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NOMA for Integrating Sensing and Communications towards 6G: A Multiple Access Perspective

Xidong Mu, Zhaolin Wang, Yuanwei Liu

arXiv:2206.00377v1cs.ITeess.SP

TL;DR

The paper addresses how ISAC can accommodate sensing and communications while controlling interference under shared radio resources. It develops NOMA-based downlink and uplink designs, including flexible semi-NOMA resource allocation, and reports numerical confirmation of their effectiveness.

  • Problem

    ISAC must coordinate sensing and communication under shared hardware and radio resources, where inter-functionality interference complicates non-orthogonal integration.

  • Method

    The paper develops NOMA-empowered and NOMA-inspired downlink designs plus pure-NOMA-based and semi-NOMA-based uplink designs for interference management and resource allocation.

  • Results

    Numerical results confirmed the effectiveness of the proposed NOMA-ISAC designs.

  • Takeaways & Limitations

    Pure-NOMA uplink ISAC suits sensing-prior operation, while semi-NOMA uplink ISAC supports different ISAC objectives through flexible resource allocation.

Abstract

from arXiv · show

This article focuses on the development of integrated sensing and communications (ISAC) from a multiple access (MA) perspective, where the idea of non-orthogonal multiple access (NOMA) is exploited for harmoniously accommodating the sensing and communication functionalities. We first reveal that the developing trend of ISAC is from \emph{orthogonality} to \emph{non-orthogonality}, and introduce the fundamental models of the downlink and uplink ISAC while identifying the design challenges from the MA perspective. (1) For the downlink ISAC, we propose two novel designs, namely \emph{NOMA-empowered} downlink ISAC and \emph{NOMA-inspired} downlink ISAC to effectively coordinate the inter-user interference and the sensing-to-communication interference, respectively. (2) For the uplink ISAC, we first propose a \emph{pure-NOMA-based} uplink ISAC design, where a fixed communication-to-sensing successive interference cancellation order is employed for distinguishing the mixed sensing-communication signal received over the fully shared radio resources. Then, we propose a general \emph{semi-NOMA-based} uplink ISAC design, which includes the conventional orthogonal multiple access-based and pure-NOMA-based uplink ISAC as special cases, thus being capable of providing flexible resource allocation strategies between sensing and communication. Along each proposed NOMA-ISAC design, numerical results are provided for showing the superiority over conventional ISAC designs.

I. INTRODUCTION

ISAC is motivated by growing sensing demands in 6G and can integrate sensing and communications on shared wireless infrastructure. From a multiple-access perspective, the article examines NOMA to manage interference and resource sharing in ISAC.

  • I. INTRODUCTION: ISAC supports sensing-intensive 6G applications by integrating sensing and communications over shared wireless infrastructure.The article cites smart cities, industrial IoT, and smart homes as example applications.
  • I. INTRODUCTION: Designing ISAC requires balancing sensing and communication because shared hardware and radio resources can create severe inter-functionality interference.Efficient interference mitigation and resource management are therefore central design requirements.
  • I. INTRODUCTION: NOMA uses superposition coding and successive interference cancellation to serve multiple communication users on the same radio resources, improving connectivity and resource efficiency.The article investigates whether these multiple-access mechanisms can help coordinate ISAC interference.
  • I. INTRODUCTION: The article introduces ISAC models and challenges from the multiple-access perspective, then proposes NOMA-based downlink and uplink designs evaluated numerically.The proposed designs address interference coordination and flexible resource allocation between sensing and communication.

II. ISAC: TRENDS, MODELS, AND CHALLENGES

ISAC is developing from orthogonal resource separation toward non-orthogonal integration of sensing and communications. This transition increases the need for effective inter-functionality interference mitigation.

  • A. From Orthogonal-ISAC to Non-Orthogonal-ISAC: ISAC seeks harmonious sensing and communication through a shared hardware platform and radio-wave-based operation.Its intended mutualism includes communication-assisted sensing and sensing-assisted communication.
  • A. From Orthogonal-ISAC to Non-Orthogonal-ISAC: Orthogonal-ISAC separates sensing and communication across time, frequency, space, or code resources to coordinate their mutual interference.This approach represents the earlier resource-orthogonality direction in ISAC development.
  • A. From Orthogonal-ISAC to Non-Orthogonal-ISAC: Non-orthogonal ISAC shares radio resources between sensing and communication, but requires efficient methods to mitigate the resulting inter-functionality interference.The article uses ISAC to refer to non-orthogonal ISAC in its remaining context.

