Uplink Non-Orthogonal Multiple Access with Channel Estimation Errors for Internet of Things Applications.

Area of Science:

• Wireless Communication Systems
• Signal Processing
• Internet of Things (IoT)

Background:

• Next-generation wireless systems require efficient support for a large number of Internet of Things (IoT) connections.
• Uplink non-orthogonal multiple access (NOMA) schemes enable superimposed pilot and data symbols on shared resources.
• Channel estimation errors severely degrade performance in uplink NOMA, especially with many superimposed packets.

Purpose of the Study:

• To address the performance degradation caused by channel estimation errors in uplink NOMA systems.
• To propose a novel uplink NOMA scheme that mitigates the impact of channel estimation inaccuracies.
• To analyze the performance of uplink NOMA with quadrature phase shift keying (QPSK) modulation under channel estimation errors.

Main Methods:

• Investigated uplink NOMA schemes with channel estimation errors using quadrature phase shift keying (QPSK) modulation.
• Analyzed scenarios with superimposed pilot signals and concurrent random access from numerous devices.
• Developed and evaluated a proposed uplink NOMA scheme designed to alleviate performance degradation.

Main Results:

• Channel estimation can be inaccurate in high signal-to-noise ratio (SNR) environments when many devices access a single base station resource concurrently.
• Performance degradation due to channel estimation errors is a significant challenge in uplink NOMA systems.
• The proposed uplink NOMA scheme demonstrates an ability to alleviate performance degradation.

Conclusions:

• Accurate channel estimation is critical for uplink NOMA performance, even in high SNR.
• The proposed uplink NOMA scheme offers a viable solution to mitigate performance issues arising from channel estimation errors.
• This research contributes to the development of robust communication systems for dense IoT deployments.