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Is NOMA Efficient in Multi-Antenna Networks? A Critical Look at Next Generation Multiple Access Techniques (2101.04802v1)

Published 12 Jan 2021 in cs.IT, eess.SP, and math.IT

Abstract: In this paper, we take a critical and fresh look at the downlink multi-antenna NOMA literature. Instead of contrasting NOMA with OMA, we contrast NOMA with two other baselines. The first is conventional Multi-User Linear Precoding (MULP). The second is Rate-Splitting Multiple Access (RSMA) based on multi-antenna Rate-Splitting (RS) and SIC. We show that there is some confusion about the benefits of NOMA, and we dispel the associated misconceptions. First, we highlight why NOMA is inefficient in multi-antenna settings based on basic multiplexing gain analysis. We stress that the issue lies in how the NOMA literature has been hastily applied to multi-antenna setups, resulting in a misuse of spatial dimensions and therefore loss in multiplexing gains and rate. Second, we show that NOMA incurs a severe multiplexing gain loss despite an increased receiver complexity due to an inefficient use of SIC receivers. Third, we emphasize that much of the merits of NOMA are due to the constant comparison to OMA instead of comparing it to MULP and RS baselines. We then expose the pivotal design constraint that multi-antenna NOMA requires one user to fully decode the messages of the other users. This design constraint is responsible for the multiplexing gain erosion, rate loss, and inefficient use of SIC receivers in multi-antenna settings. Our results confirm that NOMA should not be applied blindly to multi-antenna settings, highlight the scenarios where MULP outperforms NOMA and vice versa, and demonstrate the inefficiency, performance loss and complexity disadvantages of NOMA compared to RS. The first takeaway message is that, while NOMA is not beneficial in most multi-antenna deployments. The second takeaway message is that other non-orthogonal transmission frameworks, such as RS, exist which fully exploit the multiplexing gain and the benefits of SIC to boost the rate in multi-antenna settings.

Citations (147)

Summary

  • The paper argues NOMA is inefficient in multi-antenna settings because its required SIC processing fails to leverage the full spatial multiplexing gains available.
  • Analysis shows NOMA suffers significant multiplexing gain loss in multi-antenna settings compared to MU-LP and RSMA.
  • NOMA's SIC approach increases receiver complexity with limited multiplexing gain benefits, whereas RSMA offers better performance under imperfect channel conditions.

Efficiency of NOMA in Multi-Antenna Networks: A Critical Evaluation

Recent advances in non-orthogonal multiple access (NOMA) have received significant attention for their potential in satisfying the high throughput, reliability, and quality of service (QoS) requirements necessary for future wireless networks. However, the paper "Is NOMA Efficient in Multi-Antenna Networks? A Critical Look at Next Generation Multiple Access Techniques" challenges the perceived superiority of NOMA, particularly in multi-antenna settings, and instead advocates for a reconsideration of how non-orthogonal access should be adapted to these environments.

The paper emphasizes that the majority of the literature contrasts NOMA primarily with orthogonal multiple access (OMA). However, this study provides a more critical perspective by comparing NOMA with multi-user linear precoding (MU--LP) and rate-splitting multiple access (RSMA). The authors dispel several misconceptions and highlight fundamental issues in adapting NOMA from single-antenna to multi-antenna configurations.

Key Insights

  1. Inefficiency in Multi-Antenna Settings: The paper effectively argues that NOMA's application, originally intended for single-antenna systems, is inefficient for multi-antenna settings. The crux of the inefficiency lies in the stringent requirement for one user to fully decode the messages of other users, which neglects the inherent spatial multiplexing advantages of multi-antenna systems.
  2. Multiplexing Gain Loss: Through a multiplexing gain analysis, the authors illustrate that NOMA incurs a significant loss in multiplexing gain in multi-antenna scenarios compared to MU--LP and RSMA. The analysis reveals that the sum multiplexing gain for NOMA is often less than that attainable by MU--LP and RSMA, particularly in scenarios with multiple antennas (M) greater than the number of user groups (G).
  3. Inefficient Use of SIC Receivers: The paper highlights a paradox in NOMA's design philosophy. While NOMA uses successive interference cancellation (SIC) receivers to manage multi-user interference, the approach results in higher receiver complexity with reduced benefits in terms of multiplexing gain. The deployment of SIC should translate into performance incentives, yet in NOMA, it instead results in constraints that limit these advantages.
  4. Robustness to CSIT Imperfections: The paper also points out that NOMA's multiplexing gains are relatively insensitive to the quality of channel state information at the transmitter (CSIT), which, under imperfect conditions, fails to flexibly capitalize on available spatial dimensions. In contrast, RSMA demonstrates a notable robustness by accommodating partial interference cancellation, which enhances its performance integrity against CSIT inaccuracies.
  5. Comparative Baselines: The paper asserts that NOMA's perceived merits are often magnified due to inappropriate baselining against OMA, instead of critically comparing it with MU--LP and RSMA, which offer more realistic insights into its performance limitations.

Implications for Future Research and Development

In outlining the inefficiencies of NOMA in multi-antenna settings, the paper makes a critical case for the reassessment of non-orthogonal transmission design strategies. Whereas NOMA might not fully exploit the spatial dimensions and the benefits of SIC, RSMA emerges as a superior candidate for future wireless standards, highlighting the importance of rate-splitting to optimize performance without substantially raising receiver complexity.

The authors suggest that RSMA’s ability to simultaneously treat interference (partially decode it and treat the remainder as noise) provides a more adept response to the demands of modern networks, leveraging the benefits of both SDMA and NOMA. This proposition invites a renewed focus on RSMA's development, adherence to optimal strategies in multi-antenna environments, and the potential elevation of RSMA as a key technology in 5G and beyond.

The paper provides a foundational argument for future researchers to consider not only the rate and capacity benefits of such strategies but also the practical aspects of deployability, such as algorithm complexity, requirement stringentness, and user-device compatibility.

In conclusion, this examination compels the wireless research community to pause and reconsider the hastened adoption of NOMA in multi-antenna settings, recognizing the critical need for optimized transmission strategies that genuinely leverage multi-antenna potential and offer practical, scalable solutions for next-generation wireless communications.

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