Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial networks with terrestrial wireless systems, are vital enablers of the emerging sixth-generation (6G) wireless networks. They offer significant benefits, including extending high-speed broadband coverage to remote and hard-to-reach areas. However, due to constraints like limited power and storage resources, SAGINs must be intelligently configured and managed to meet their envisioned requirements. Meanwhile, Artificial Intelligence (AI) is another critical enabler of 6G. Due to the recent advancements in AI techniques and hardware capabilities, AI has been leveraged to address the pressing challenges of current and future wireless networks. By adding AI and facilitating the decision-making and prediction procedures, SAGINs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics. In this work, we aim to investigate the interplay of AI and SAGINs by providing a holistic overview of state-of-the-art research in AI-enabled SAGINs. Specifically, we present a comprehensive overview of some potential applications of AI in SAGINs. We also cover open issues in employing AI and detail the contributions of SAGINs in developing AI. Finally, we highlight some limitations of the existing research works and outline potential future research directions.
{"title":"On the Interplay of Artificial Intelligence and Space-Air-Ground Integrated Networks: A Survey","authors":"Adilya Bakambekova;Nour Kouzayha;Tareq Al-Naffouri","doi":"10.1109/OJCOMS.2024.3429198","DOIUrl":"10.1109/OJCOMS.2024.3429198","url":null,"abstract":"Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial networks with terrestrial wireless systems, are vital enablers of the emerging sixth-generation (6G) wireless networks. They offer significant benefits, including extending high-speed broadband coverage to remote and hard-to-reach areas. However, due to constraints like limited power and storage resources, SAGINs must be intelligently configured and managed to meet their envisioned requirements. Meanwhile, Artificial Intelligence (AI) is another critical enabler of 6G. Due to the recent advancements in AI techniques and hardware capabilities, AI has been leveraged to address the pressing challenges of current and future wireless networks. By adding AI and facilitating the decision-making and prediction procedures, SAGINs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics. In this work, we aim to investigate the interplay of AI and SAGINs by providing a holistic overview of state-of-the-art research in AI-enabled SAGINs. Specifically, we present a comprehensive overview of some potential applications of AI in SAGINs. We also cover open issues in employing AI and detail the contributions of SAGINs in developing AI. Finally, we highlight some limitations of the existing research works and outline potential future research directions.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599519","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721574","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 : 2024-07-16DOI: 10.1109/OJCOMS.2024.3429284
Bishoy Salama Attia;Aamen Elgharably;Mariam Nabil Aboelwafa;Ghada Alsuhli;Karim Banawan;Karim G. Seddik
We consider the problem of jointly enhancing the network throughput, minimizing energy consumption, and improving the network coverage of mobile networks. The problem is cast as a reinforcement learning (RL) problem. The reward function accounts for the joint optimization of throughput, energy consumption, and coverage (through the number of uncovered users); our RL framework allows the network operator to assign weights to each of these cost functions based on the operator’s preferences. Moreover, the state is defined by key performance indicators (KPIs) that are readily available on the network operator side. Finally, the action space for the RL agent comprises a hybrid action space, where we have two continuous action elements, namely, cell individual offsets (CIOs) and transmission powers, and one discrete action element, which is switching MIMO ON and OFF. To that end, we propose a new layered RL agent structure to account for the agent hybrid space. We test our proposed RL agent over two scenarios: a simple (proof of concept) scenario and a realistic network scenario. Our results show significant performance gains of the proposed RL agent compared to baseline approaches, such as systems without optimization or RL agents that optimize only one or two parameters.”
