Pub Date : 2025-12-23DOI: 10.1109/OJCOMS.2025.3647566
Ahmed O. Elmeligy;Ioannis Psaromiligkos;Au Minh
The use of cellular networks for massive machine-type communications (mMTC), is an attractive solution due to the availability of existing infrastructure. However, the sheer number of user equipments (UEs) creates congestion and overloading challenges on the random access channel (RACH). To address this, we develop a multi-armed bandit (MAB)-based reinforcement learning (RL) approach that learns optimal preamble selection strategies without requiring the base station (BS) to know the number of UEs in the network. We first model a two-priority RACH that captures the behavior of UEs through access patterns observed at the BS. This enables us to design a non-uniform preamble selection scheme and formulate an optimization problem that seeks the best preamble selection probabilities to maximize high-priority UE success while constraining low-priority access. Our proposed RL framework uses a discretized and compressed the action space (AS) to improve scalability, and uses cross-entropy methods to efficiently update the MAB solution. In addition, we present a compact AS (CAS) approach that leverages a lookup table of pre-optimized preamble selection probabilities across different network loads. This not only reduces the AS further but also enables implicit network load estimation. Numerical experiments show that the proposed method offers higher throughput for high priority UEs compared to the uniform preamble selection scheme, as well as an access class barring scheme, while maintaining a minimum throughput for low priority UEs.
{"title":"Preamble Selection Probability Optimization in RACH: A Multi-Armed Bandits Approach","authors":"Ahmed O. Elmeligy;Ioannis Psaromiligkos;Au Minh","doi":"10.1109/OJCOMS.2025.3647566","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3647566","url":null,"abstract":"The use of cellular networks for massive machine-type communications (mMTC), is an attractive solution due to the availability of existing infrastructure. However, the sheer number of user equipments (UEs) creates congestion and overloading challenges on the random access channel (RACH). To address this, we develop a multi-armed bandit (MAB)-based reinforcement learning (RL) approach that learns optimal preamble selection strategies without requiring the base station (BS) to know the number of UEs in the network. We first model a two-priority RACH that captures the behavior of UEs through access patterns observed at the BS. This enables us to design a non-uniform preamble selection scheme and formulate an optimization problem that seeks the best preamble selection probabilities to maximize high-priority UE success while constraining low-priority access. Our proposed RL framework uses a discretized and compressed the action space (AS) to improve scalability, and uses cross-entropy methods to efficiently update the MAB solution. In addition, we present a compact AS (CAS) approach that leverages a lookup table of pre-optimized preamble selection probabilities across different network loads. This not only reduces the AS further but also enables implicit network load estimation. Numerical experiments show that the proposed method offers higher throughput for high priority UEs compared to the uniform preamble selection scheme, as well as an access class barring scheme, while maintaining a minimum throughput for low priority UEs.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10761-10780"},"PeriodicalIF":6.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313341","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mid-band frequencies have recently attracted attention as promising sixth-generation (6G) candidates due to their potential to mitigate the instability of sub-terahertz (sub-THz) and millimeter-wave (mmWave) bands. While ongoing studies investigate channel models for this spectrum, they largely focus on individual frequencies across diverse environments. For mobile network operators (MNOs), measurement-based comparative studies that directly evaluate the advantages and limitations of candidate bands under identical deployment scenarios are essential. Obtaining high-resolution channel impulse responses (CIRs) in the mid-band, however, is constrained by limited spectrum availability, and existing approaches often rely on costly, synchronization-dependent equipment, thereby restricting portability and versatility. This paper proposes an asynchronous and portable software-defined radio (SDR)-based channel sounder that employs a Zadoff-Chu (ZC) sequence to enable direct comparison between frequency range 1 (FR1, 4.55 GHz and 6.55 GHz) and FR3 (7.15 GHz) under identical transceiver conditions. The SDR system was validated through back-to-back calibration, and the verified platform was subsequently used to conduct channel measurement campaigns in both indoor hotspot (InH) and urban microcell (UMi) environments. The measured data were analyzed in terms of path loss and large-scale characteristics, and parameter comparisons with the third generation partnership projects (3GPP) standard were performed to ensure validity. The results of this channel analysis are expected to provide practical insights into frequency band selection for future 6G services.
