Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000067
Love Allen Chijioke Ahakonye;Gabriel Chukwunonso Amaizu;Cosmas Ifeanyi Nwakanma;Jae Min Lee;Dong-Seong Kim
The domain name system (DNS) has evolved into an essential component of network communications, as well as a critical component of critical industrial systems (CIS) and Supervisory Control and Data Acquisition (SCADA) network connection. DNS over HTTPS (DoH) encapsulating DNS within hypertext transfer protocol secure (HTTPS) does not eliminate network access exploitation. This paper proposes a hybrid deep learning model for the early classification of encoded network traffic into one of the two classes: DoH and NonDoH. They can be malicious, benign, or zero-day attacks. The proposed scheme incorporates the swiftness of the convolutional neural network (CNN) in extracting useful information and the ease of long short-term memory (LSTM) in learning long-term dependencies. The simulation results showed that the proposed approach accurately classifies the encoded network traffic as DoH or NonDoH and characterizes the traffic as benign, zero-day, or malicious. The proposed robust hybrid deep learning model had high accuracy and precision of 99.28%, recall of 99.75%, and AUC of 0.9975 at a minimal training and testing time of 745s and 0.000324 s, respectively. In addition to outperforming other compared contemporary algorithms and existing techniques, the proposed technique significantly detects all attack types. This study also investigated the impact of the SMOTE technique as a tool for data balancing. To further validate the reliability of the proposed scheme, an industrial control system SCADA (ICS-SCADA) dataset, in addition to two (2) other cyber-security datasets (NSL-KDD and CICDS2017), were evaluated. Mathews correlation coefficient (MCC) was employed to validate the model performance, confirming the applicability of the proposed model in a critical industrial system such as SCADA.
{"title":"Classification and characterization of encoded traffic in SCADA network using hybrid deep learning scheme","authors":"Love Allen Chijioke Ahakonye;Gabriel Chukwunonso Amaizu;Cosmas Ifeanyi Nwakanma;Jae Min Lee;Dong-Seong Kim","doi":"10.23919/JCN.2023.000067","DOIUrl":"https://doi.org/10.23919/JCN.2023.000067","url":null,"abstract":"The domain name system (DNS) has evolved into an essential component of network communications, as well as a critical component of critical industrial systems (CIS) and Supervisory Control and Data Acquisition (SCADA) network connection. DNS over HTTPS (DoH) encapsulating DNS within hypertext transfer protocol secure (HTTPS) does not eliminate network access exploitation. This paper proposes a hybrid deep learning model for the early classification of encoded network traffic into one of the two classes: DoH and NonDoH. They can be malicious, benign, or zero-day attacks. The proposed scheme incorporates the swiftness of the convolutional neural network (CNN) in extracting useful information and the ease of long short-term memory (LSTM) in learning long-term dependencies. The simulation results showed that the proposed approach accurately classifies the encoded network traffic as DoH or NonDoH and characterizes the traffic as benign, zero-day, or malicious. The proposed robust hybrid deep learning model had high accuracy and precision of 99.28%, recall of 99.75%, and AUC of 0.9975 at a minimal training and testing time of 745s and 0.000324 s, respectively. In addition to outperforming other compared contemporary algorithms and existing techniques, the proposed technique significantly detects all attack types. This study also investigated the impact of the SMOTE technique as a tool for data balancing. To further validate the reliability of the proposed scheme, an industrial control system SCADA (ICS-SCADA) dataset, in addition to two (2) other cyber-security datasets (NSL-KDD and CICDS2017), were evaluated. Mathews correlation coefficient (MCC) was employed to validate the model performance, confirming the applicability of the proposed model in a critical industrial system such as SCADA.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 1","pages":"65-79"},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2024.000010
{"title":"Copyright transfer form","authors":"","doi":"10.23919/JCN.2024.000010","DOIUrl":"https://doi.org/10.23919/JCN.2024.000010","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 1","pages":"153-155"},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.23919/JCN.2023.000062
Raghu Thekke Veedu;Kiran Manjappa