{"title":"Self-Optimized Agent for Load Balancing and Energy Efficiency: A Reinforcement Learning Framework With Hybrid Action Space","authors":"Bishoy Salama Attia;Aamen Elgharably;Mariam Nabil Aboelwafa;Ghada Alsuhli;Karim Banawan;Karim G. Seddik","doi":"10.1109/OJCOMS.2024.3429284","DOIUrl":"10.1109/OJCOMS.2024.3429284","url":null,"abstract":"We consider the problem of jointly enhancing the network throughput, minimizing energy consumption, and improving the network coverage of mobile networks. The problem is cast as a reinforcement learning (RL) problem. The reward function accounts for the joint optimization of throughput, energy consumption, and coverage (through the number of uncovered users); our RL framework allows the network operator to assign weights to each of these cost functions based on the operator’s preferences. Moreover, the state is defined by key performance indicators (KPIs) that are readily available on the network operator side. Finally, the action space for the RL agent comprises a hybrid action space, where we have two continuous action elements, namely, cell individual offsets (CIOs) and transmission powers, and one discrete action element, which is switching MIMO ON and OFF. To that end, we propose a new layered RL agent structure to account for the agent hybrid space. We test our proposed RL agent over two scenarios: a simple (proof of concept) scenario and a realistic network scenario. Our results show significant performance gains of the proposed RL agent compared to baseline approaches, such as systems without optimization or RL agents that optimize only one or two parameters.”","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721569","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 : 2024-07-16DOI: 10.1109/OJCOMS.2024.3428925
Muhammad Nafees;Shenjie Huang;John Thompson;Majid Safari
Future networks are expected to make substantial use of unmanned aerial vehicles (UAVs) as aerial base stations (BSs). The backhauling of UAVs is often considered with license-free and highbandwidth free-space optical (FSO) communication. Employing UAVs and FSO technology together is appropriate for numerous applications such as user offloading, network capacity enhancement, and relaying services. However, the reliability of the backhaul FSO link can be jeopardized by infrequent adverse weather conditions such as fog. In this study, we proposed the capacity enhancement of a ground BS (GBS) with the aid of an FSO-backhualed UAV aerial BS. In particular, we optimize the UAV’s circular trajectory and parameters (i.e., coverage radius and beamwidth) to maximize the total network throughput during both normal and adverse weather (e.g., fog events). Two trajectories, namely rate maximization (RMT) and fairness-constrained rate maximization (FRMT), are considered. A novel expression for the average capacity of the FSO backhaul over the entire trajectory is derived. The formulated problem aims to maximize the average network throughput with constraints pertaining to backhaul capacity, network fairness, and UAV parameters. It is shown that the UAV changes its trajectory using its coverage radius and directional antenna beamwidth according to the weather conditions and fairness requirements to maximize the total system capacity. Furthermore, real weather data from the cities of Edinburgh and London in the U.K. is used to evaluate the performance of the system under low-visibility conditions. The numerical results show the proposed FSO-backhauled UAV can provide significant capacity enhancement even in thin, light, and moderately foggy conditions.
{"title":"Backhaul-Aware UAV-Aided Capacity Enhancement in Mixed FSO-RF Network","authors":"Muhammad Nafees;Shenjie Huang;John Thompson;Majid Safari","doi":"10.1109/OJCOMS.2024.3428925","DOIUrl":"10.1109/OJCOMS.2024.3428925","url":null,"abstract":"Future networks are expected to make substantial use of unmanned aerial vehicles (UAVs) as aerial base stations (BSs). The backhauling of UAVs is often considered with license-free and highbandwidth free-space optical (FSO) communication. Employing UAVs and FSO technology together is appropriate for numerous applications such as user offloading, network capacity enhancement, and relaying services. However, the reliability of the backhaul FSO link can be jeopardized by infrequent adverse weather conditions such as fog. In this study, we proposed the capacity enhancement of a ground BS (GBS) with the aid of an FSO-backhualed UAV aerial BS. In particular, we optimize the UAV’s circular trajectory and parameters (i.e., coverage radius and beamwidth) to maximize the total network throughput during both normal and adverse weather (e.g., fog events). Two trajectories, namely rate maximization (RMT) and fairness-constrained rate maximization (FRMT), are considered. A novel expression for the average capacity of the FSO backhaul over the entire trajectory is derived. The formulated problem aims to maximize the average network throughput with constraints pertaining to backhaul capacity, network fairness, and UAV parameters. It is shown that the UAV changes its trajectory using its coverage radius and directional antenna beamwidth according to the weather conditions and fairness requirements to maximize the total system capacity. Furthermore, real weather data from the cities of Edinburgh and London in the U.K. is used to evaluate the performance of the system under low-visibility conditions. The numerical results show the proposed FSO-backhauled UAV can provide significant capacity enhancement even in thin, light, and moderately foggy conditions.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721570","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 : 2024-07-16DOI: 10.1109/OJCOMS.2024.3429151
Vinay Kumar Chapala;S. M. Zafaruddin
Existing performance analysis of wireless systems based on reconfigurable intelligent surfaces (RIS) over fading channels has primarily focused on providing statistical insights into the sum and product of random variables, typically represented as a single-variate Fox-H function. A research gap exists for an exact performance analysis when the statistical characterization of wireless systems, including RIS-assisted systems, requires more than a single-variate Fox-H function. In such cases, incorporating a multivariate representation becomes imperative, particularly when addressing generalized fading models and channel estimation errors, even with simpler one-parameter fading models. This paper introduces a novel approach to derive the distribution of the sum and product of independent and nonidentical distributed (i.ni.d) random variables characterized by the multivariate Fox-H function. We also establish a general framework for an exact analysis of ergodic capacity and average signal-to-noise ratio (SNR) when the multivariate Fox-H function describes the statistics of the channel. Applying the derived results, we conduct an exact performance analysis of outage probability and ergodic capacity, exemplified by RIS-assisted communication over Rician fading channels with imperfect phase compensation and channel estimation errors. Computer simulations validate the exact analysis and illustrate the performance of the RIS-assisted system under various practically relevant scenarios, enhancing the overall performance assessment.