{"title":"SDR-Based Portable Channel Sounding System for 6G FR1 and FR3 Bands: Design and Validation","authors":"Yunhwa Shin;Sangwoo Shin;Jinyoung Lee;Jihoon Kim;Minsoo Na;Jaehyun Lee;Jeongsik Choi","doi":"10.1109/OJCOMS.2025.3647510","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3647510","url":null,"abstract":"Mid-band frequencies have recently attracted attention as promising sixth-generation (6G) candidates due to their potential to mitigate the instability of sub-terahertz (sub-THz) and millimeter-wave (mmWave) bands. While ongoing studies investigate channel models for this spectrum, they largely focus on individual frequencies across diverse environments. For mobile network operators (MNOs), measurement-based comparative studies that directly evaluate the advantages and limitations of candidate bands under identical deployment scenarios are essential. Obtaining high-resolution channel impulse responses (CIRs) in the mid-band, however, is constrained by limited spectrum availability, and existing approaches often rely on costly, synchronization-dependent equipment, thereby restricting portability and versatility. This paper proposes an asynchronous and portable software-defined radio (SDR)-based channel sounder that employs a Zadoff-Chu (ZC) sequence to enable direct comparison between frequency range 1 (FR1, 4.55 GHz and 6.55 GHz) and FR3 (7.15 GHz) under identical transceiver conditions. The SDR system was validated through back-to-back calibration, and the verified platform was subsequently used to conduct channel measurement campaigns in both indoor hotspot (InH) and urban microcell (UMi) environments. The measured data were analyzed in terms of path loss and large-scale characteristics, and parameter comparisons with the third generation partnership projects (3GPP) standard were performed to ensure validity. The results of this channel analysis are expected to provide practical insights into frequency band selection for future 6G services.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10802-10815"},"PeriodicalIF":6.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313337","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates pilot and data power optimization for cell-free massive MIMO (CF-mMIMO). We propose an iterative algorithm that jointly updates pilot and data power levels to improve channel estimation and ensure reliable data transmission. Pilot powers are allocated based on the normalized mean square error (NMSE) of channel estimation, granting higher power to users with poor estimates while reducing interference for users with favorable conditions. Based on the resulting channel state information (CSI), data powers are then optimized via geometric programming to achieve max–min fairness across users. By alternating between NMSE-driven pilot power control and fairness-oriented data power allocation until convergence, the proposed method achieves efficient CSI acquisition, balanced interference management, and enhanced fairness. In addition, we introduce a lightweight access point (AP)–user association algorithm that ranks AP–user channel strengths, limits the number of users per AP, and employs iterative replacement to ensure scalability and full user connectivity. Simulation results demonstrate that the proposed framework significantly improves spectral efficiency and fairness compared to conventional methods, while remaining suitable for practical CF-mMIMO deployments.