This study aims to give an edge to public safety applications over commercial applications in an underlay cellular-assisted device-to-device (D2D) communication. The proposed framework introduces two frameworks: Cluster-based many-to-many resource allocation and resource sharing framework (CMMRARS) and constant time power control algorithm (CTPCA). The RB assigned to a CUE can share with multiple DUE pairs, and the DUE pairs can also use RB assigned to multiple CUEs under the many-to-many strategy. The CMMRARS framework is responsible for resource allocation and resource sharing and accordingly, it is further divided into three sub-problems. The CTPCA framework is divided into two subproblems and used to find optimal power for cellular users and D2D transmitters to avoid cross-tier and co-tier interference. The K-means clustering algorithm is employed to form application-specific clusters, and it ensures that more cellular users fall into the public safety clusters so that the D2D users will get more resource-sharing options. Cellular users use a weighted bipartite graph to form a priority list of D2D users for resource sharing. The main objective of the proposed work is to enhance the system's sum rate by simultaneously reusing the same resource by multiple D2D pairs and safeguarding the Quality of Services provided to all kinds of network users. A theoretical justification is presented to ensure that the proposed frameworks terminate after a certain number of runs and congregate to a consistent matching. Simulation results show that the proposed method influences the overall system's sum rate and provides a preference for public safety applications over commercial applications.
{"title":"An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach","authors":"Raghu Thekke Veedu;Kiran Manjappa","doi":"10.23919/JCN.2023.000062","DOIUrl":"https://doi.org/10.23919/JCN.2023.000062","url":null,"abstract":"This study aims to give an edge to public safety applications over commercial applications in an underlay cellular-assisted device-to-device (D2D) communication. The proposed framework introduces two frameworks: Cluster-based many-to-many resource allocation and resource sharing framework (CMMRARS) and constant time power control algorithm (CTPCA). The RB assigned to a CUE can share with multiple DUE pairs, and the DUE pairs can also use RB assigned to multiple CUEs under the many-to-many strategy. The CMMRARS framework is responsible for resource allocation and resource sharing and accordingly, it is further divided into three sub-problems. The CTPCA framework is divided into two subproblems and used to find optimal power for cellular users and D2D transmitters to avoid cross-tier and co-tier interference. The K-means clustering algorithm is employed to form application-specific clusters, and it ensures that more cellular users fall into the public safety clusters so that the D2D users will get more resource-sharing options. Cellular users use a weighted bipartite graph to form a priority list of D2D users for resource sharing. The main objective of the proposed work is to enhance the system's sum rate by simultaneously reusing the same resource by multiple D2D pairs and safeguarding the Quality of Services provided to all kinds of network users. A theoretical justification is presented to ensure that the proposed frameworks terminate after a certain number of runs and congregate to a consistent matching. Simulation results show that the proposed method influences the overall system's sum rate and provides a preference for public safety applications over commercial applications.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 1","pages":"19-34"},"PeriodicalIF":3.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10459141","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.23919/JCN.2023.000051
Mir Muhammad Suleman Sarwar;Afaq Muhammad;Wang-Cheol Song
This paper presents an intent-based networking (IBN) system for the orchestration of OpenStack-based clouds and overlay networks between multiple clouds. Clouds need to communicate with other clouds for various reasons such as reducing latency and overcoming single points of failure. An overlay network provides connectivity between multiple Clouds for communication. Moreover, there can be several paths of communication between a source and a destination cloud in the overlay network. A machine learning model can be used to proactively select the best path for efficient network performance. Communication between the source and destination can then be established over the selected path. Communication in such type of a scenario requires complex networking configurations. IBN provides a closed-loop and Intelligent system for cloud to cloud communication. To this end, IBN abstracts complex networking and cloud configurations by receiving an intent from a user, translating the intent, generating complex configurations for the intent, and deploying the configurations, thereby assuring the intent. Therefore, the IBN that is presented here has three major features: (1) It can deploy an OpenStack cloud at a target machine, (2) it can deploy GENEVE tunnels between different clouds that form an overlay network, and (3) it can then leverage the advantages of machine learning to find the best path for communication between any two clouds. As machine learning is an essential component of the intelligent IBN system, two linear and three non-linear models were tested. RNN, LSTM, and GRU models were employed for non-linear modeling. Linear regression and SVR models were employed for linear modeling. Overall all the non-linear models outperformed the linear model with an 81% R 2 score, exhibiting similar performance. Linear models also showed similar performance but with lower accuracy. The testbed contains an overlay network of 11 GENEVE tunnels between 7 OpenStack-based clouds deployed in Malaysia, Korea, Pakistan, and Cambodia at TEIN.
