Random Beamforming in Millimeter-Wave NOMA Networks (1607.06302v3)

Abstract: This paper investigates the coexistence between two key enabling technologies for the fifth generation (5G) mobile networks, non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) communications. Particularly, the application of random beamforming to the addressed mmWave-NOMA scenario is considered in this paper, in order to avoid the requirement that the base station knows all the users' channel state information. Stochastic geometry is used to characterize the performance of the proposed mmWave-NOMA transmission scheme, by using the key features of mmWave systems, e.g., mmWave transmission is highly directional and potential blockages will thin the user distribution. Two random beamforming approaches which can further reduce the system overhead are also proposed to the addressed mmWave-NOMA communication scenario, where their performance is studied by developing analytical results about sum rates and outage probabilities. Simulation results are also provided to demonstrate the performance of the proposed mmWave-NOMA transmission schemes and verify the accuracy of the developed analytical results.

• The paper introduces a novel random beamforming method that significantly reduces CSI feedback overhead in mmWave-NOMA systems.
• It employs stochastic geometry to evaluate sum rates and outage probabilities, demonstrating performance gains over traditional approaches.
• The study proposes low-feedback protocols, including one-bit and distance-based schemes, to enhance network scalability and manage interference.

Overview of Random Beamforming in Millimeter-Wave NOMA Networks

This paper presents an analytical investigation into the integration of random beamforming techniques within millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) networks, designed for fifth-generation (5G) mobile networks. The research aims to alleviate the overhead associated with the acquisition of full channel state information (CSI) by the base station, a pivotal requirement in traditional beamforming schemes.

Key Contributions

This paper makes several notable contributions:

1. Random Beamforming Scheme: The paper proposes a novel application of random beamforming to mmWave-NOMA networks, whereby the base station foregoes complete channel vector knowledge in favor of utilizing highly directional beamforming intrinsic to mmWave communication. This method significantly reduces network overhead by limiting the number of users required to share feedback about channel quality.
2. Stochastic Geometry for Performance Characterization: The authors employ stochastic geometry to model user distribution and performance metrics such as sum rates and outage probabilities, factoring in the unique characteristics of mmWave signals, including directional propagation and attenuation due to blockages.
3. Low-Feedback Scenarios: The paper introduces constrained-feedback protocols, including a scheme utilizing only user distance information and another requiring a single bit of feedback per user. These approaches minimize feedback requirements, investigating the impact on performance in scenarios with rapidly varying channel conditions.
4. Multiple-Beam Considerations: In evaluating scenarios with multiple orthonormal beams, the paper analyzes intra- and inter-beam interference and provides expressions for outage probabilities, offering insight into diversified performance impacts with random beamforming.

Numerical Results and Performance Evaluation

The paper provides comprehensive numerical results to validate the proposed methods and theoretical findings:

• Sum Rate and Outage Probability: The simulation results demonstrate significant performance gains of mmWave-NOMA over traditional mmWave-OMA in terms of both sum rates and outage probabilities, particularly for users with stronger channels.
• Partial CSI Efficiency: Interestingly, the constrained-feedback schemes sometimes outperform the perfect CSI scenario due to favorable user scheduling, underscoring the potential of random beamforming in practical applications with incomplete CSI.
• Feedback Thresholds Impact: The research identifies the sensitivity of system performance to feedback thresholds, especially affecting the diversity gain of strong users in one-bit schemes.

Implications and Future Directions

The paper's findings have profound implications for the design of mmWave-NOMA systems in 5G and beyond:

• Practical System Design: By significantly reducing feedback requirements, proposed schemes offer practical solutions for large-scale, dense networks.
• Interference Management: The analysis provides insights into beam management strategies essential for mitigating inter-beam interference, paving the way for more effective multi-user access strategies in NOMA.
• Scalability and Flexibility: The methods promote scalability and adaptability in dynamic wireless environments, benefiting applications with high mobility and varying network loads.

Future research could explore the integration of machine learning to optimize beam selection and user pairing, potentially enhancing the adaptability and efficiency of mmWave-NOMA networks beyond static environmental assumptions. Additionally, practical deployment aspects, such as hardware constraints and real-time processing capabilities, would be essential to address for realizing these theoretical advancements in real-world networks.