Beamforming-Aided NOMA-OFDM Systems with Successive Interference Cancellation for Enhanced Connectivity

Abstract

Orthogonal Frequency Division Multiplexing (OFDM) is widely used in wireless communication because of its ability to handle multipath propagation. However, conventional OFDM uses orthogonal resource allocation, which can limit spectral efficiency when multiple users need to share the available resources. This work investigates a beamforming-aided Non-Orthogonal Multiple Access (NOMA)-OFDM system that integrates power-domain NOMA, superposition coding, convolutional coding, Least Mean Square (LMS) adaptive equalization, and Successive Interference Cancellation (SIC). The proposed system allows two users to share the same time-frequency resources through power allocation, assigning a power coefficient of 0.8 to the far user and 0.2 to the near user. The system performance is evaluated under Additive White Gaussian Noise (AWGN), Rayleigh fading, and Rician fading channel conditions. Bit Error Rate (BER), spectral efficiency, sum rate, fairness index, and outage probability are used as performance metrics, with conventional OFDM serving as the reference system. The simulation results reported in the thesis indicate that the proposed NOMA-OFDM system achieves lower BER and outage probability, along with improvements in spectral efficiency, sum rate, and fairness index compared with conventional OFDM. The study demonstrates the potential of integrating NOMA, adaptive signal processing, and SIC to improve the reliability and resource utilization of wireless communication systems.

Introduction

The increasing demand for high-speed, reliable wireless communication has encouraged the development of techniques that improve spectral efficiency and reduce transmission errors. Orthogonal Frequency Division Multiplexing (OFDM) effectively handles multipath fading, while Non-Orthogonal Multiple Access (NOMA) allows multiple users to share the same time-frequency resources through power-domain allocation. This study investigates a beamforming-aided NOMA-OFDM communication system designed to improve transmission reliability, spectral efficiency, data rate, and fairness under different wireless channel conditions.

The proposed system integrates NOMA power allocation, OFDM modulation, convolutional channel coding, QPSK modulation, Least Mean Square (LMS) adaptive equalization, Successive Interference Cancellation (SIC), and Viterbi decoding. Two users share the communication resources, with 80% of the transmit power allocated to the far user and 20% to the near user. A rate-1/2 convolutional code with constraint length 7 provides error correction, while the LMS algorithm, using a step size of 0.01, helps compensate for channel effects. SIC separates the superimposed user signals at the receiver.

The system is evaluated through MATLAB simulations using three wireless channel models: Additive White Gaussian Noise (AWGN), Rayleigh fading, and Rician fading. The OFDM configuration uses 64 subcarriers and a cyclic prefix of 16 samples. The simulations examine different signal-to-noise ratio (SNR) ranges to assess communication performance under varying conditions.

The study uses five key performance metrics:

• Bit Error Rate (BER): Measures the reliability of data transmission.

• Spectral efficiency: Evaluates how efficiently the available bandwidth is utilized.

• Sum rate: Measures the combined data rate achieved by the users.

• Jain’s fairness index: Evaluates the fairness of resource allocation between users.

• Outage probability: Measures the likelihood that communication performance falls below a required threshold.

The literature review identifies a research gap in combining OFDM, NOMA, convolutional coding, adaptive equalization, and interference cancellation within an integrated communication framework. Previous studies have examined these techniques individually or in different combinations, whereas the proposed work evaluates their combined performance under multiple channel conditions.

The results and discussion focus on comparing coded and uncoded OFDM, conventional OFDM, SISO-LMS, and the proposed NOMA-SISO configuration. The thesis reports improvements in error performance, spectrum utilization, data rate, fairness, and communication reliability. However, the magnitude of these improvements must be established from the actual simulation results for each channel and configuration.

Conclusion

This dissertation presented a beamforming-aided NOMA-OFDM communication system that integrates power-domain NOMA, OFDM, convolutional coding, LMS equalization, and Successive Interference Cancellation (SIC) to improve wireless communication performance. The proposed system was developed and evaluated under AWGN, Rayleigh, and Rician channel conditions. By allowing two users to share the same time-frequency resources through appropriate power allocation, the proposed framework improves spectrum utilization while maintaining reliable data transmission. The performance of the proposed system was evaluated using Bit Error Rate (BER), spectral efficiency, sum rate, fairness index, and outage probability. The results indicate that the proposed NOMA-OFDM system provides lower BER, higher spectral efficiency, improved sum rate, better fairness, and lower outage probability compared with the conventional OFDM system. Among the evaluated channel models, the AWGN channel achieved the best overall performance, followed by the Rician channel, while the Rayleigh channel showed comparatively higher BER due to severe multipath fading. These results demonstrate that the proposed framework effectively enhances communication reliability and bandwidth utilization, making it a suitable approach for next-generation wireless communication systems.

References

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Copyright

Copyright © 2026 Suram Akshaya, Dr. M Madhavi Latha. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.