{"title":"Sum and Product of Multivariate Fox-H Functions: Exact Analysis for RIS-Assisted System Over Rician Fading With Imperfect CSI","authors":"Vinay Kumar Chapala;S. M. Zafaruddin","doi":"10.1109/OJCOMS.2024.3429151","DOIUrl":"10.1109/OJCOMS.2024.3429151","url":null,"abstract":"Existing performance analysis of wireless systems based on reconfigurable intelligent surfaces (RIS) over fading channels has primarily focused on providing statistical insights into the sum and product of random variables, typically represented as a single-variate Fox-H function. A research gap exists for an exact performance analysis when the statistical characterization of wireless systems, including RIS-assisted systems, requires more than a single-variate Fox-H function. In such cases, incorporating a multivariate representation becomes imperative, particularly when addressing generalized fading models and channel estimation errors, even with simpler one-parameter fading models. This paper introduces a novel approach to derive the distribution of the sum and product of independent and nonidentical distributed (i.ni.d) random variables characterized by the multivariate Fox-H function. We also establish a general framework for an exact analysis of ergodic capacity and average signal-to-noise ratio (SNR) when the multivariate Fox-H function describes the statistics of the channel. Applying the derived results, we conduct an exact performance analysis of outage probability and ergodic capacity, exemplified by RIS-assisted communication over Rician fading channels with imperfect phase compensation and channel estimation errors. Computer simulations validate the exact analysis and illustrate the performance of the RIS-assisted system under various practically relevant scenarios, enhancing the overall performance assessment.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599556","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721572","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 : 2024-07-15DOI: 10.1109/ojcoms.2024.3427628
Si-Yu Zhang, Xinwei Yue, Behnam Shahrrava, Yuexia Zhang, Gongpu Wang
{"title":"A Polar-Coded PAPR Reduction Scheme Based On Hybrid Index Modulation","authors":"Si-Yu Zhang, Xinwei Yue, Behnam Shahrrava, Yuexia Zhang, Gongpu Wang","doi":"10.1109/ojcoms.2024.3427628","DOIUrl":"https://doi.org/10.1109/ojcoms.2024.3427628","url":null,"abstract":"","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":7.9,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-15DOI: 10.1109/OJCOMS.2024.3427639
Elvan Kuzucu Hidir;Ertugrul Basar;Hakan Ali Cirpan
Beyond fifth-generation (5G) wireless communication, reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology that can redefine how we interact with and harness electromagnetic waves. Advancements in meta-materials and metasurfaces have brought about exceptional flexibility in controlling electromagnetic waves at scales smaller than the wavelength. The frequency-mixing RIS (FMx-RIS) has been introduced, considering the benefits of programmable metasurfaces. This method introduces additional frequencies into the original signal, making the communication environment non-linear. Among the different multicarrier transmission methods, orthogonal frequency division multiplexing (OFDM) has become the most commonly used option in wireless communications due to reducing intersymbol interference caused by the frequency selectivity of wireless channels. Upon examining the structure of FMx-RIS, it has been observed that signals similar to OFDM can be obtained at the receiver. This situation indicates the possibility of generating a signal in the air similar to OFDM using an RIS. Therefore, in this study, we propose a novel Over-the-Air OFDM system design by integrating frequency mixing and modulating RIS (FMMx-RIS) to exploit its ability to manipulate the incident wave’s magnitude and frequency. The most notable aspect of this innovative scheme is its ability to offer multi-carrier transmission with a straightforward transmitter structure rather than requiring the complex system design typical of OFDM. The novel concept of index modulation (IM), which leverages the spatial domain to transmit extra information more efficiently, enhancing energy and spectrum efficiency, has attracted considerable interest in both academic and industrial fields. Hence, we extend the system model into the Over-the-Air OFDM-IM system by toggling frequency-changing RIS on and off. Furthermore, we analytically assess the average bit error probability (ABEP) of the proposed Over-the-Air OFDM-IM system using the maximum likelihood (ML) decoder. Subsequently, we present comprehensive computer simulation results to demonstrate the significant improvement in bit error rate (BER) performance of the proposed Over-the-Air OFDM-IM system compared to reference systems employing RIS-aided OFDM.
