In this article, we design and implement a multiantenna configured secure multiuser discrete Fourier transform (DFT)-Spread orthogonal frequency division multiplexing (OFDM) system based on frequency-domain spectrum shaping (FDSS) for reconfigurable intelligent surfaces (RISs) and unmanned aerial vehicle (UAV)-assisted terahertz (THz) communications. Our proposed simulated system highlights more suitable performance matrices for a typical case of three users for color image transmission. We introduced a six-dimensional hyperchaotic system-based encryption algorithm to enhance the physical layer security (PLS) of a UAV-to-ground communication network. In addition, the block diagonalization (BD) precoding technique reduces multiuser interference (MUI). Furthermore, we included repeat and accumulate (RA) channel coding with Cholesky decomposition-based zero-forcing (CD-ZF) and minimum mean square error (MMSE) signal detection schemes to improve the bit error rate (BER). We adopted the FDSS scheme and considered null carriers to reduce the out-of-band (OOB) spectrum power. The simulation results demonstrate the effectiveness of the proposed system in terms of PLS enhancement for color image transmission, with a low image structural similarity index of 0.65%, 1.60%, and 0.70% for users 1, 2, and 3, respectively; an achievable OOB power emission of 337 dB; and estimated peak-to-average power ratios (PAPRs) ranging from 7.10 to 7.85 dB at a complementary cumulative distribution function (CCDF) of $1times 10^{-4}$ for different ground-transmitting channels. At signal-to-noise ratios of 13.7, 9.4, and 7.5 dB, users 1, 2, and 3 achieve a BER of $1times 10^{-3}$ under RA channel coding, MMSE, and binary phase shift keying (BPSK) digital modulation.
{"title":"Transceiver Design of a Secure Multiuser FDSS-Based DFT-Spread OFDM System for RIS- and UAV-Assisted THz Communications","authors":"Md. Najmul Hossain;Kottakkaran Sooppy Nisar;Tetsuya Shimamura;Md. Rakibul Islam;Sk. Tamanna Kamal;Shaikh Enayet Ullah","doi":"10.1109/OJCOMS.2025.3526889","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526889","url":null,"abstract":"In this article, we design and implement a multiantenna configured secure multiuser discrete Fourier transform (DFT)-Spread orthogonal frequency division multiplexing (OFDM) system based on frequency-domain spectrum shaping (FDSS) for reconfigurable intelligent surfaces (RISs) and unmanned aerial vehicle (UAV)-assisted terahertz (THz) communications. Our proposed simulated system highlights more suitable performance matrices for a typical case of three users for color image transmission. We introduced a six-dimensional hyperchaotic system-based encryption algorithm to enhance the physical layer security (PLS) of a UAV-to-ground communication network. In addition, the block diagonalization (BD) precoding technique reduces multiuser interference (MUI). Furthermore, we included repeat and accumulate (RA) channel coding with Cholesky decomposition-based zero-forcing (CD-ZF) and minimum mean square error (MMSE) signal detection schemes to improve the bit error rate (BER). We adopted the FDSS scheme and considered null carriers to reduce the out-of-band (OOB) spectrum power. The simulation results demonstrate the effectiveness of the proposed system in terms of PLS enhancement for color image transmission, with a low image structural similarity index of 0.65%, 1.60%, and 0.70% for users 1, 2, and 3, respectively; an achievable OOB power emission of 337 dB; and estimated peak-to-average power ratios (PAPRs) ranging from 7.10 to 7.85 dB at a complementary cumulative distribution function (CCDF) of <inline-formula> <tex-math>$1times 10^{-4}$ </tex-math></inline-formula> for different ground-transmitting channels. At signal-to-noise ratios of 13.7, 9.4, and 7.5 dB, users 1, 2, and 3 achieve a BER of <inline-formula> <tex-math>$1times 10^{-3}$ </tex-math></inline-formula> under RA channel coding, MMSE, and binary phase shift keying (BPSK) digital modulation.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"708-726"},"PeriodicalIF":6.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993775","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 : 2025-01-06DOI: 10.1109/OJCOMS.2025.3526421
Vasileios Kouvakis;Stylianos E. Trevlakis;Alexandros-Apostolos A. Boulogeorgos;Hongwu Liu;Waqas Khalid;Theodoros A. Tsiftsis;Octavia A. Dobre
Demands for secure, ubiquitous, and always-available connectivity have been identified as the pillar design parameters of the next generation radio access networks (RANs). Motivated by this, the current contribution introduces a network architecture that leverages blockchain technologies to augment security in RANs, while enabling dynamic coverage expansion through the use of intermediate commercial or private wireless nodes. To assess the efficiency and limitations of the architecture, we employ Markov chain theory in order to extract a theoretical model with increased engineering insights. Building upon this model, we quantify the latency as well as the security capabilities in terms of probability of successful attack, for three scenarios, namely fixed topology fronthaul network, advanced coverage expansion and advanced mobile node connectivity, which reveal the scalability of the blockchain-RAN architecture.
