve the code-expanded random access (CeRA) scheme.
• To propose an optimal preamble codeword set selection algorithm for CeRA.

Main Methods:

• Investigated code-expanded random access (CeRA) by extending preamble resources into the code domain.
• Developed an optimal preamble codeword set selection algorithm based on mathematical analysis.
• Simulated the proposed CeRA scheme to evaluate its performance.

Main Results:

• The proposed code-expanded random access scheme to enhance success probability (CeRA-eSP) reduces the phantom codeword and PUSCH resource shortage issues.
• CeRA-eSP demonstrates a higher random access success rate compared to existing schemes.
• The enhanced CeRA scheme achieves a lower access delay.

Conclusions:

• The proposed optimal preamble codeword set selection algorithm effectively solves existing CeRA limitations.
• CeRA-eSP offers a viable solution for improving mMTC services in cellular networks.
• The enhanced CeRA scheme significantly improves the efficiency and reliability of massive IoT device access.