{"title":"Over-the-Air OFDM-IM Through Frequency Mixing and Modulating Reconfigurable Intelligent Surfaces","authors":"Elvan Kuzucu Hidir;Ertugrul Basar;Hakan Ali Cirpan","doi":"10.1109/OJCOMS.2024.3427639","DOIUrl":"10.1109/OJCOMS.2024.3427639","url":null,"abstract":"Beyond fifth-generation (5G) wireless communication, reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology that can redefine how we interact with and harness electromagnetic waves. Advancements in meta-materials and metasurfaces have brought about exceptional flexibility in controlling electromagnetic waves at scales smaller than the wavelength. The frequency-mixing RIS (FMx-RIS) has been introduced, considering the benefits of programmable metasurfaces. This method introduces additional frequencies into the original signal, making the communication environment non-linear. Among the different multicarrier transmission methods, orthogonal frequency division multiplexing (OFDM) has become the most commonly used option in wireless communications due to reducing intersymbol interference caused by the frequency selectivity of wireless channels. Upon examining the structure of FMx-RIS, it has been observed that signals similar to OFDM can be obtained at the receiver. This situation indicates the possibility of generating a signal in the air similar to OFDM using an RIS. Therefore, in this study, we propose a novel Over-the-Air OFDM system design by integrating frequency mixing and modulating RIS (FMMx-RIS) to exploit its ability to manipulate the incident wave’s magnitude and frequency. The most notable aspect of this innovative scheme is its ability to offer multi-carrier transmission with a straightforward transmitter structure rather than requiring the complex system design typical of OFDM. The novel concept of index modulation (IM), which leverages the spatial domain to transmit extra information more efficiently, enhancing energy and spectrum efficiency, has attracted considerable interest in both academic and industrial fields. Hence, we extend the system model into the Over-the-Air OFDM-IM system by toggling frequency-changing RIS on and off. Furthermore, we analytically assess the average bit error probability (ABEP) of the proposed Over-the-Air OFDM-IM system using the maximum likelihood (ML) decoder. Subsequently, we present comprehensive computer simulation results to demonstrate the significant improvement in bit error rate (BER) performance of the proposed Over-the-Air OFDM-IM system compared to reference systems employing RIS-aided OFDM.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721573","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 : 2024-07-15DOI: 10.1109/ojcoms.2024.3428531
Himanshi Babbar, Shalli Rani, Wadii Boulila
{"title":"Fortifying the Connection: Cybersecurity Tactics for WSN-driven Smart Manufacturing in the Era of Industry 5.0","authors":"Himanshi Babbar, Shalli Rani, Wadii Boulila","doi":"10.1109/ojcoms.2024.3428531","DOIUrl":"https://doi.org/10.1109/ojcoms.2024.3428531","url":null,"abstract":"","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":7.9,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141721571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1109/OJCOMS.2024.3426495
Adel Khaled;Ahmed S. Alwakeel;Abdullah M. Shaheen;Mostafa M. Fouda;Mohamed I. Ismail
Employing Reconfigurable Intelligent Surface (RIS) is an advanced strategy to enhance the efficiency of wireless communication systems. However, the number and positions of the RISs elements are still challenging and require a smart optimization framework. This paper aims to optimize the number of RISs subject to the technical limitations of the average achievable data rate with consideration of the practical overlapping between the associated multi-RISs in wireless communication systems. In this regard, the Differential evolution optimizer (DEO) algorithm is created to minimize the number of RIS devices to be installed. Accordingly, the number, positions, and phase shift matrix coefficients of RISs are then jointly optimized using the intended DEO. Also, it is contrasted to several recent algorithms, including Particle swarm optimization (PSO), Gradient-based optimizer (GBO), Growth optimizer (GO), and Seahorse optimization (SHO). The outcomes from the simulation demonstrate the high efficiency of the proposed DEO and GO in obtaining a 100% feasibility rate for finding the minimum number of RISs under different threshold values of the achievable rates. PSO scores a comparable result of 99.09%, while SHO and GBO attain poor rates of 66.36% and 53.94%, respectively. Nevertheless, the excellence of the created DEO becomes evident through having the lowest average number of RISs when compared to the other algorithms. Numerically, the DEO drives improvements by 5.13%, 15.68%, 30.58%, and 51.01% compared to GO, PSO, SHO and GBO, respectively.