{"title":"Hierarchical Blockchain Radio Access Networks: Architecture, Modelling, and Performance Assessment","authors":"Vasileios Kouvakis;Stylianos E. Trevlakis;Alexandros-Apostolos A. Boulogeorgos;Hongwu Liu;Waqas Khalid;Theodoros A. Tsiftsis;Octavia A. Dobre","doi":"10.1109/OJCOMS.2025.3526421","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526421","url":null,"abstract":"Demands for secure, ubiquitous, and always-available connectivity have been identified as the pillar design parameters of the next generation radio access networks (RANs). Motivated by this, the current contribution introduces a network architecture that leverages blockchain technologies to augment security in RANs, while enabling dynamic coverage expansion through the use of intermediate commercial or private wireless nodes. To assess the efficiency and limitations of the architecture, we employ Markov chain theory in order to extract a theoretical model with increased engineering insights. Building upon this model, we quantify the latency as well as the security capabilities in terms of probability of successful attack, for three scenarios, namely fixed topology fronthaul network, advanced coverage expansion and advanced mobile node connectivity, which reveal the scalability of the blockchain-RAN architecture.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"576-592"},"PeriodicalIF":6.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829652","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993671","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 : 2025-01-06DOI: 10.1109/OJCOMS.2025.3526759
Ghazal Asemian;Mohammadreza Amini;Burak Kantarci
The integration of Non-Orthogonal Multiple Access (NOMA) and Reconfigurable Intelligent Surfaces (RIS) significantly enhances 5G across a variety of technologies such as the Internet of Things (IoT), smart cities, and industrial automation. This work explores an active RIS-assisted NOMA uplink system aimed at mitigating jamming attacks while ensuring the reliability and latency requirements of ultra-reliable low-latency communication (URLLC) applications. We investigate the potential of RIS with active elements that adjust the phase and amplitude of the received signals for robust jamming mitigation. The study incorporates finite blocklength (FBL) and Automatic Repeat Request (ARQ) strategies to handle real-world complex configurations effectively. A thorough examination of various network parameters is conducted, including user transmit powers, active RIS elements amplitude, and the number of RIS elements. The paper utilizes the surrogate optimization technique, particularly the Radial Basis Function (RBF), to address the non-convex optimization problem minimizing the power consumption. The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. The findings emphasize the delicate balance required in optimizing network parameters. For instance, increasing the blocklength from 100 to 150 increases the reliability feasibility by 12.19%. The results demonstrate an optimal range for the amplitude value of active RIS elements $(2lt beta lt 15)$ . Exceeding this range results in over-amplification, high latency, and lower reliability, due to the interference related to NOMA cluster users. The deep regression model converges to a weighted mean square error (WMSE) of 10.6 for RIS with 25 elements and 15.8 for larger RIS size, highlighting the effectiveness of the deep regression model and RIS configuration’s importance.