{"title":"IBN@Cloud: An intent-based cloud and overlay network orchestration system","authors":"Mir Muhammad Suleman Sarwar;Afaq Muhammad;Wang-Cheol Song","doi":"10.23919/JCN.2023.000051","DOIUrl":"https://doi.org/10.23919/JCN.2023.000051","url":null,"abstract":"This paper presents an intent-based networking (IBN) system for the orchestration of OpenStack-based clouds and overlay networks between multiple clouds. Clouds need to communicate with other clouds for various reasons such as reducing latency and overcoming single points of failure. An overlay network provides connectivity between multiple Clouds for communication. Moreover, there can be several paths of communication between a source and a destination cloud in the overlay network. A machine learning model can be used to proactively select the best path for efficient network performance. Communication between the source and destination can then be established over the selected path. Communication in such type of a scenario requires complex networking configurations. IBN provides a closed-loop and Intelligent system for cloud to cloud communication. To this end, IBN abstracts complex networking and cloud configurations by receiving an intent from a user, translating the intent, generating complex configurations for the intent, and deploying the configurations, thereby assuring the intent. Therefore, the IBN that is presented here has three major features: (1) It can deploy an OpenStack cloud at a target machine, (2) it can deploy GENEVE tunnels between different clouds that form an overlay network, and (3) it can then leverage the advantages of machine learning to find the best path for communication between any two clouds. As machine learning is an essential component of the intelligent IBN system, two linear and three non-linear models were tested. RNN, LSTM, and GRU models were employed for non-linear modeling. Linear regression and SVR models were employed for linear modeling. Overall all the non-linear models outperformed the linear model with an 81% R\u0000<sup>2</sup>\u0000 score, exhibiting similar performance. Linear models also showed similar performance but with lower accuracy. The testbed contains an overlay network of 11 GENEVE tunnels between 7 OpenStack-based clouds deployed in Malaysia, Korea, Pakistan, and Cambodia at TEIN.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 1","pages":"131-146"},"PeriodicalIF":3.6,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10416318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.23919/JCN.2023.000053
Mahmoud A. Albreem;Saeed Abdallah;Khawla A. Alnajjar;Mahmoud Aldababsa
Massive multiple-input multiple-output (MIMO) is one of the essential technologies in beyond fifth generation (B5G) communication systems due to its impact in attaining high power efficiency and spectrum efficiency. The design of low-complexity detectors for massive MIMO continues to attract significant research and industry attention due to the critical need to find the right balance between performance and computational complexity, especially with a large number of antennas at both the transmitting and receiving sides. It has been noticed in several recent studies that appropriate initialization of iterative data detection techniques plays a crucial role in both the performance and the computational complexity. In this article, we propose three efficient initialization methods that achieve a favorable balance between performance and complexity. Instead of using the conventional diagonal matrix, we employ the scaled identity matrix, the stair matrix, and the band matrix with the first iteration of the Newton method to initialize the accelerated overrelaxation (AOR), the successive overrelaxation (SOR), the Gauss-Seidel (GS), the Jacobi (JA), and the Richardson (RI) based detectors. The scaling factor depends on the minimum and maximum eigenvalues of the equalization matrix. The proposed detectors are tested with different massive MIMO configurations, different modulation schemes (QPSK, 16QAM and 64QAM), and perfect and imperfect channel state information (CSI). Using simulations, we show that the proposed detectors achieve a significant performance gain compared to the minimum mean-squared error (MMSE) based detector, the conventional linear massive MIMO detectors, and other existing detectors, at a remarkable complexity reduction.
