NOMA Inspired Integrated Sensing and Communication

Wang, Zhaolin; Mu, Xidong; Liu, Yuanwei; Ding, Zhiguo

doi:10.48550/arxiv.2201.04547

Cited by 4 publications

(6 citation statements)

References 26 publications

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“…Therefore, by jointly designing the novel unified ISAC waveform, the flexible trade-off between sensing and communication performance has been widely investigated [28]- [30]. Recent research contributions have also evaluated the benefits of NOMA for ISAC [7]- [9].…”

Section: ) Studies On Isacmentioning

confidence: 99%

“…In NOMA, the superposition coding (SC) and successive interference cancellation (SIC) are exploited at the transmitter and the receiver to allow multiple users to share the same resource block [6]. In this context, various benefits of NOMA in terms of enhancing the resource efficiency and mitigating the interference have been widely investigated in both in both ISAC systems [7]- [9] and mobile computing systems [10]- [14]. Hence, it is highly valuable to evaluate the potential benefits of NOMA in the multi-functional wireless networks.…”

Section: Introductionmentioning

confidence: 99%

“…From another aspect, the authors of [8] considered a scenario where the radar targets also require information transmission and proposed two multicast-unicast frameworks for both single and multiple user-target pairs based on beamformer-based and cluster-based NOMA, respectively. As a further advance, the authors of [9] exploited a composite signal model and developed a NOMA-inspired scheme to achieve the double benefits of the sensing signal for both communication and sensing.…”

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confidence: 99%

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NOMA-aided Joint Communication, Sensing, and Multi-tier Computing Systems

Wang¹,

Mu²,

Liu³

et al. 2022

Preprint

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A non-orthogonal multiple access (NOMA)-aided joint communication, sensing, and multi-tier computing (JCSMC) framework is proposed. In this framework, a multi-functional base station (BS) carries out target sensing, while providing edge computing services to the nearby users. To enhance the computation efficiency, the multi-tier computing structure is exploited, where the BS can further offload the computation tasks to a powerful Cloud server (CS). The potential benefits of employing NOMA in the proposed JCSMC framework is investigated, which can maximize the computation offloading capacity and suppress the inter-function interference. Based on the proposed framework, the transmit beamformer of the BS and computation resource allocation at the BS and the CS are jointly optimized to maximize the computation rate subject to the communication-computation causality and the sensing quality constraints.Both partial and binary computation offloading modes are considered: 1) For the partial offloading mode, a weighted minimum mean square error based alternating optimization algorithm is proposed to solve the corresponding non-convex optimization problem. It is proved that a Karush-Kuhn-Tucker optimal solution can be obtained; 2) For the binary offloading mode, the resultant highly-coupled mixedinteger optimization problem is first transformed to an equivalent but more tractable form. Then, the reformulated problem is solved by utilizing the alternating direction method of multipliers approach to obtain a nearly optimal solution. Finally, numerical results verify the effectiveness of the proposed algorithms and reveal that: i) the computation rate can be significantly enhanced by exploiting the multitier computing architecture when the BS is resource-limited; and ii) the proposed NOMA-aided JSCMC framework is superior in multi-function interference management and can achieve high-quality sensing and computing functions simultaneously compared with other benchmark schemes.

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Section: ) Studies On Isacmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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NOMA-aided Joint Communication, Sensing, and Multi-tier Computing Systems

Wang¹,

Mu²,

Liu³

et al. 2022

Preprint

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“…As a further advance, the information bits conveyed in the additional joint S&C waveforms can be also made useful to communication users. For example, the additional joint S&C waveforms in [14] are employed to convey multicast messages intended for all communication users, thus benefiting both sensing and communication, namely double benefits. Here, "Ideal SenIC" refers to ideally removing sensing interference at the user [10] and "No SenIC" refers to not removing the sensing interference [11].…”

Section: B Noma-inspired Downlink Isac Designmentioning

confidence: 99%

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

Mu¹,

Wang²,

Liu³

2022

Preprint

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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 orthogonality to 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 NOMA-empowered downlink ISAC and NOMA-inspired downlink ISAC to effectively coordinate the inter-user interference and the sensingto-communication interference, respectively. (2) For the uplink ISAC, we first propose a 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 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.

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“…The advancement of the beyond-fifth-generation (B5G) and sixth-generation (6G) communication networks has led to various integrated sensing and communication (ISAC) applications, such as auto-driving, vehicle-to-everything, smart home, virtual/augmented reality, and edge intelligence [1]- [5]. In ISAC systems, the sensing and communication capabilities are tightly integrated to provide both sensing and communication services [6]- [16]. The resources of communication and radar sensing can be shared in ISAC systems, thereby boosting the efficiency of utilization in terms of spectrum, hardware, energy, and cost [17].…”

Section: Introductionmentioning

confidence: 99%

Optimized Design for IRS-Assisted Integrated Sensing and Communication Systems in Clutter Environments

Chikun¹,

Wang²,

Lau³

2022

Preprint

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In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform linear array (ULA), a multi-antenna base station (BS) is targeted for communicating with multiple communication users (CUs) and sensing multiple targets simultaneously. We consider the IRSassisted ISAC design in the case with Type-I or Type-II CUs, where each Type-I and Type-II CU can and cannot cancel the interference from sensing signals, respectively. In particular, we aim to maximize the minimum sensing beampattern gain among multiple targets, by jointly optimizing the BS transmit beamforming vectors and the IRS phase shifting matrix, subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each Type-I/Type-II CU, the interference power constraint per clutter, the transmission power constraint at the BS, and the cross-correlation pattern constraint. Due to the coupling of the BS's transmit design variables and the IRS's phase shifting matrix, the formulated max-min IRSassisted ISAC design problem in the case with Type-I/Type-II CUs is highly non-convex. As such, we propose an efficient algorithm based on the alternating-optimization and semi-definite relaxation (SDR) techniques. In the case with Type-I CUs, we show that the dedicated sensing signal at the BS is always beneficial to improve the sensing performance. By contrast, the dedicated sensing signal at the BS is not required in the case with Type-II CUs. Numerical results are provided to show that the proposed IRS-assisted ISAC design schemes achieve a significant gain over the existing benchmark schemes.

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NOMA Inspired Integrated Sensing and Communication

Cited by 4 publications

References 26 publications

NOMA-aided Joint Communication, Sensing, and Multi-tier Computing Systems

NOMA-aided Joint Communication, Sensing, and Multi-tier Computing Systems

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

Optimized Design for IRS-Assisted Integrated Sensing and Communication Systems in Clutter Environments

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