Pub Date : 2026-02-03DOI: 10.1109/tcomm.2026.3660724
Ahrar N. Hamad, Ahmad Adnan Qidan, Taisir E.H. El-Gorashi, Jaafar M. H. Elmirghani
{"title":"Two-Agent DRL for Power Allocation and IRS Orientation in Dynamic NOMA-based OWC Networks","authors":"Ahrar N. Hamad, Ahmad Adnan Qidan, Taisir E.H. El-Gorashi, Jaafar M. H. Elmirghani","doi":"10.1109/tcomm.2026.3660724","DOIUrl":"https://doi.org/10.1109/tcomm.2026.3660724","url":null,"abstract":"","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"44 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1109/tcomm.2026.3659436
Yinghui Ye, Shuang Lu, Liqin Shi, Xiaoli Chu, Sumei Sun
{"title":"Symbiotic Backscatter Communication: A Design Perspective on the Modulation Scheme of Backscatter Devices","authors":"Yinghui Ye, Shuang Lu, Liqin Shi, Xiaoli Chu, Sumei Sun","doi":"10.1109/tcomm.2026.3659436","DOIUrl":"https://doi.org/10.1109/tcomm.2026.3659436","url":null,"abstract":"","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"87 1","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TCOMM.2026.3659026
Ricardo Souza Senandes;Glauber Brante;Richard Demo Souza;Amirhossein Azarbahram;Onel Luis Alcaraz López
This paper investigates the problem of energy beamforming for wireless power transfer (WPT) using dynamic metasurface antennas (DMAs). We propose a novel solution based on the bat algorithm (BA) to efficiently optimize the beamforming process. The proposed BA-based scheme enables simultaneous charging of multiple devices while avoiding power transmission in specific directions, such as areas where people or animals may be present. Our approach provides a robust and computationally efficient solution, considering key system constraints, including power transfer efficiency, antenna configurations, and DMA characteristics. Simulation results demonstrate that the BA-based method outperforms existing techniques in the literature, particularly those relying on alternating optimization, by achieving lower total power consumption and reduced computational complexity. These findings highlight the potential of the proposed method as a promising solution for future WPT systems employing DMAs.
{"title":"Bat Algorithm-Based Energy Beamforming for Wireless Power Transfer With Dynamic Metasurface Antennas","authors":"Ricardo Souza Senandes;Glauber Brante;Richard Demo Souza;Amirhossein Azarbahram;Onel Luis Alcaraz López","doi":"10.1109/TCOMM.2026.3659026","DOIUrl":"10.1109/TCOMM.2026.3659026","url":null,"abstract":"This paper investigates the problem of energy beamforming for wireless power transfer (WPT) using dynamic metasurface antennas (DMAs). We propose a novel solution based on the bat algorithm (BA) to efficiently optimize the beamforming process. The proposed BA-based scheme enables simultaneous charging of multiple devices while avoiding power transmission in specific directions, such as areas where people or animals may be present. Our approach provides a robust and computationally efficient solution, considering key system constraints, including power transfer efficiency, antenna configurations, and DMA characteristics. Simulation results demonstrate that the BA-based method outperforms existing techniques in the literature, particularly those relying on alternating optimization, by achieving lower total power consumption and reduced computational complexity. These findings highlight the potential of the proposed method as a promising solution for future WPT systems employing DMAs.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"4078-4089"},"PeriodicalIF":8.3,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TCOMM.2026.3658393
Sepehr Asvadi;Farid Ashtiani
Information freshness is one of the critical aspects of communication networks. Average age of information (AoI) and peak AoI (PAoI) are the main metrics for evaluating information freshness. Modeling the communication system with a stochastic hybrid system (SHS) is an effective approach for finding these metrics, especially in complex network scenarios. A regular SHS is comprised of a Markov chain (MC) and some stochastic processes evolving according to the state of the MC. The Markovian property of the chain in regular SHSs limits the capability of this approach in analyzing general network scenarios, e.g., when the transmission times of packets follow a general non-exponential distribution. In this work, we focus on the semi-Markovian-SHSs (SM-SHSs). In SM-SHSs, compared to regular SHSs, the Markovian property of the system chain is extended to semi-Markovian property, i.e., the sojourn time in each state follows an arbitrary distribution depending on the next transition in the system chain. We derive theorems for finding the average AoI and PAoI when the communication system is modeled with an SM-SHS. We also propose an age-ordering-aware multi-stream M/G/1/1 queueing system with the assumption of deterministic vacation times for the server and analyze this system using the SM-SHS approach.
