[Paper Review] Performance Analysis of 6G Multiuser Massive MIMO-OFDM THz Wireless Systems with Hybrid Beamforming under Intercarrier Interference
This paper proposes a two-stage hybrid beamforming design for multiuser massive MIMO-OFDM terahertz (THz) systems, incorporating intercarrier interference (ICI) mitigation via Riemannian manifold optimization for analog beamforming and zero-forcing (ZF) digital beamforming. The key contribution is demonstrating that accounting for ICI significantly improves spectral efficiency, especially at high SNR and with increased RF chains and antennas, while reducing system complexity and latency.
6G networks are expected to provide more diverse capabilities than their predecessors and are likely to support applications beyond current mobile applications, such as virtual and augmented reality (VR/AR), AI, and the Internet of Things (IoT). In contrast to typical multiple-input multiple-output (MIMO) systems, THz MIMO precoding cannot be conducted totally at baseband using digital precoders due to the restricted number of signal mixers and analog-to-digital converters that can be supported due to their cost and power consumption. In this thesis, we analyzed the performance of multiuser massive MIMO-OFDM THz wireless systems with hybrid beamforming. Carrier frequency offset (CFO) is one of the most well-known disturbances for OFDM. For practicality, we accounted for CFO, which results in Intercarrier Interference. Incorporating the combined impact of molecular absorption, high sparsity, and multi-path fading, we analyzed a three-dimensional wideband THz channel and the carrier frequency offset in multi-carrier systems. With this model, we first presented a two-stage wideband hybrid beamforming technique comprising Riemannian manifolds optimization for analog beamforming and then a zero-forcing (ZF) approach for digital beamforming. We adjusted the objective function to reduce complexity, and instead of maximizing the bit rate, we determined parameters by minimizing interference. Numerical results demonstrate the significance of considering ICI for practical implementation for the THz system. We demonstrated how our change in problem formulation minimizes latency without compromising results. We also evaluated spectral efficiency by varying the number of RF chains and antennas. The spectral efficiency grows as the number of RF chains and antennas increases, but the spectral efficiency of antennas declines when the number of users increases.
Motivation & Objective
- To address the challenge of intercarrier interference (ICI) in multiuser massive MIMO-OFDM THz systems, which degrades spectral efficiency and system performance.
- To design a low-complexity, low-latency hybrid beamforming architecture suitable for practical 6G deployment, combining analog and digital precoding.
- To evaluate the impact of ICI, carrier frequency offset (CFO), and system parameters such as RF chains, antennas, and user count on spectral efficiency.
- To optimize beamforming by minimizing interference instead of maximizing rate, reducing computational complexity while maintaining high performance.
- To validate the model using realistic 3D wideband THz channel characteristics, including molecular absorption, multipath fading, and high path loss.
Proposed method
- Developed a three-dimensional wideband THz channel model incorporating frequency-selective fading, molecular absorption, and high sparsity.
- Proposed a two-stage hybrid beamforming framework: Riemannian manifold optimization for analog beamforming and zero-forcing (ZF) digital beamforming.
- Formulated the beamforming problem to minimize interference rather than maximize spectral rate, reducing computational complexity.
- Incorporated carrier frequency offset (CFO) effects to model intercarrier interference (ICI), critical for OFDM systems in high-mobility or frequency-uncertain environments.
- Used a fully-connected hybrid beamforming architecture to enable full spatial multiplexing gain with reduced hardware cost.
- Evaluated spectral efficiency using the Shannon capacity formula under realistic system parameters, including SNR, distance, and number of RF chains and antennas.
Experimental results
Research questions
- RQ1How does intercarrier interference (ICI) impact spectral efficiency in massive MIMO-OFDM THz systems with hybrid beamforming?
- RQ2What is the performance gain of incorporating ICI modeling in the beamforming design compared to ignoring it?
- RQ3How do the number of RF chains and antennas affect spectral efficiency and system latency in hybrid beamforming THz systems?
- RQ4Can a reformulated beamforming objective that minimizes interference instead of maximizing rate reduce complexity without significant performance loss?
- RQ5How does transmission distance affect spectral efficiency in indoor THz MIMO-OFDM systems with hybrid beamforming and ICI?
Key findings
- Considering ICI in the beamforming design leads to a significant improvement in spectral efficiency, especially at high signal-to-noise ratio (SNR), demonstrating its critical role in practical THz system design.
- Spectral efficiency increases with the number of RF chains and transmit antennas, but declines as the number of users increases due to higher interference and resource sharing.
- The proposed method reduces system latency by reformulating the beamforming objective to minimize interference instead of maximizing rate, achieving a negligible performance drop with lower complexity.
- Spectral efficiency drops dramatically beyond 5 meters of transmission distance, indicating strong path loss and limited range for high-data-rate THz communications.
- Numerical results show that ignoring ICI leads to suboptimal beamforming performance, with a noticeable degradation in spectral efficiency, particularly at high SNR and with dense user deployment.
- The system achieves high spectral efficiency under high SNR conditions when ICI is properly modeled and mitigated, confirming the effectiveness of the proposed two-stage hybrid beamforming approach.
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This review was created by AI and reviewed by human editors.