{"title":"Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning","authors":"Ghazal Asemian;Mohammadreza Amini;Burak Kantarci","doi":"10.1109/OJCOMS.2025.3526759","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526759","url":null,"abstract":"The integration of Non-Orthogonal Multiple Access (NOMA) and Reconfigurable Intelligent Surfaces (RIS) significantly enhances 5G across a variety of technologies such as the Internet of Things (IoT), smart cities, and industrial automation. This work explores an active RIS-assisted NOMA uplink system aimed at mitigating jamming attacks while ensuring the reliability and latency requirements of ultra-reliable low-latency communication (URLLC) applications. We investigate the potential of RIS with active elements that adjust the phase and amplitude of the received signals for robust jamming mitigation. The study incorporates finite blocklength (FBL) and Automatic Repeat Request (ARQ) strategies to handle real-world complex configurations effectively. A thorough examination of various network parameters is conducted, including user transmit powers, active RIS elements amplitude, and the number of RIS elements. The paper utilizes the surrogate optimization technique, particularly the Radial Basis Function (RBF), to address the non-convex optimization problem minimizing the power consumption. The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. The findings emphasize the delicate balance required in optimizing network parameters. For instance, increasing the blocklength from 100 to 150 increases the reliability feasibility by 12.19%. The results demonstrate an optimal range for the amplitude value of active RIS elements <inline-formula> <tex-math>$(2lt beta lt 15)$ </tex-math></inline-formula>. Exceeding this range results in over-amplification, high latency, and lower reliability, due to the interference related to NOMA cluster users. The deep regression model converges to a weighted mean square error (WMSE) of 10.6 for RIS with 25 elements and 15.8 for larger RIS size, highlighting the effectiveness of the deep regression model and RIS configuration’s importance.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"690-707"},"PeriodicalIF":6.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829864","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993774","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 : 2025-01-03DOI: 10.1109/OJCOMS.2025.3525468
Ferdaous Tarhouni;Ruibo Wang;Mohamed-Slim Alouini
Free space optical (FSO) communication, known for its high data rates and immunity to electromagnetic interference, encounters challenges such as weather dependency, misalignment issues, and line-of-sight (LoS) requirements. Mesh networks, with their inherent scalability and redundancy, can mitigate these limitations by providing multiple pathways for data transmission and robust network configurations. This paper investigates the key motivations for integrating FSO transmission within mesh structures. We review existing literature on both FSO and hybrid RF/FSO mesh networks, discussing technical studies aimed at maximizing network performance and minimizing delay and cost deployments. We equally explore some relaying approaches in FSO mesh networks and shed light on the advantages of some relaying solutions, mainly, flying platforms and reconfigurable intelligent surfaces (RIS). We discuss the use of FSO in satellite communication to establish two types of mesh networks: inter-satellite and satellite-aerial/ground mesh networks. Finally, some open issues and future research directions are explored.
{"title":"Free Space Optical Mesh Networks: A Survey","authors":"Ferdaous Tarhouni;Ruibo Wang;Mohamed-Slim Alouini","doi":"10.1109/OJCOMS.2025.3525468","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525468","url":null,"abstract":"Free space optical (FSO) communication, known for its high data rates and immunity to electromagnetic interference, encounters challenges such as weather dependency, misalignment issues, and line-of-sight (LoS) requirements. Mesh networks, with their inherent scalability and redundancy, can mitigate these limitations by providing multiple pathways for data transmission and robust network configurations. This paper investigates the key motivations for integrating FSO transmission within mesh structures. We review existing literature on both FSO and hybrid RF/FSO mesh networks, discussing technical studies aimed at maximizing network performance and minimizing delay and cost deployments. We equally explore some relaying approaches in FSO mesh networks and shed light on the advantages of some relaying solutions, mainly, flying platforms and reconfigurable intelligent surfaces (RIS). We discuss the use of FSO in satellite communication to establish two types of mesh networks: inter-satellite and satellite-aerial/ground mesh networks. Finally, some open issues and future research directions are explored.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"642-655"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10821003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993773","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 : 2025-01-03DOI: 10.1109/OJCOMS.2025.3525954
Usman Ali;Luca De Nardis;Maria-Gabriella Di Benedetto
The performance of Space Division Multiple Access (SDMA) in Multiuser Multiple Input Single Output (MU-MISO) systems degrades significantly under imperfect Channel State Information at the Transmitter (CSIT). To address this, Rate-Splitting Multiple Access (RSMA) has been shown to outperform SDMA in scenarios where CSIT is imperfect, particularly in underloaded scenarios, where the number of potential users is lower than the number of antennas. This paper investigates the use of RSMA in a large-scale, overloaded system, where the number of users exceeds the number of antennas at the base station. We propose a novel approximation of the RSMA sum rate under limited feedback conditions and develop an optimal power allocation strategy that dynamically switches between RSMA and SDMA to maximize energy efficiency and system performance. Additionally, a robust Minimum Mean Square Error (MMSE) based precoding method is introduced to mitigate the effects of imperfect CSIT in private streams of RSMA. Numerical simulations validate our analytical derivations and show that RSMA offers superior performance over SDMA in large user regimes with low feedback loads, providing significant performance gains in realistic network conditions. These findings offer new insights into the design of energy-efficient and scalable downlink communication systems for future wireless networks.