{"title":"Semi-Markovian Stochastic Hybrid System: A New Method for Information Freshness Analysis","authors":"Sepehr Asvadi;Farid Ashtiani","doi":"10.1109/TCOMM.2026.3658393","DOIUrl":"10.1109/TCOMM.2026.3658393","url":null,"abstract":"Information freshness is one of the critical aspects of communication networks. Average age of information (AoI) and peak AoI (PAoI) are the main metrics for evaluating information freshness. Modeling the communication system with a stochastic hybrid system (SHS) is an effective approach for finding these metrics, especially in complex network scenarios. A regular SHS is comprised of a Markov chain (MC) and some stochastic processes evolving according to the state of the MC. The Markovian property of the chain in regular SHSs limits the capability of this approach in analyzing general network scenarios, e.g., when the transmission times of packets follow a general non-exponential distribution. In this work, we focus on the semi-Markovian-SHSs (SM-SHSs). In SM-SHSs, compared to regular SHSs, the Markovian property of the system chain is extended to semi-Markovian property, i.e., the sojourn time in each state follows an arbitrary distribution depending on the next transition in the system chain. We derive theorems for finding the average AoI and PAoI when the communication system is modeled with an SM-SHS. We also propose an age-ordering-aware multi-stream M/G/1/1 queueing system with the assumption of deterministic vacation times for the server and analyze this system using the SM-SHS approach.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"3984-3998"},"PeriodicalIF":8.3,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TCOMM.2026.3658408
Ali Nouruzi;Saeed Sheikhzadeh;Nader Mokari;Paeiz Azmi;Eduard A. Jorswieck;Melike Erol-Kantarci
In large-scale Internet of Things (IoT) deployments, efficiently allocating computing resources to IoT devices, while preserving the integrity and utility of their data, remains a critical challenge. This paper introduces a novel online probabilistic model designed to handle uncertainties in both demand and resource availability within IoT networks, where the computing tasks of requesting devices (RDs) are fulfilled by serving devices (SDs). The proposed model integrates stochastic elements and formulates an optimization problem that aims to minimize the number of active serving devices required for task offloading, subject to the constraints of available computing resources. To further enhance decision-making, the model incorporates the concept of Value of Information (VoI) to ensure that the informational utility of each device’s data remains above a predefined threshold during task processing. The optimization problem is addressed using a heuristic algorithm. In scenarios where no serving device is immediately available, tasks are temporarily stored in a buffer and deferred to the next time slot, with their waiting time being tracked. This task allocation process is inspired by bin-packing algorithms, which are known for their efficiency in resource management and task scheduling. Moreover, the paper evaluates the performance of the proposed solution under worst-case conditions through feasibility analysis, thereby demonstrating its robustness. Two buffering strategies, First-In First-Out (FIFO) and Last-In First-Out (LIFO), are also examined to model task retrieval and execution behavior. Results show that adopting the FIFO strategy can reduce the average waiting time by approximately 50%. Overall, the proposed framework provides a reliable and scalable task computing service, with each serving device capable of supporting, on average, four requesting devices under typical operating conditions.
