Cooperative NOMA Empowered Integrated Sensing and Communication: Joint Beamforming and User Pairing

IF 7 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-07-03 DOI:10.1109/TCCN.2024.3414394
Ali Amhaz;Mohamed Elhattab;Chadi Assi;Sanaa Sharafeddine
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Abstract

In this paper, we consider a downlink communication and sensing system where cooperative non-orthogonal multiple access (C-NOMA) is adopted as a multiple access technique to jointly provide communication functionality to a set of users and sensing functionality to targets. Specifically, we leverage the potential gains of cooperative links between far and near NOMA users in terms of reducing the power allocated from the base station (BS) to far NOMA users to dedicate more resources to the sensing function. In doing so, we formulate this framework as an optimization problem to maximize the achievable sum rate of the communication users by jointly optimizing the users’ pairing scheme, transmit beamforming at the BS, and near users’ transmit power while respecting the required communication and sensing quality of service (QoS) constraints. Owing to the non-convexity of the formulated problem, we divide this problem into two sub-problems, namely the user paring sub-problem and the power allocation sub-problem. To solve the first sub-problem, we present a novel pairing approach that exploits channel orthogonality and correlation among different users. Then, we define a double-layer penalty-based algorithm to handle the non-convex structure of the second sub-problem. Finally, the numerical results clearly showed the effectiveness of our adopted C-NOMA system over traditional baseline schemes, where our proposed scheme achieves gains reaching up to 20% compared to traditional NOMA, and 40% compared to spatial division multiple access (SDMA). Moreover, our pairing strategy achieved performance reaching 95% that of the optimal pairing scheme.
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合作式 NOMA 增强型综合传感与通信:联合波束成形和用户配对
本文研究了一种采用协同非正交多址(C-NOMA)作为多址技术的下行通信传感系统,该系统为一组用户共同提供通信功能,同时为目标提供传感功能。具体来说,我们利用远端和近端NOMA用户之间的合作链路的潜在收益,减少从基站(BS)分配给远端NOMA用户的功率,从而将更多的资源用于传感功能。在此过程中,我们将该框架定义为一个优化问题,通过共同优化用户的配对方案、在BS处发射波束成形和接近用户发射功率,同时尊重所需的通信和感知服务质量(QoS)约束,从而最大化可实现的通信用户和速率。由于所提问题的非凸性,我们将该问题分为两个子问题,即用户配对子问题和功率分配子问题。为了解决第一个子问题,我们提出了一种新的配对方法,利用信道正交性和不同用户之间的相关性。然后,我们定义了一个基于双层惩罚的算法来处理第二个子问题的非凸结构。最后,数值结果清楚地显示了我们所采用的C-NOMA系统比传统基准方案的有效性,与传统NOMA相比,我们所提出的方案的增益可达20%,与SDMA相比可达40%。此外,我们的配对策略的性能达到了最优配对方案的95%。
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来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
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