{"title":"Energy Efficiency and Fairness in Large Scale Systems Using RSMA","authors":"Usman Ali;Luca De Nardis;Maria-Gabriella Di Benedetto","doi":"10.1109/OJCOMS.2025.3525954","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525954","url":null,"abstract":"The performance of Space Division Multiple Access (SDMA) in Multiuser Multiple Input Single Output (MU-MISO) systems degrades significantly under imperfect Channel State Information at the Transmitter (CSIT). To address this, Rate-Splitting Multiple Access (RSMA) has been shown to outperform SDMA in scenarios where CSIT is imperfect, particularly in underloaded scenarios, where the number of potential users is lower than the number of antennas. This paper investigates the use of RSMA in a large-scale, overloaded system, where the number of users exceeds the number of antennas at the base station. We propose a novel approximation of the RSMA sum rate under limited feedback conditions and develop an optimal power allocation strategy that dynamically switches between RSMA and SDMA to maximize energy efficiency and system performance. Additionally, a robust Minimum Mean Square Error (MMSE) based precoding method is introduced to mitigate the effects of imperfect CSIT in private streams of RSMA. Numerical simulations validate our analytical derivations and show that RSMA offers superior performance over SDMA in large user regimes with low feedback loads, providing significant performance gains in realistic network conditions. These findings offer new insights into the design of energy-efficient and scalable downlink communication systems for future wireless networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"611-628"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824841","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993666","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 : 2025-01-03DOI: 10.1109/OJCOMS.2025.3525506
Chuan-Wei Cho;Meng-Shiuan Pan
The integrated access and backhaul (IAB) architecture utilizes wireless backhaul to facilitate the expansion of fifth-generation (5G) New Radio (NR) networks. In an IAB network, intermediate base stations (or say IAB nodes) can be connected in a multi-hop fashion. However, optimizing resource scheduling in such a network remains a critical challenge. In this work, we present a novel method that integrates multi-user multiple-input and multiple-output (MU-MIMO) and non-orthogonal multiple access (NOMA) technologies into IAB networks. The designed two-phase algorithm has the following features: 1) support for multi-path routing and efficient resource utilization through the combined use of MU-MIMO and NOMA, 2) a novel route decision phase that selects optimal paths by considering load balancing among IAB nodes, and 3) a dynamic link scheduling phase that allocates transmission power and schedules links to maximize network capacity. Simulation results demonstrate that the proposed solution achieves significant improvements in throughput, fairness, and latency compared to existing methods.