{"title":"Pilot and Data Power Control for Scalable Uplink Cell-Free Massive MIMO","authors":"Saeed Mohammadzadeh;Mostafa Rahmani Ghourtani;Kanapathippillai Cumanan;Alister Burr;Pei Xiao","doi":"10.1109/OJCOMS.2025.3647368","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3647368","url":null,"abstract":"This paper investigates pilot and data power optimization for cell-free massive MIMO (CF-mMIMO). We propose an iterative algorithm that jointly updates pilot and data power levels to improve channel estimation and ensure reliable data transmission. Pilot powers are allocated based on the normalized mean square error (NMSE) of channel estimation, granting higher power to users with poor estimates while reducing interference for users with favorable conditions. Based on the resulting channel state information (CSI), data powers are then optimized via geometric programming to achieve max–min fairness across users. By alternating between NMSE-driven pilot power control and fairness-oriented data power allocation until convergence, the proposed method achieves efficient CSI acquisition, balanced interference management, and enhanced fairness. In addition, we introduce a lightweight access point (AP)–user association algorithm that ranks AP–user channel strengths, limits the number of users per AP, and employs iterative replacement to ensure scalability and full user connectivity. Simulation results demonstrate that the proposed framework significantly improves spectral efficiency and fairness compared to conventional methods, while remaining suitable for practical CF-mMIMO deployments.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10829-10844"},"PeriodicalIF":6.3,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11311474","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1109/OJCOMS.2025.3646332
Mohammad Reza Yari;Paeiz Azmi;Moslem Forouzesh
This study investigates covert communication in the presence of a half-duplex amplify-and-forward (AF) relay, while accounting for transceiver hardware impairments. A cooperative jamming strategy and channel uncertainty are employed to achieve covertness. For a trusted relay, informed jammers mitigate the effect of artificial noise (AN) at the legitimate receiver and increase the warden’s uncertainty, thereby enhancing the covert rate. For an untrusted relay, the jammer must emit AN while the data signal is transmitted toward the untrusted relay to reduce the untrusted relay’s signal-to-interference-plus-noise ratio (SINR), which poses a challenge for deploying an informed jammer. The results show that, in both trusted and untrusted relay scenarios, increasing the transmit power yields only marginal performance gains due to hardware impairments, highlighting the importance of high-quality transceivers and compensation algorithms. Notably, under specific conditions, impairments in the legitimate receiver’s transmitter can slightly enhance performance in the trusted relay case, while in untrusted relay scenarios, impairments in any legitimate node degrade covert communication performance. Differences in hardware equipment quality between the transmitter (or retransmitter) and its associated jammer also affect the warden’s ability to detect the transmission.
{"title":"Cooperative Covert Communication With Transceiver Hardware Impairments","authors":"Mohammad Reza Yari;Paeiz Azmi;Moslem Forouzesh","doi":"10.1109/OJCOMS.2025.3646332","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3646332","url":null,"abstract":"This study investigates covert communication in the presence of a half-duplex amplify-and-forward (AF) relay, while accounting for transceiver hardware impairments. A cooperative jamming strategy and channel uncertainty are employed to achieve covertness. For a trusted relay, informed jammers mitigate the effect of artificial noise (AN) at the legitimate receiver and increase the warden’s uncertainty, thereby enhancing the covert rate. For an untrusted relay, the jammer must emit AN while the data signal is transmitted toward the untrusted relay to reduce the untrusted relay’s signal-to-interference-plus-noise ratio (SINR), which poses a challenge for deploying an informed jammer. The results show that, in both trusted and untrusted relay scenarios, increasing the transmit power yields only marginal performance gains due to hardware impairments, highlighting the importance of high-quality transceivers and compensation algorithms. Notably, under specific conditions, impairments in the legitimate receiver’s transmitter can slightly enhance performance in the trusted relay case, while in untrusted relay scenarios, impairments in any legitimate node degrade covert communication performance. Differences in hardware equipment quality between the transmitter (or retransmitter) and its associated jammer also affect the warden’s ability to detect the transmission.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10781-10801"},"PeriodicalIF":6.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11304711","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of Terrestrial and Non-Terrestrial Networks (T/NTNs) represents one of the most disruptive innovations on the basis of the upcoming $6{^{text {th}}}$ Generation (6G) of mobile communication systems. By incorporating Uncrewed Aerial Vehicles, High Altitude Platform, and multi-orbit satellite constellations, it ushers in a new concept of network deployment that intends to enrich the coverage of typical terrestrial wireless systems in congested scenarios, provide ubiquitous connectivity to unconnected areas, and offer concrete support to next-generation use cases and applications. At the time of this writing, the standardization process of integrated T/NTNs is going to reach its peak of activity and many technological issues (spanning from advanced physical layer transmission techniques to flexible network management operations) are still under investigation. Indeed, considering that experimental tests can significantly sustain the study of both academia and industry, the knowledge of hardware and software tools able to emulate specific aspects of the overall network architecture would significantly boost the research towards concrete and solid technical solutions moving from theory to practice. Based on these premises, the contribution presented herein provides a comprehensive survey of hands-on solutions through which experimental testbeds dedicated to integrated T/NTNs can be deployed. Specifically, it encompasses hardware (such as Software-Defined Radios, channel emulators, Commercial Off-The-Shelf User Equipment, etc.), software (including those emulating core and radio access network), remotely accessible platforms, and other key enabling technologies of 6G. After reviewing some significant scientific works that adopted a subset of these solutions in their investigations, this survey sheds light on their adoption in more complex and heterogeneous network deployments. Finally, it summarizes the lessons learned and provides a list of challenging research topics related to the experimental tests of integrated T/NTNs.