{"title":"Placement Optimization and Power Management in a Multiuser Wireless Communication System With Reconfigurable Intelligent Surfaces","authors":"Adel Khaled;Ahmed S. Alwakeel;Abdullah M. Shaheen;Mostafa M. Fouda;Mohamed I. Ismail","doi":"10.1109/OJCOMS.2024.3426495","DOIUrl":"10.1109/OJCOMS.2024.3426495","url":null,"abstract":"Employing Reconfigurable Intelligent Surface (RIS) is an advanced strategy to enhance the efficiency of wireless communication systems. However, the number and positions of the RISs elements are still challenging and require a smart optimization framework. This paper aims to optimize the number of RISs subject to the technical limitations of the average achievable data rate with consideration of the practical overlapping between the associated multi-RISs in wireless communication systems. In this regard, the Differential evolution optimizer (DEO) algorithm is created to minimize the number of RIS devices to be installed. Accordingly, the number, positions, and phase shift matrix coefficients of RISs are then jointly optimized using the intended DEO. Also, it is contrasted to several recent algorithms, including Particle swarm optimization (PSO), Gradient-based optimizer (GBO), Growth optimizer (GO), and Seahorse optimization (SHO). The outcomes from the simulation demonstrate the high efficiency of the proposed DEO and GO in obtaining a 100% feasibility rate for finding the minimum number of RISs under different threshold values of the achievable rates. PSO scores a comparable result of 99.09%, while SHO and GBO attain poor rates of 66.36% and 53.94%, respectively. Nevertheless, the excellence of the created DEO becomes evident through having the lowest average number of RISs when compared to the other algorithms. Numerically, the DEO drives improvements by 5.13%, 15.68%, 30.58%, and 51.01% compared to GO, PSO, SHO and GBO, respectively.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10596074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141615043","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}
In this article, we focus on a generic multiterminal (remote) source coding scenario in which, via a joint design, several intermediate nodes must locally compress their noisy observations from various sets of user / source signals ahead of forwarding them through multiple error-free and rate-limited channels to a (remote) processing unit. Although different local compressors might receive noisy observations from a / several common source signal(s), each local quantizer should also compress noisy observations from its own, i.e., uncommon source signal(s). This, in turn, yields a highly generalized scheme with most flexibility w.r.t. the assignment of users to the serving nodes, compared to the State-of-the-Art techniques designed exclusively for a common source signal. Following the Information Bottleneck (IB) philosophy, we choose the Mutual Information as the fidelity criterion here, and, by taking advantage of the Variational Calculus, we characterize the form of stationary solutions for two different types of processing flow/ strategy. We utilize the derived solutions as the core of our devised algorithmic approach, the GE neralized M ultivariate IB (GEMIB), to (efficiently) address the corresponding design problems. We further provide the respective convergence proofs of GEMIB to a stationary point of the pertinent objective functionals and substantiate its effectiveness by means of numerical investigations over a couple of (typical) digital transmission scenarios.