{"title":"VoI-Guaranteed Task Computing for Massive IoT Under Demand and Resource Uncertainties","authors":"Ali Nouruzi;Saeed Sheikhzadeh;Nader Mokari;Paeiz Azmi;Eduard A. Jorswieck;Melike Erol-Kantarci","doi":"10.1109/TCOMM.2026.3658408","DOIUrl":"10.1109/TCOMM.2026.3658408","url":null,"abstract":"In large-scale Internet of Things (IoT) deployments, efficiently allocating computing resources to IoT devices, while preserving the integrity and utility of their data, remains a critical challenge. This paper introduces a novel online probabilistic model designed to handle uncertainties in both demand and resource availability within IoT networks, where the computing tasks of requesting devices (RDs) are fulfilled by serving devices (SDs). The proposed model integrates stochastic elements and formulates an optimization problem that aims to minimize the number of active serving devices required for task offloading, subject to the constraints of available computing resources. To further enhance decision-making, the model incorporates the concept of Value of Information (VoI) to ensure that the informational utility of each device’s data remains above a predefined threshold during task processing. The optimization problem is addressed using a heuristic algorithm. In scenarios where no serving device is immediately available, tasks are temporarily stored in a buffer and deferred to the next time slot, with their waiting time being tracked. This task allocation process is inspired by bin-packing algorithms, which are known for their efficiency in resource management and task scheduling. Moreover, the paper evaluates the performance of the proposed solution under worst-case conditions through feasibility analysis, thereby demonstrating its robustness. Two buffering strategies, First-In First-Out (FIFO) and Last-In First-Out (LIFO), are also examined to model task retrieval and execution behavior. Results show that adopting the FIFO strategy can reduce the average waiting time by approximately 50%. Overall, the proposed framework provides a reliable and scalable task computing service, with each serving device capable of supporting, on average, four requesting devices under typical operating conditions.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"3937-3951"},"PeriodicalIF":8.3,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an innovative framework that integrates electromagnetic inverse scattering with improved quadrature spatial modulation (IQSM) to simultaneously accomplish sensing, identification, and backscatter communication. Specifically tailored for energy- and spectrum-efficient wireless operations in highly cluttered environments, the proposed system employs distinct load impedance modulation at the tags to effectively separate structural and antenna mode signatures. Structural mode signals are processed using inverse scattering combined with compressive sensing techniques, enabling precise localization of both tags and surrounding clutter. Concurrently, antenna mode signals are utilized for accurate tag identification. In addition, the antenna mode enables the acquisition of the reliable channel state information (CSI), facilitating the integration of IQSM schemes into the backscatter communication module. Furthermore, we present a theoretical analysis by deriving the bit error probability (BEP) for the proposed system. The proposed system is validated through a proof-of-concept experimental setup consisting of transmit and receive arrays, each configured as a $3times 3$ uniform linear antenna array (ULA). Both simulation and experimental results confirm that the inverse scattering-based approach achieves high-precision sensing and accurate identification of tags individually or in combination. Additionally, the integration of IQSM significantly enhances spectral efficiency (SE) and data throughput, compared with the state-of-the-art systems that do not incorporate spatial modulation (SM) techniques. These findings highlight the effectiveness and practical viability of the proposed integrated sensing and communication system for challenging clutter-rich scenarios.
