RIS 增强型反向散射无线共生网络的资源分配设计

IF 7 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-08-05 DOI:10.1109/TCCN.2024.3438363
Yibo Yi;Xinyue Hu;Caihong Kai;Wei Huang
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引用次数: 0

摘要

同时无线信息和电力传输(SWIPT)与反向散射和可重构智能表面(RIS)辅助通信的集成为降低能耗提供了一个有前途的范例。在本文中,我们提出了一种在共生无线网络中ris增强的混合反向散射和无线供电传输方案。在此设置下,通过联合优化发射波束形成、无源波束形成、发射功率、后向散射系数和时隙分配,提出了吞吐量最大化问题。由于变量耦合,公式优化是非凸的。为了解决这一问题,提出了一种迭代算法,将其分解为多个子问题。具体地说,我们得到了这些变量在单用户系统中的闭型解。对于多用户系统,我们采用二阶锥规划(SOCP)和半确定规划(SDP)方法来解决这个问题。仿真结果表明,所提出的混合传输方案能够有效地提高网络吞吐量。
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Resource Allocation Design for RIS-Enhanced Backscatter Wireless-Powered Symbiotic Networks
The integration of simultaneous wireless information and power transfer (SWIPT) with backscatter and reconfigurable intelligent surface (RIS)-aided communication provides a promising paradigm to reduce the energy consumption. In this paper, we propose a RIS-enhanced hybrid backscatter and wireless-powered transmission scheme in the symbiotic radio network. Under this setting, we formulate the throughput maximization problem by jointly optimizing the transmit beamforming, passive beamforming, transmit power, backscatter coefficient, and slot allocation. Due to the coupled variables, the formulated optimization is non-convex. To solve it, an iterative algorithm is developed to decompose it into multiple subproblems. Specifically, we obtain the closed-form solutions for those variables in the single-user system. For the multi-user system, we solve the problem via the second-order cone programming (SOCP) and semi-definite programming (SDP) methods. Numerical simulations show that the proposed hybrid transmission scheme can effectively improve the network throughput.
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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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