{"title":"Resource Scheduling in MU-MIMO and NOMA Enabled Integrated Access and Backhaul Networks","authors":"Chuan-Wei Cho;Meng-Shiuan Pan","doi":"10.1109/OJCOMS.2025.3525506","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525506","url":null,"abstract":"The integrated access and backhaul (IAB) architecture utilizes wireless backhaul to facilitate the expansion of fifth-generation (5G) New Radio (NR) networks. In an IAB network, intermediate base stations (or say IAB nodes) can be connected in a multi-hop fashion. However, optimizing resource scheduling in such a network remains a critical challenge. In this work, we present a novel method that integrates multi-user multiple-input and multiple-output (MU-MIMO) and non-orthogonal multiple access (NOMA) technologies into IAB networks. The designed two-phase algorithm has the following features: 1) support for multi-path routing and efficient resource utilization through the combined use of MU-MIMO and NOMA, 2) a novel route decision phase that selects optimal paths by considering load balancing among IAB nodes, and 3) a dynamic link scheduling phase that allocates transmission power and schedules links to maximize network capacity. Simulation results demonstrate that the proposed solution achieves significant improvements in throughput, fairness, and latency compared to existing methods.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"551-559"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820963","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993776","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}
A novel technology based on stacked intelligent metasurfaces (SIM) has recently emerged. This platform involves cascading multiple metasurfaces, each acting as a digitally programmable physical layer within a diffractive neural network. SIM enable the implementation of signal-processing transformations directly in the electromagnetic wave domain, eliminating the need for expensive, high-precision, and power-intensive digital platforms. However, existing studies employing SIM in wireless communication applications rely solely on nearly passive structures that control only the phase of the meta-atoms in each layer. In this study, we propose a SIM-aided downlink multiuser transmission scheme, where the SIM at the base station (BS) end is designed by combining nearly passive layers with phase-only reconfiguration capabilities and active layers integrated with amplifier chips to enable amplitude control. Our optimal design aims at maximizing the sum rate for the best group of users by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM. In addition to the standard sum-power constraint at the BS, our optimization framework includes two additional constraints: (i) a per-stream power preserving constraint to prevent propagation losses across the SIM, and (ii) an amplitude constraint to account for power limitations for each active layer. To further reduce the complexity of the optimal beamforming solution, we explore a simple yet suboptimal zero-forcing (ZF) beamforming design, where the wave-based transformation implemented by the SIM is selected to eliminate interference among user streams. Finally, extensive Monte Carlo simulations demonstrate that incorporating both nearly passive and active layers within the SIM significantly enhances capacity compared to previously reported phase-only coding SIM. Additionally, the numerical results reveal that low-complexity ZF beamforming approaches optimality in terms of maximum sum rate even for a relatively small number of users.
{"title":"Design of Stacked Intelligent Metasurfaces With Reconfigurable Amplitude and Phase for Multiuser Downlink Beamforming","authors":"Donatella Darsena;Francesco Verde;Ivan Iudice;Vincenzo Galdi","doi":"10.1109/OJCOMS.2025.3526126","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526126","url":null,"abstract":"A novel technology based on stacked intelligent metasurfaces (SIM) has recently emerged. This platform involves cascading multiple metasurfaces, each acting as a digitally programmable physical layer within a diffractive neural network. SIM enable the implementation of signal-processing transformations directly in the electromagnetic wave domain, eliminating the need for expensive, high-precision, and power-intensive digital platforms. However, existing studies employing SIM in wireless communication applications rely solely on nearly passive structures that control only the phase of the meta-atoms in each layer. In this study, we propose a SIM-aided downlink multiuser transmission scheme, where the SIM at the base station (BS) end is designed by combining nearly passive layers with phase-only reconfiguration capabilities and active layers integrated with amplifier chips to enable amplitude control. Our optimal design aims at maximizing the sum rate for the best group of users by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM. In addition to the standard sum-power constraint at the BS, our optimization framework includes two additional constraints: (i) a per-stream power preserving constraint to prevent propagation losses across the SIM, and (ii) an amplitude constraint to account for power limitations for each active layer. To further reduce the complexity of the optimal beamforming solution, we explore a simple yet suboptimal zero-forcing (ZF) beamforming design, where the wave-based transformation implemented by the SIM is selected to eliminate interference among user streams. Finally, extensive Monte Carlo simulations demonstrate that incorporating both nearly passive and active layers within the SIM significantly enhances capacity compared to previously reported phase-only coding SIM. Additionally, the numerical results reveal that low-complexity ZF beamforming approaches optimality in terms of maximum sum rate even for a relatively small number of users.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"531-550"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993667","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 : 2025-01-01DOI: 10.1109/OJCOMS.2024.3523518
Mehmood Ul Hassan;Yawar Abbas Bangash;Waseem Iqbal;Abdellah Chehri;Javed Iqbal
The metaverse is a new virtual world that has the potential to significantly impact our interactions with digital content and with each other. It is a shared virtual environment where users can seamlessly and with immersive experiences create, interact, and enjoy digital assets. Nevertheless, the metaverse also poses fundamental challenges, particularly about security and privacy concerns, that require careful consideration. One of the most daunting aspects of securing the metaverse is authentication. Several solutions have been proposed, including deployment of blockchain technology and smart contracts, to address these authentication challenges. While these methods provide a secure and tamper-proof authentication mechanism, they fail to meet certain critical security and privacy requirements like interoperability and decentralization. This research proposes an enhanced privacy-preserving authentication scheme based on blockchain, elliptic curve cryptography, biohashing, and a physical unclonable function that guards against various attacks. The proposed scheme does not rely on a single central authority and consists of various phases, including user and avatar authentication, password change, and avatar generation phases. The proposed scheme underwent security assessment using the Burrows Abadi Needham (BAN) logic, ProVerif tool, and Scyther tool. The results demonstrate that it provides a better level of security against a wide range of attack vectors. The proposed scheme offers a swift and efficient authentication mechanism that adheres to the requirements of the metaverse environment, such as interoperability, decentralization, and privacy protection, and requires less computation cost as compared to state-of-the-art schemes.
