Joint reflection coefficient, time proportion and power allocation for multicarrier backscatter communications

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication Pub Date : 2025-09-04 DOI:10.1016/j.phycom.2025.102827

Gerryn Jo-Vee Goh, Chee Keong Tan, Joanne Mun-Yee Lim, Ying Loong Lee, Ke Feng, Li-Chun Wang

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引用次数: 0

Abstract

Massive growth of Internet of Things (IoT) applications is anticipated to result in an inevitable increase in network energy consumption (EC). To address this concern, we tackle the energy efficiency (EE) maximization problem for the multicarrier wireless-powered backscatter communication networks (WPBCNs), by jointly optimizing the resource allocation (RA) of transmit power, reflection coefficient (RC), and time proportion, under the worst-case scenario with interference between multiple backscatter devices in the multicarrier WPBCNs. To solve this problem, we propose an adaptive nonlinear fractional programming (NLFP)-based time-power swarm optimization (ANT-PSO) scheme, which is specifically designed to circumvent the hardness of the NLFP problem (NLFPP), as well as the randomness in the channel gains and interference present in the network. We apply the NLFP transformation method to improve the tractability of the problem. Additionally, we develop a new joint RC, time proportion and transmit power optimization algorithm based on swarm intelligence, with additional functions designed according to energy causality and resource constraints to facilitate solution exploration within the feasible range. Simulation results show that our proposed scheme outperforms several baseline schemes in the average worst-case EE for scenarios with different maximum transmit power levels, numbers of backscatter links and numbers of subcarriers.

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多载波反向散射通信的联合反射系数、时间比例和功率分配

物联网（IoT）应用的大规模增长预计将不可避免地导致网络能耗（EC）的增加。为解决这一问题，在多载波反向散射通信网络（WPBCNs）中多个反向散射设备相互干扰的最坏情况下，通过联合优化发射功率、反射系数（RC）和时间比例的资源分配（RA），解决了多载波反向散射通信网络（WPBCNs）的能效最大化问题。为了解决这一问题，我们提出了一种基于自适应非线性分数规划（NLFP）的时间-功率群优化（ANT-PSO）方案，该方案专门设计用于规避NLFP问题（NLFPP）的硬度，以及信道增益的随机性和网络中存在的干扰。我们应用NLFP变换方法来提高问题的可追溯性。此外，我们开发了一种新的基于群体智能的联合RC、时间比例和发射功率优化算法，并根据能量因果关系和资源约束设计了附加函数，便于在可行范围内进行求解。仿真结果表明，在不同最大发射功率水平、反向散射链路数量和子载波数量的情况下，我们提出的方案在平均最坏情况下的EE优于几种基准方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical Communication ENGINEERING, ELECTRICAL & ELECTRONICTELECO-TELECOMMUNICATIONS

CiteScore

5.00

自引率

9.10%

发文量

212

审稿时长

55 days

期刊介绍： PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published. Topics of interest include but are not limited to: Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.