{"title":"Hands-On Solutions for Testing Integrated Terrestrial and Non-Terrestrial Networks: A Comprehensive Survey","authors":"Salvatore Carbonara;Marco Olivieri;Arcangela Rago;Vincenzo Sciancalepore;Giuseppe Piro;Gennaro Boggia;Luigi Alfredo Grieco","doi":"10.1109/OJCOMS.2025.3646364","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3646364","url":null,"abstract":"The integration of Terrestrial and Non-Terrestrial Networks (T/NTNs) represents one of the most disruptive innovations on the basis of the upcoming <inline-formula> <tex-math>$6{^{text {th}}}$ </tex-math></inline-formula> Generation (6G) of mobile communication systems. By incorporating Uncrewed Aerial Vehicles, High Altitude Platform, and multi-orbit satellite constellations, it ushers in a new concept of network deployment that intends to enrich the coverage of typical terrestrial wireless systems in congested scenarios, provide ubiquitous connectivity to unconnected areas, and offer concrete support to next-generation use cases and applications. At the time of this writing, the standardization process of integrated T/NTNs is going to reach its peak of activity and many technological issues (spanning from advanced physical layer transmission techniques to flexible network management operations) are still under investigation. Indeed, considering that experimental tests can significantly sustain the study of both academia and industry, the knowledge of hardware and software tools able to emulate specific aspects of the overall network architecture would significantly boost the research towards concrete and solid technical solutions moving from theory to practice. Based on these premises, the contribution presented herein provides a comprehensive survey of hands-on solutions through which experimental testbeds dedicated to integrated T/NTNs can be deployed. Specifically, it encompasses hardware (such as Software-Defined Radios, channel emulators, Commercial Off-The-Shelf User Equipment, etc.), software (including those emulating core and radio access network), remotely accessible platforms, and other key enabling technologies of 6G. After reviewing some significant scientific works that adopted a subset of these solutions in their investigations, this survey sheds light on their adoption in more complex and heterogeneous network deployments. Finally, it summarizes the lessons learned and provides a list of challenging research topics related to the experimental tests of integrated T/NTNs.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10729-10760"},"PeriodicalIF":6.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11304714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vehicle-to-Everything (V2X) networks face significant challenges in achieving optimal, reliable routing due to their large scale, high mobility, and rapidly changing topologies. Traditional routing approaches have been applied to address this highly dynamic behavior, but they often fail to deliver steady performance in dynamic environments. In this study, we introduce Quantum-Heuristic Routing for $V2X$ (QHR-V2X), a novel paradigm that integrates the heuristic efficiency of the $A^{*}$ algorithm with quantum-inspired amplitude amplification. The proposed scheme is designed to enable rapid and optimal route discovery while reducing redundant exploration. This makes it particularly suitable for latency-sensitive vehicular environments. To validate its effectiveness, QHR-V2X was evaluated against two classical baselines, Dijkstra and $A^{*}$ , within grid-based simulation environments of increasing size and obstacle density. Experimental results show that QHR-V2X achieves significantly lower route-discovery time and reduced message overhead compared to classical algorithms, while maintaining path lengths nearly identical to those of the optimal routes produced by Dijkstra. These findings demonstrate the potential of QHR-V2X to improve scalability and responsiveness in next-generation $V2X$ communications.