{"title":"PRIDA-ME: A Privacy-Preserving, Interoperable and Decentralized Authentication Scheme for Metaverse Environment","authors":"Mehmood Ul Hassan;Yawar Abbas Bangash;Waseem Iqbal;Abdellah Chehri;Javed Iqbal","doi":"10.1109/OJCOMS.2024.3523518","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3523518","url":null,"abstract":"The metaverse is a new virtual world that has the potential to significantly impact our interactions with digital content and with each other. It is a shared virtual environment where users can seamlessly and with immersive experiences create, interact, and enjoy digital assets. Nevertheless, the metaverse also poses fundamental challenges, particularly about security and privacy concerns, that require careful consideration. One of the most daunting aspects of securing the metaverse is authentication. Several solutions have been proposed, including deployment of blockchain technology and smart contracts, to address these authentication challenges. While these methods provide a secure and tamper-proof authentication mechanism, they fail to meet certain critical security and privacy requirements like interoperability and decentralization. This research proposes an enhanced privacy-preserving authentication scheme based on blockchain, elliptic curve cryptography, biohashing, and a physical unclonable function that guards against various attacks. The proposed scheme does not rely on a single central authority and consists of various phases, including user and avatar authentication, password change, and avatar generation phases. The proposed scheme underwent security assessment using the Burrows Abadi Needham (BAN) logic, ProVerif tool, and Scyther tool. The results demonstrate that it provides a better level of security against a wide range of attack vectors. The proposed scheme offers a swift and efficient authentication mechanism that adheres to the requirements of the metaverse environment, such as interoperability, decentralization, and privacy protection, and requires less computation cost as compared to state-of-the-art schemes.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"493-515"},"PeriodicalIF":6.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10819498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938456","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}
While the application of deep neural networks (DNNs) for channel decoding is a well-researched topic, most studies focus on hard output decoding, potentially restricting the practical application of such decoders in real communication systems. Modern receivers require iterative decoders, a pivotal criterion for which is the ability to produce soft output. In this paper, we focus on this property. We begin by modifying the syndrome-based DNN-decoding approach proposed by Bennatan et al. (2018). The DNN model is trained to provide soft output and replicate the maximum a posteriori probability decoder. To assess the quality of the proposed decoder’s soft output, we examine the iterative decoding method, specifically the turbo product code (TPC) with extended BCH (eBCH) codes as its component codes. A sequential training procedure for optimizing the behavior of component decoders is utilized. We illustrate that the described approach achieves exceptional performance results and is applicable for iterative codes with larger code lengths $[n=4096, k=2025]$ , compared to state-of-the-art DNN-based methods. Finally, we address the issues of computational complexity and memory requirements of DNN-based decoding by analyzing the model’s compression limits through pruning and matrix decomposition methods.
