A Novel Expectation-Maximization-Based Blind Receiver for Low-Complexity Uplink STLC-NOMA Systems

Area of Science:

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

Background:

• Non-orthogonal multiple access (NOMA) is crucial for enhancing spectral efficiency in wireless networks.
• Existing space-time line coded NOMA (STLC-NOMA) systems face challenges with high receiver complexity.
• Internet-of-things (IoT) networks require efficient and low-complexity communication solutions.

Purpose of the Study:

• To propose a novel, low-complexity STLC-NOMA system for uplink IoT networks.
• To reduce the computational complexity at the access point (AP) for decoding signals.
• To analyze the bit-error-rate (BER) performance and develop an efficient blind energy estimation (BEE) algorithm.

Main Methods:

• Utilizing amplitude-shift keying (ASK) modulators with symbols aligned to in-phase and quadrature axes.
• Employing space-time line coding (STLC) to compensate for phase distortion.
• Implementing a single-user maximum-likelihood (ML) detector at the AP.
• Developing an expectation-maximization (EM)-based blind energy estimation (BEE) algorithm for power and channel gain estimation.

Main Results:

• The proposed system achieves lower computational complexity compared to conventional STLC-NOMA.
• Mathematical analysis confirms the exact BER performance of the novel system.
• The EM-based BEE algorithm effectively estimates transmit power and channel gain, even in short-packet scenarios.
• The proposed architecture demonstrates superior BER performance, particularly with high-order modulation.

Conclusions:

• The novel uplink STLC-NOMA system offers a significant reduction in receiver complexity.
• The system provides improved BER performance over conventional STLC-NOMA.
• The developed BEE algorithm enhances system efficiency by eliminating the need for pilot signals.