{"title":"QHR-V2X: A Quantum-Heuristic Routing Framework for Efficient V2X Path Discovery","authors":"Zahid Khan;Sultan Hamad Almogbil;Muhammad Babar;Adel Ammar;Wadii Boulila","doi":"10.1109/OJCOMS.2025.3644144","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3644144","url":null,"abstract":"Vehicle-to-Everything (V2X) networks face significant challenges in achieving optimal, reliable routing due to their large scale, high mobility, and rapidly changing topologies. Traditional routing approaches have been applied to address this highly dynamic behavior, but they often fail to deliver steady performance in dynamic environments. In this study, we introduce Quantum-Heuristic Routing for <inline-formula> <tex-math>$V2X$ </tex-math></inline-formula> (QHR-V2X), a novel paradigm that integrates the heuristic efficiency of the <inline-formula> <tex-math>$A^{*}$ </tex-math></inline-formula> algorithm with quantum-inspired amplitude amplification. The proposed scheme is designed to enable rapid and optimal route discovery while reducing redundant exploration. This makes it particularly suitable for latency-sensitive vehicular environments. To validate its effectiveness, QHR-V2X was evaluated against two classical baselines, Dijkstra and <inline-formula> <tex-math>$A^{*}$ </tex-math></inline-formula>, within grid-based simulation environments of increasing size and obstacle density. Experimental results show that QHR-V2X achieves significantly lower route-discovery time and reduced message overhead compared to classical algorithms, while maintaining path lengths nearly identical to those of the optimal routes produced by Dijkstra. These findings demonstrate the potential of QHR-V2X to improve scalability and responsiveness in next-generation <inline-formula> <tex-math>$V2X$ </tex-math></inline-formula> communications.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"211-221"},"PeriodicalIF":6.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11304703","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1109/OJCOMS.2025.3645857
Hong Liang;Boyang Guo;Youjia Chen;Yuchuan Ye;Xi Wang;Jinsong Hu;Haifeng Zheng
Compared with traditional fixed frequency reuse patterns or optimization relying on channel information, artificial intelligence (AI)-based approaches using mobile big data provide another effective and efficient way for interference management. This paper proposes a data-driven interference coordination framework. First, Graphormer is adopted to model the inter-cell interference, where the node features capture the cell’s parameters, like power and allocated spectrum, and the edge features capture the interference relationships between neighboring cells. Second, a performance evaluation module is designed to establish a comprehensive understanding between network performance and wireless resource allocation, traffic requirement, interference, and so on. Then, proximal policy optimization (PPO) is utilized to dynamically optimize the spectrum allocation to enhance network performance while meeting dynamic traffic demands. Experimental results demonstrate that: i) the Graphormer-based interference modeling outperforms other algorithms in estimation accuracy; ii) the proposed approach effectively reduces inter-cell interference and improves network performance compared to other benchmark algorithms.