{"title":"Iterative Syndrome-Based Deep Neural Network Decoding","authors":"Dmitry Artemasov;Kirill Andreev;Pavel Rybin;Alexey Frolov","doi":"10.1109/OJCOMS.2024.3524429","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3524429","url":null,"abstract":"While the application of deep neural networks (DNNs) for channel decoding is a well-researched topic, most studies focus on hard output decoding, potentially restricting the practical application of such decoders in real communication systems. Modern receivers require iterative decoders, a pivotal criterion for which is the ability to produce soft output. In this paper, we focus on this property. We begin by modifying the syndrome-based DNN-decoding approach proposed by Bennatan et al. (2018). The DNN model is trained to provide soft output and replicate the maximum a posteriori probability decoder. To assess the quality of the proposed decoder’s soft output, we examine the iterative decoding method, specifically the turbo product code (TPC) with extended BCH (eBCH) codes as its component codes. A sequential training procedure for optimizing the behavior of component decoders is utilized. We illustrate that the described approach achieves exceptional performance results and is applicable for iterative codes with larger code lengths <inline-formula> <tex-math>$[n=4096, k=2025]$ </tex-math></inline-formula>, compared to state-of-the-art DNN-based methods. Finally, we address the issues of computational complexity and memory requirements of DNN-based decoding by analyzing the model’s compression limits through pruning and matrix decomposition methods.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"629-641"},"PeriodicalIF":6.3,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993592","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 : 2024-12-30DOI: 10.1109/OJCOMS.2024.3523797
Mostafa Naseri;Eli De Poorter;Ingrid Moerman;H. Vincent Poor;Adnan Shahid
Co-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improvement to this approach is adaptive CCI, which reduces interference without relying on prior knowledge of the interfering signal characteristics. Recent work suggested using machine learning (ML) models for this purpose, but high-throughput ML solutions are still lacking, especially for edge devices with limited resources. This work explores the adaptation of U-Net Convolutional Neural Network models for high-throughput adaptive source separation. Our approach is established on architectural modifications, notably through quantization and the incorporation of depthwise separable convolution, to achieve a balance between computational efficiency and performance. Our results demonstrate that the proposed models achieve superior MSE scores when removing unknown interference sources from the signals while maintaining significantly lower computational complexity compared to baseline models. One of our proposed models is deeper and fully convolutional, while the other is shallower with a convolutional structure incorporating an LSTM. Depthwise separable convolution and quantization further reduce the memory footprint and computational demands, albeit with some performance tradeoffs. Specifically, applying depthwise separable convolutions to the model with the LSTM results in only a 0.72% degradation in MSE score while reducing MACs by 58.66%. For the fully convolutional model, we observe a 0.63% improvement in MSE score with even 61.10% fewer MACs. Additionally, the models exhibit excellent scalability on GPUs, with the fully convolutional model achieving the highest symbol rates (up to 800$times$ 103 symbol per second) at larger batch sizes. Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.
{"title":"High-Throughput Adaptive Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning","authors":"Mostafa Naseri;Eli De Poorter;Ingrid Moerman;H. Vincent Poor;Adnan Shahid","doi":"10.1109/OJCOMS.2024.3523797","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3523797","url":null,"abstract":"Co-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improvement to this approach is adaptive CCI, which reduces interference without relying on prior knowledge of the interfering signal characteristics. Recent work suggested using machine learning (ML) models for this purpose, but high-throughput ML solutions are still lacking, especially for edge devices with limited resources. This work explores the adaptation of U-Net Convolutional Neural Network models for high-throughput adaptive source separation. Our approach is established on architectural modifications, notably through quantization and the incorporation of depthwise separable convolution, to achieve a balance between computational efficiency and performance. Our results demonstrate that the proposed models achieve superior MSE scores when removing unknown interference sources from the signals while maintaining significantly lower computational complexity compared to baseline models. One of our proposed models is deeper and fully convolutional, while the other is shallower with a convolutional structure incorporating an LSTM. Depthwise separable convolution and quantization further reduce the memory footprint and computational demands, albeit with some performance tradeoffs. Specifically, applying depthwise separable convolutions to the model with the LSTM results in only a 0.72% degradation in MSE score while reducing MACs by 58.66%. For the fully convolutional model, we observe a 0.63% improvement in MSE score with even 61.10% fewer MACs. Additionally, the models exhibit excellent scalability on GPUs, with the fully convolutional model achieving the highest symbol rates (up to 800<inline-formula> <tex-math>$times$ </tex-math></inline-formula>103 symbol per second) at larger batch sizes. Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"656-670"},"PeriodicalIF":6.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993669","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}
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