B. Downlink ISAC

In downlink ISAC, the base station jointly transmits sensing and communication waveforms while receiving the sensing echo and serving a communication user. The main challenge is mitigating sensing-to-communication interference from additional sensing waveforms.

  • B. Downlink ISAC: The ISAC base station transmits a probing signal toward a target and a communication signal toward the user, then estimates sensing parameters from the returned echo.The downlink model contains one base station, one sensing target, and one communication user.
  • B. Downlink ISAC: The downlink design problem is therefore to construct joint sensing-and-communication waveforms that support both functionalities while controlling the asymmetric interference.The paper discusses NOMA-based approaches for addressing this challenge.
  • B. Downlink ISAC: Downlink ISAC generally has no communication-to-sensing interference because the base station knows the communication information and sensing analysis does not depend on its modulated bits.The sensing side analyzes the echo rather than the information bits carried by the joint waveforms.
  • B. Downlink ISAC: Additional sensing waveforms may be needed for high-quality sensing when more joint waveforms are required than downlink communication streams, creating sensing-to-communication interference.Mitigating this interference is identified as the major downlink design challenge.

C. Uplink ISAC

In uplink ISAC, the base station receives sensing and communication signals from different transmitters but must estimate sensing parameters and decode information at the same destination. The central challenge is mitigating their mutual interference.

  • C. Uplink ISAC: Uplink ISAC keeps sensing transmission at the base station while the communication user uploads its signal to that same base station.The sensing echo and communication signal are consequently processed at a common destination.
  • C. Uplink ISAC: Unlike the downlink, the base station initially knows neither the sensing result contained in the echo nor the communication information to be decoded.This lack of prior knowledge complicates joint processing of the received signals.
  • C. Uplink ISAC: The major uplink design challenge is mitigating mutual interference while the base station simultaneously analyzes the sensing echo and decodes the communication message.The mixed sensing-communication reception creates interference in both processing tasks.

III. NOMA-ENHANCED DOWNLINK ISAC

The downlink ISAC designs use NOMA to address both inter-user interference and sensing-to-communication interference, targeting a better sensing-versus-communication tradeoff.

  • Two NOMA-based downlink ISAC designs separately target inter-user interference and sensing-to-communication interference.Their key distinction is whether NOMA operates within the communication functionality or between sensing and communication.
  • NOMA-empowered downlink ISAC addresses inter-user interference, while NOMA-inspired downlink ISAC mitigates sensing-to-communication interference.

A. NOMA-empowered Downlink ISAC Design

NOMA-empowered downlink ISAC uses superposition coding and successive interference cancellation while reusing communication signals for sensing. It improves the sensing-versus-communication tradeoff especially when spatial degrees of freedom are limited, but offers little benefit when they are sufficient.

  • A. NOMA-empowered Downlink ISAC Design: Superposition coding and SIC transmit and detect each user’s communication signal, while the superimposed signals also support target sensing.Because the communication signals are used for sensing, the number of joint sensing-and-communication waveforms equals the number of users, avoiding additional sensing-to-communication interference.
  • A. NOMA-empowered Downlink ISAC Design: NOMA-empowered downlink ISAC significantly enlarges the sensing-versus-communication tradeoff region in the overloaded regime compared with conventional downlink ISAC.SIC supplies extra degrees of freedom for inter-user interference mitigation when spatial degrees of freedom cannot support one per user.
  • A. NOMA-empowered Downlink ISAC Design: In underloaded settings, NOMA-empowered downlink ISAC is superior with high channel correlation and improves throughput under sensing-prior designs regardless of channel correlation.
  • A. NOMA-empowered Downlink ISAC Design: NOMA-empowered downlink ISAC is ineffective with low channel correlation and relaxed sensing requirements because available spatial degrees of freedom make SIC redundant.The authors relate its importance to future networks becoming more overloaded as connected-device numbers increase.

B. NOMA-inspired Downlink ISAC Design

NOMA-inspired downlink ISAC treats additional sensing signals as multicast transmissions to mitigate their interference with communication. It achieves a significant gain over designs that ideally remove or do not remove sensing interference, while the two proposed designs remain non-unified.

  • B. NOMA-inspired Downlink ISAC Design: Additional sensing waveforms improve sensing quality but can cause harmful communication interference, motivating a practical NOMA-inspired mitigation design.
  • B. NOMA-inspired Downlink ISAC Design: NOMA-inspired downlink ISAC achieves a significant sensing-versus-communication performance gain by further exploiting additional sensing signals for multicast transmission.Fig. 4(b) compares it with baselines that ideally remove sensing interference and that do not remove it.
  • B. NOMA-inspired Downlink ISAC Design: The two downlink NOMA-ISAC designs separately focus on inter-user interference and sensing-to-communication interference.A unified design that adaptively mitigates both interference types is identified as future work.