{"title":"Data-Driven Inter-Cell Interference Coordination for Mobile Cellular Networks","authors":"Hong Liang;Boyang Guo;Youjia Chen;Yuchuan Ye;Xi Wang;Jinsong Hu;Haifeng Zheng","doi":"10.1109/OJCOMS.2025.3645857","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3645857","url":null,"abstract":"Compared with traditional fixed frequency reuse patterns or optimization relying on channel information, artificial intelligence (AI)-based approaches using mobile big data provide another effective and efficient way for interference management. This paper proposes a data-driven interference coordination framework. First, Graphormer is adopted to model the inter-cell interference, where the node features capture the cell’s parameters, like power and allocated spectrum, and the edge features capture the interference relationships between neighboring cells. Second, a performance evaluation module is designed to establish a comprehensive understanding between network performance and wireless resource allocation, traffic requirement, interference, and so on. Then, proximal policy optimization (PPO) is utilized to dynamically optimize the spectrum allocation to enhance network performance while meeting dynamic traffic demands. Experimental results demonstrate that: i) the Graphormer-based interference modeling outperforms other algorithms in estimation accuracy; ii) the proposed approach effectively reduces inter-cell interference and improves network performance compared to other benchmark algorithms.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"169-181"},"PeriodicalIF":6.3,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11303575","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-17DOI: 10.1109/OJCOMS.2025.3645207
Iqra Batool;Mostafa M. Fouda;Muhammad Ismail;Mohamed I. Ibrahem;Zubair Md Fadlullah;Nei Kato
Massive MIMO beamforming for 6G networks faces a fundamental tradeoff between solution quality and computational complexity. Exhaustive search guarantees optimal antenna selection; however, this becomes prohibitively expensive for arrays exceeding 16 elements, while polynomial-time classical heuristics sacrifice 15–25% performance to achieve practical scalability. This paper introduces a quantum-enhanced optimization framework using the Quantum Approximate Optimization Algorithm (QAOA) to address this challenge for IoT-integrated 6G massive MIMO systems. Our approach combines quantum solution exploration with classical parameter optimization, integrating realistic 3GPP TR 38.901 channel models across 28–60 GHz bands and heterogeneous IoT device characteristics (mMTC, URLLC, eMBB). The framework incorporates an adaptive penalty mechanism that achieves constraint satisfaction within five iterations while maintaining polynomial complexity. Statistical validation across 50 independent channel realizations demonstrates significant advantages: 10–20% spectral efficiency improvement over classical heuristics ($p lt 0.001$ , Cohen’s $d = 1.24$ ), 35–42% IoT energy reduction, and 90–95% near-optimal solution quality compared to 65–85% for polynomial-time classical methods. Hardware validation on IBM quantum platforms (127–133 qubits) confirms practical feasibility for medium-scale systems with $M leq 16$ antennas, achieving 89.3% of ideal performance with 22% measurement success rate. Current hardware limitations restrict deployment to proof-of-concept demonstrations, with full-scale 6G implementations requiring quantum error correction projected for 2030 +.
6G网络的大规模MIMO波束形成面临着解决方案质量和计算复杂性之间的基本权衡。穷举搜索保证最佳天线选择；然而，对于超过16个元素的数组，这将变得非常昂贵，而多项式时间的经典启发式算法将牺牲15-25个元素% performance to achieve practical scalability. This paper introduces a quantum-enhanced optimization framework using the Quantum Approximate Optimization Algorithm (QAOA) to address this challenge for IoT-integrated 6G massive MIMO systems. Our approach combines quantum solution exploration with classical parameter optimization, integrating realistic 3GPP TR 38.901 channel models across 28–60 GHz bands and heterogeneous IoT device characteristics (mMTC, URLLC, eMBB). The framework incorporates an adaptive penalty mechanism that achieves constraint satisfaction within five iterations while maintaining polynomial complexity. Statistical validation across 50 independent channel realizations demonstrates significant advantages: 10–20% spectral efficiency improvement over classical heuristics ( $p lt 0.001$ , Cohen’s $d = 1.24$ ), 35–42% IoT energy reduction, and 90–95% near-optimal solution quality compared to 65–85% for polynomial-time classical methods. Hardware validation on IBM quantum platforms (127–133 qubits) confirms practical feasibility for medium-scale systems with $M leq 16$ antennas, achieving 89.3% of ideal performance with 22% measurement success rate. Current hardware limitations restrict deployment to proof-of-concept demonstrations, with full-scale 6G implementations requiring quantum error correction projected for 2030 +.