大规模多输入多输出（MIMO）是超越第五代（B5G）通信系统的基本技术之一，因为它对实现高功率效率和频谱效率具有重要影响。由于亟需在性能和计算复杂度之间找到合适的平衡点，特别是在发射端和接收端都有大量天线的情况下，为大规模多输入多输出设计低复杂度探测器的工作继续吸引着研究人员和业界的极大关注。最近的一些研究注意到，迭代数据检测技术的适当初始化对性能和计算复杂度都起着至关重要的作用。在本文中，我们提出了三种高效的初始化方法，在性能和复杂度之间取得了良好的平衡。我们没有使用传统的对角矩阵，而是采用了缩放标识矩阵、阶梯矩阵和带状矩阵与牛顿法的第一次迭代，来初始化基于加速过度松弛（AOR）、连续过度松弛（SOR）、高斯-赛德尔（GS）、雅可比（JA）和理查森（RI）的检测器。缩放因子取决于均衡矩阵的最小和最大特征值。我们使用不同的大规模多输入多输出（MIMO）配置、不同的调制方案（QPSK、16QAM 和 64QAM）以及完美和不完美的信道状态信息（CSI）对所提出的检测器进行了测试。通过仿真，我们发现，与基于最小均方误差 (MMSE) 的检测器、传统线性大规模 MIMO 检测器和其他现有检测器相比，所提出的检测器在显著降低复杂性的同时，实现了显著的性能提升。
{"title":"Efficient detectors for uplink massive MIMO systems","authors":"Mahmoud A. Albreem;Saeed Abdallah;Khawla A. Alnajjar;Mahmoud Aldababsa","doi":"10.23919/JCN.2023.000053","DOIUrl":"https://doi.org/10.23919/JCN.2023.000053","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) is one of the essential technologies in beyond fifth generation (B5G) communication systems due to its impact in attaining high power efficiency and spectrum efficiency. The design of low-complexity detectors for massive MIMO continues to attract significant research and industry attention due to the critical need to find the right balance between performance and computational complexity, especially with a large number of antennas at both the transmitting and receiving sides. It has been noticed in several recent studies that appropriate initialization of iterative data detection techniques plays a crucial role in both the performance and the computational complexity. In this article, we propose three efficient initialization methods that achieve a favorable balance between performance and complexity. Instead of using the conventional diagonal matrix, we employ the scaled identity matrix, the stair matrix, and the band matrix with the first iteration of the Newton method to initialize the accelerated overrelaxation (AOR), the successive overrelaxation (SOR), the Gauss-Seidel (GS), the Jacobi (JA), and the Richardson (RI) based detectors. The scaling factor depends on the minimum and maximum eigenvalues of the equalization matrix. The proposed detectors are tested with different massive MIMO configurations, different modulation schemes (QPSK, 16QAM and 64QAM), and perfect and imperfect channel state information (CSI). Using simulations, we show that the proposed detectors achieve a significant performance gain compared to the minimum mean-squared error (MMSE) based detector, the conventional linear massive MIMO detectors, and other existing detectors, at a remarkable complexity reduction.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 1","pages":"35-48"},"PeriodicalIF":3.6,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10416319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140031707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.23919/JCN.2023.000043
Hyeongtae Ahn;Harim Lee;Young Deok Park
Recently, full-duplex radio has attracted attention as a solution for wireless local area networks (WLANs) where traffic is exploding but available frequency bands are insufficient. Full-duplex radio exploits various self-interference cancellation technologies to transmit and receive signals concurrently in the same frequency band. Thus, the efficiency of the frequency band is doubled compared with that of conventional half-duplex radios. However, to effectively exploit full-duplex radio, new problems that do not exist in conventional half-duplex radio, such as full-duplex link setup, inter-node interference avoidance, and idle uplink period (IUP), must be addressed. We propose a full-duplex medium access control (MAC) protocol to effectively exploit full-duplex radio by addressing these problems. In particular, our MAC protocol uses an IUP to transmit an acknowledgment (ACK) frame and report the buffer information of nodes. Accordingly, an access point can gather the node's buffer information during the IUP and schedule the transmission of nodes without competition. In addition, because the uplink ACK frame is transmitted during the IUP, additional channel usage time for the uplink ACK frame transmission is not required. Therefore, the proposed MAC protocol improves the WLAN throughput by reducing the number of control frame transmissions and the IUP. The results of our performance analysis and simulation show that the MAC protocol achieves throughput improvements compared with those of previous studies.