IV. NOMA-BASED UPLINK ISAC

Uplink ISAC must mitigate mutual interference between sensing echoes and communication signals colliding at the base station. The paper proposes pure-NOMA and semi-NOMA designs that differ in how fully sensing and communication share radio resources.

  • The uplink challenge is mitigating mutual interference between the sensing echo and communication signal received at the ISAC base station.
  • Pure-NOMA-based and semi-NOMA-based uplink ISAC designs differ in whether sensing and communication fully or partially share radio resources.Only the uplink communication signal carries information bits.

A. Pure-NOMA-based uplink ISAC

Pure-NOMA-based uplink ISAC fully shares radio resources and uses a fixed communication-to-sensing decoding order to separate communication and sensing. It protects sensing from communication interference but limits the communication rate.

  • Pure-NOMA-based uplink ISAC: Compared with OMA, pure-NOMA provides more available radio resources by mixing sensing and communication signals instead of separating them orthogonally.OMA allocates different orthogonal resources to the sensing echo and communication signal, which may reduce resource efficiency.
  • Pure-NOMA-based uplink ISAC: Figure 5 compares OMA, pure-NOMA, and semi-NOMA uplink designs using their achieved sensing-versus-communication tradeoffs.The figure presents the system configurations and initial numerical results for these three schemes.
  • Pure-NOMA-based uplink ISAC: A fixed communication-to-sensing SIC order removes the communication signal before sensing-echo analysis, enabling interference-free sensing over shared resources.Only the communication signal carries information bits, so it can be decoded and removed first.
  • Pure-NOMA-based uplink ISAC: Pure-NOMA treats communication as an add-on that does not negatively affect sensing, making it suitable for sensing-prior designs and spectrum already occupied by sensing.Its fixed decoding order preserves the sensing functionality while accommodating communication on shared resources.
  • Pure-NOMA-based uplink ISAC: The fixed decoding order makes the communication message decode against sensing interference, resulting in a limited communication rate.This limitation is compatible with IoT applications where required uplink data rates are usually low and sensing performance has priority.

B. Semi-NOMA-based uplink ISAC Design

Semi-NOMA-based uplink ISAC partitions radio resources into orthogonal sensing-only, communication-only, and shared components. This framework includes OMA and pure-NOMA as special cases while enabling flexible tradeoffs between sensing and communication.

  • B. Semi-NOMA-based uplink ISAC Design: Semi-NOMA partitions total radio resources into three orthogonal resource blocks for sensing-only, communication-only, and jointly shared operation.Only part of the resources is shared between sensing and communication except at the extreme cases.
  • B. Semi-NOMA-based uplink ISAC Design: Resource optimization can reduce semi-NOMA to OMA by nulling the shared block or to pure-NOMA by nulling both dedicated blocks.These reductions make the conventional schemes special cases of the proposed framework.
  • B. Semi-NOMA-based uplink ISAC Design: Semi-NOMA supports sensing-prior, communication-prior, and sensing-versus-communication tradeoff designs that neither OMA nor pure-NOMA can realize alone.Different objectives are addressed by adjusting allocation across the three resource blocks.
  • B. Semi-NOMA-based uplink ISAC Design: Allocating communication-only resources improves communication performance because those signals are not sensing-interference-limited as in pure-NOMA.This allocation enables a better sensing-versus-communication tradeoff.

V. CONCLUSIONS

The article develops NOMA-based ISAC designs from a multiple-access perspective to address interference between users and between sensing and communication. Its downlink and uplink proposals are reported as effective, with flexible uplink operation through semi-NOMA.

  • V. CONCLUSIONS: The article studies ISAC through NOMA and introduces downlink and uplink models alongside multiple-access design challenges caused by inter-functionality interference.The work follows ISAC’s development toward non-orthogonal operation.
  • V. CONCLUSIONS: NOMA-empowered and NOMA-inspired downlink designs address typical inter-user interference and sensing-to-communication interference, respectively.The designs employ NOMA within communication and between the two functionalities.
  • V. CONCLUSIONS: Pure-NOMA uplink ISAC targets sensing-prior operation, whereas semi-NOMA provides flexible resource allocation for different ISAC objectives.Semi-NOMA covers partially or fully shared resource operation through resource allocation.
  • V. CONCLUSIONS: Numerical results confirm the effectiveness of the proposed NOMA-ISAC designs.The article also identifies future directions including fundamental-limit analysis, resource-allocation optimization, and prototype implementation.
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