{"title":"Multi-Source Distributed Data CompressionBased on Information Bottleneck Principle","authors":"Shayan Hassanpour;Alireza Danaee;Dirk Wübben;Armin Dekorsy","doi":"10.1109/OJCOMS.2024.3426049","DOIUrl":"10.1109/OJCOMS.2024.3426049","url":null,"abstract":"In this article, we focus on a generic multiterminal (remote) source coding scenario in which, via a joint design, several intermediate nodes must locally compress their noisy observations from various sets of user / source signals ahead of forwarding them through multiple error-free and rate-limited channels to a (remote) processing unit. Although different local compressors might receive noisy observations from a / several common source signal(s), each local quantizer should also compress noisy observations from its own, i.e., uncommon source signal(s). This, in turn, yields a highly generalized scheme with most flexibility w.r.t. the assignment of users to the serving nodes, compared to the State-of-the-Art techniques designed exclusively for a common source signal. Following the Information Bottleneck (IB) philosophy, we choose the Mutual Information as the fidelity criterion here, and, by taking advantage of the Variational Calculus, we characterize the form of stationary solutions for two different types of processing flow/ strategy. We utilize the derived solutions as the core of our devised algorithmic approach, the \u0000<underline>GE</u>\u0000neralized \u0000<underline>M</u>\u0000ultivariate \u0000<underline>IB</u>\u0000 (GEMIB), to (efficiently) address the corresponding design problems. We further provide the respective convergence proofs of GEMIB to a stationary point of the pertinent objective functionals and substantiate its effectiveness by means of numerical investigations over a couple of (typical) digital transmission scenarios.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10592014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141585955","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 : 2024-07-10DOI: 10.1109/OJCOMS.2024.3425831
Pedro Martinez-Julia;Ved P. Kafle;Hitoshi Asaeda
Network automation has become crucial in supporting services in 6G networks. This mainly derives from the complexity of the composition of numerous distributed virtual network functions (VNFs) in creating highly flexible virtual network services. Therefore, a network service automation system is a key technology enabler for 6G. However, the added complexity renders network service automation systems particularly sensitive to faults, some of which cause network outages that harm the smooth operation of basic societal services. Current state-of-the-art (SotA) solutions for fault detection can barely detect hidden faults. Herein, we propose a mechanism for automated network service analysis (ANSA), which constructs and analyzes a digital twin of a network service. The digital twin represents the available information about the network service based on category theory. It uses the properties of category theory to perform an analysis through which the faults of the network service are identified. We evaluate a prototype of a network service automation system that incorporates ANSA to demonstrate 1) the benefits of using digital twins for analyzing network services, 2) the benefits of using category theory for constructing digital twins of the network services, and 3) the resulting improvements in fault detection. Overall, ANSA can detect an average of 94% of the faults present in a network service. In comparison, previous SotA solutions can detect only 30%–50% of all faults.
{"title":"Application of Category Theory to Network Service Fault Detection","authors":"Pedro Martinez-Julia;Ved P. Kafle;Hitoshi Asaeda","doi":"10.1109/OJCOMS.2024.3425831","DOIUrl":"10.1109/OJCOMS.2024.3425831","url":null,"abstract":"Network automation has become crucial in supporting services in 6G networks. This mainly derives from the complexity of the composition of numerous distributed virtual network functions (VNFs) in creating highly flexible virtual network services. Therefore, a network service automation system is a key technology enabler for 6G. However, the added complexity renders network service automation systems particularly sensitive to faults, some of which cause network outages that harm the smooth operation of basic societal services. Current state-of-the-art (SotA) solutions for fault detection can barely detect hidden faults. Herein, we propose a mechanism for automated network service analysis (ANSA), which constructs and analyzes a digital twin of a network service. The digital twin represents the available information about the network service based on category theory. It uses the properties of category theory to perform an analysis through which the faults of the network service are identified. We evaluate a prototype of a network service automation system that incorporates ANSA to demonstrate 1) the benefits of using digital twins for analyzing network services, 2) the benefits of using category theory for constructing digital twins of the network services, and 3) the resulting improvements in fault detection. Overall, ANSA can detect an average of 94% of the faults present in a network service. In comparison, previous SotA solutions can detect only 30%–50% of all faults.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10592034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141585958","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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