{"title":"Quantum-Enhanced Massive MIMO Beamforming for 6G IoT Networks: A QAOA-Based Optimization Framework","authors":"Iqra Batool;Mostafa M. Fouda;Muhammad Ismail;Mohamed I. Ibrahem;Zubair Md Fadlullah;Nei Kato","doi":"10.1109/OJCOMS.2025.3645207","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3645207","url":null,"abstract":"Massive MIMO beamforming for 6G networks faces a fundamental tradeoff between solution quality and computational complexity. Exhaustive search guarantees optimal antenna selection; however, this becomes prohibitively expensive for arrays exceeding 16 elements, while polynomial-time classical heuristics sacrifice 15–25% performance to achieve practical scalability. This paper introduces a quantum-enhanced optimization framework using the Quantum Approximate Optimization Algorithm (QAOA) to address this challenge for IoT-integrated 6G massive MIMO systems. Our approach combines quantum solution exploration with classical parameter optimization, integrating realistic 3GPP TR 38.901 channel models across 28–60 GHz bands and heterogeneous IoT device characteristics (mMTC, URLLC, eMBB). The framework incorporates an adaptive penalty mechanism that achieves constraint satisfaction within five iterations while maintaining polynomial complexity. Statistical validation across 50 independent channel realizations demonstrates significant advantages: 10–20% spectral efficiency improvement over classical heuristics (<inline-formula> <tex-math>$p lt 0.001$ </tex-math></inline-formula>, Cohen’s <inline-formula> <tex-math>$d = 1.24$ </tex-math></inline-formula>), 35–42% IoT energy reduction, and 90–95% near-optimal solution quality compared to 65–85% for polynomial-time classical methods. Hardware validation on IBM quantum platforms (127–133 qubits) confirms practical feasibility for medium-scale systems with <inline-formula> <tex-math>$M leq 16$ </tex-math></inline-formula> antennas, achieving 89.3% of ideal performance with 22% measurement success rate. Current hardware limitations restrict deployment to proof-of-concept demonstrations, with full-scale 6G implementations requiring quantum error correction projected for 2030 +.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"7 ","pages":"222-238"},"PeriodicalIF":6.3,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11303130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1109/OJCOMS.2025.3643949
Aicha Meghraoui;Mohamed L. Tayebi;Mokhtar Besseghier;Hossien B. Eldeeb;Tu Dac Ho;Van Nhan Vo;Iman Tavakkolnia;Harald Haas
This paper introduces a novel vehicle-to-vehicle (V2V) visible light communication (VLC) system leveraging the multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) framework to improve communication reliability and ensure user fairness under realistic outdoor conditions. The proposed system employs commercial headlamps as dual transmitters and two rear-mounted photodetectors (PDs) as receivers. To enable intensity modulation, we adopt direct-current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) technique, while a zero-force (ZF) detector separates spatial streams at the receiver. Power domain multiplexing utilizes normalized gain difference power allocation (NGDPA), and both perfect and imperfect successive interference cancellation (SIC) scenarios are investigated. For realistic modeling, a non-sequential ray-tracing channel model captures headlamp radiation patterns and environmental effects. A comprehensive evaluation of the system is conducted through the metrics of received power, achievable rate, bit error ratio (BER), and user fairness, considering the effect of key parameters including the size of the PD aperture, weather-induced attenuation, the bandwidth of the system, and artificial light interference. Results indicate that larger PD apertures significantly enhance BER performance, whereas increasing bandwidth tends to raise error rates. Moreover, the proposed system achieves up to 20% higher achievable rates compared to conventional OFDMA, particularly at high transmit power levels. Fairness indices of 0.99 and 0.94 are observed for perfect and imperfect SIC, respectively, confirming the framework’s ability to balance performance and fairness. These findings highlight the potential of the proposed NOMA-based techniques for next-generation intelligent vehicular networks.