{"title":"Advanced Spatial Modulation-Aided Integrated Sensing and Backscatter Communication: System Design and Performance Analysis","authors":"Dingfei Ma;Junxiang Yang;Jia Zhan;Chi Zhang;Qingfeng Zhang;Yi Fang","doi":"10.1109/TCOMM.2026.3658378","DOIUrl":"10.1109/TCOMM.2026.3658378","url":null,"abstract":"This paper proposes an innovative framework that integrates electromagnetic inverse scattering with improved quadrature spatial modulation (IQSM) to simultaneously accomplish sensing, identification, and backscatter communication. Specifically tailored for energy- and spectrum-efficient wireless operations in highly cluttered environments, the proposed system employs distinct load impedance modulation at the tags to effectively separate structural and antenna mode signatures. Structural mode signals are processed using inverse scattering combined with compressive sensing techniques, enabling precise localization of both tags and surrounding clutter. Concurrently, antenna mode signals are utilized for accurate tag identification. In addition, the antenna mode enables the acquisition of the reliable channel state information (CSI), facilitating the integration of IQSM schemes into the backscatter communication module. Furthermore, we present a theoretical analysis by deriving the bit error probability (BEP) for the proposed system. The proposed system is validated through a proof-of-concept experimental setup consisting of transmit and receive arrays, each configured as a <inline-formula> <tex-math>$3times 3$ </tex-math></inline-formula> uniform linear antenna array (ULA). Both simulation and experimental results confirm that the inverse scattering-based approach achieves high-precision sensing and accurate identification of tags individually or in combination. Additionally, the integration of IQSM significantly enhances spectral efficiency (SE) and data throughput, compared with the state-of-the-art systems that do not incorporate spatial modulation (SM) techniques. These findings highlight the effectiveness and practical viability of the proposed integrated sensing and communication system for challenging clutter-rich scenarios.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"4123-4137"},"PeriodicalIF":8.3,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TCOMM.2026.3658404
Yuchen Zhang;Pinjun Zheng;Jie Ma;Henk Wymeersch;Tareq Y. Al-Naffouri
We investigate a multi-low Earth orbit (LEO) satellite system that simultaneously provides positioning and communication services to terrestrial user terminals. To address the challenges of accurately acquiring channel state information in LEO satellite systems, we propose a novel two-timescale positioning-aided channel estimation framework, exploiting the distinct variation rates of position-related parameters and channel gains inherent in LEO satellite channels. Using the misspecified Cramér-Rao bound (MCRB) theory, we systematically analyze positioning performance under practical imperfections, such as inter-satellite clock bias and carrier frequency offset. Furthermore, we theoretically demonstrate how position information derived from downlink positioning can enhance uplink channel estimation accuracy, even in the presence of positioning errors, through an MCRB-based analysis. To address the limited link budgets and communication rates of single-satellite communication, we develop a multi-LEO cooperative beamforming strategy for downlink transmission that leverages cluster-wise satellite cooperation while maintaining reduced complexity. Theoretical analyses and numerical results confirm the effectiveness of the proposed framework in facilitating high-precision downlink positioning under practical imperfections, facilitating uplink channel estimation, and enabling efficient downlink communication.
{"title":"Positioning-Aided Channel Estimation for Multi-LEO Satellite Cooperative Beamforming","authors":"Yuchen Zhang;Pinjun Zheng;Jie Ma;Henk Wymeersch;Tareq Y. Al-Naffouri","doi":"10.1109/TCOMM.2026.3658404","DOIUrl":"10.1109/TCOMM.2026.3658404","url":null,"abstract":"We investigate a multi-low Earth orbit (LEO) satellite system that simultaneously provides positioning and communication services to terrestrial user terminals. To address the challenges of accurately acquiring channel state information in LEO satellite systems, we propose a novel two-timescale positioning-aided channel estimation framework, exploiting the distinct variation rates of position-related parameters and channel gains inherent in LEO satellite channels. Using the misspecified Cramér-Rao bound (MCRB) theory, we systematically analyze positioning performance under practical imperfections, such as inter-satellite clock bias and carrier frequency offset. Furthermore, we theoretically demonstrate how position information derived from downlink positioning can enhance uplink channel estimation accuracy, even in the presence of positioning errors, through an MCRB-based analysis. To address the limited link budgets and communication rates of single-satellite communication, we develop a multi-LEO cooperative beamforming strategy for downlink transmission that leverages cluster-wise satellite cooperation while maintaining reduced complexity. Theoretical analyses and numerical results confirm the effectiveness of the proposed framework in facilitating high-precision downlink positioning under practical imperfections, facilitating uplink channel estimation, and enabling efficient downlink communication.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"74 ","pages":"3888-3903"},"PeriodicalIF":8.3,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146070303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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