{"title":"Performance Enhancement of MIMO-NOMA-Based V2V-VLC Systems Under Realistic Channel Conditions and Environmental Influences","authors":"Aicha Meghraoui;Mohamed L. Tayebi;Mokhtar Besseghier;Hossien B. Eldeeb;Tu Dac Ho;Van Nhan Vo;Iman Tavakkolnia;Harald Haas","doi":"10.1109/OJCOMS.2025.3643949","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3643949","url":null,"abstract":"This paper introduces a novel vehicle-to-vehicle (V2V) visible light communication (VLC) system leveraging the multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) framework to improve communication reliability and ensure user fairness under realistic outdoor conditions. The proposed system employs commercial headlamps as dual transmitters and two rear-mounted photodetectors (PDs) as receivers. To enable intensity modulation, we adopt direct-current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) technique, while a zero-force (ZF) detector separates spatial streams at the receiver. Power domain multiplexing utilizes normalized gain difference power allocation (NGDPA), and both perfect and imperfect successive interference cancellation (SIC) scenarios are investigated. For realistic modeling, a non-sequential ray-tracing channel model captures headlamp radiation patterns and environmental effects. A comprehensive evaluation of the system is conducted through the metrics of received power, achievable rate, bit error ratio (BER), and user fairness, considering the effect of key parameters including the size of the PD aperture, weather-induced attenuation, the bandwidth of the system, and artificial light interference. Results indicate that larger PD apertures significantly enhance BER performance, whereas increasing bandwidth tends to raise error rates. Moreover, the proposed system achieves up to 20% higher achievable rates compared to conventional OFDMA, particularly at high transmit power levels. Fairness indices of 0.99 and 0.94 are observed for perfect and imperfect SIC, respectively, confirming the framework’s ability to balance performance and fairness. These findings highlight the potential of the proposed NOMA-based techniques for next-generation intelligent vehicular networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10403-10418"},"PeriodicalIF":6.3,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11299596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1109/OJCOMS.2025.3644338
Xinyi Gu;Mohammad Rowshan;Jinhong Yuan
Convolutionally precoded polar codes known as polarization-adjusted convolutional (PAC) codes are a promising variant of polar codes for short block lengths. The precoding in PAC codes has demonstrated an effective reduction in the number of minimum weight codewords (a.k.a error coefficient) of polar codes. This reduction potentially improves the error correction performance significantly. From a codeword formation perspective, this reduction has limitations. Capitalizing on the understanding of the decomposition of minimum-weight codewords, this paper proposes a new coding scheme called reverse PAC (RPAC) codes that can effectively reduce minimum-weight codewords more than in PAC codes. Additionally, we propose a look-ahead list decoding for the RPAC codes, which maintains the same order of complexity as list decoding in PAC codes. Numerical results demonstrate that RPAC codes achieve significant improvements in block error rate over polar and PAC codes, especially in high-rate short-code scenarios where existing schemes are less effective.
{"title":"Reverse Convolutional Precoding of Polar Codes: Design, Analysis, and Decoding Algorithms","authors":"Xinyi Gu;Mohammad Rowshan;Jinhong Yuan","doi":"10.1109/OJCOMS.2025.3644338","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3644338","url":null,"abstract":"Convolutionally precoded polar codes known as polarization-adjusted convolutional (PAC) codes are a promising variant of polar codes for short block lengths. The precoding in PAC codes has demonstrated an effective reduction in the number of minimum weight codewords (a.k.a error coefficient) of polar codes. This reduction potentially improves the error correction performance significantly. From a codeword formation perspective, this reduction has limitations. Capitalizing on the understanding of the decomposition of minimum-weight codewords, this paper proposes a new coding scheme called reverse PAC (RPAC) codes that can effectively reduce minimum-weight codewords more than in PAC codes. Additionally, we propose a look-ahead list decoding for the RPAC codes, which maintains the same order of complexity as list decoding in PAC codes. Numerical results demonstrate that RPAC codes achieve significant improvements in block error rate over polar and PAC codes, especially in high-rate short-code scenarios where existing schemes are less effective.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"10567-10581"},"PeriodicalIF":6.3,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11300829","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：