近来，全双工无线电作为无线局域网（WLAN）的一种解决方案备受关注，因为在这种网络中，通信量激增，但可用频段不足。全双工无线电利用各种自干扰消除技术，在同一频段同时发射和接收信号。因此，与传统的半双工无线电相比，频段的效率提高了一倍。然而，要有效利用全双工无线电，必须解决传统半双工无线电不存在的新问题，如全双工链路设置、节点间干扰避免和空闲上行链路周期（IUP）。我们提出了一种全双工介质访问控制（MAC）协议，通过解决这些问题来有效利用全双工无线电。特别是，我们的 MAC 协议使用 IUP 传输确认（ACK）帧，并报告节点的缓冲区信息。因此，接入点可以在 IUP 期间收集节点的缓冲区信息，并在没有竞争的情况下安排节点的传输。此外，由于上行链路 ACK 帧是在 IUP 期间传输的，因此上行链路 ACK 帧传输不需要额外的信道使用时间。因此，拟议的 MAC 协议通过减少控制帧传输次数和 IUP 来提高 WLAN 吞吐量。性能分析和仿真结果表明，与之前的研究相比，MAC 协议的吞吐量有所提高。
{"title":"AUB: A full-duplex MAC protocol for the efficient utilization of the idle uplink period in WLAN","authors":"Hyeongtae Ahn;Harim Lee;Young Deok Park","doi":"10.23919/JCN.2023.000043","DOIUrl":"https://doi.org/10.23919/JCN.2023.000043","url":null,"abstract":"Recently, full-duplex radio has attracted attention as a solution for wireless local area networks (WLANs) where traffic is exploding but available frequency bands are insufficient. Full-duplex radio exploits various self-interference cancellation technologies to transmit and receive signals concurrently in the same frequency band. Thus, the efficiency of the frequency band is doubled compared with that of conventional half-duplex radios. However, to effectively exploit full-duplex radio, new problems that do not exist in conventional half-duplex radio, such as full-duplex link setup, inter-node interference avoidance, and idle uplink period (IUP), must be addressed. We propose a full-duplex medium access control (MAC) protocol to effectively exploit full-duplex radio by addressing these problems. In particular, our MAC protocol uses an IUP to transmit an acknowledgment (ACK) frame and report the buffer information of nodes. Accordingly, an access point can gather the node's buffer information during the IUP and schedule the transmission of nodes without competition. In addition, because the uplink ACK frame is transmitted during the IUP, additional channel usage time for the uplink ACK frame transmission is not required. Therefore, the proposed MAC protocol improves the WLAN throughput by reducing the number of control frame transmissions and the IUP. The results of our performance analysis and simulation show that the MAC protocol achieves throughput improvements compared with those of previous studies.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"25 6","pages":"750-759"},"PeriodicalIF":3.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10387276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.23919/JCN.2023.000048
Raed Mesleh;Nareeman Jibreel;Abdelhamid Younis
Employing cutting-edge non-orthogonal multiple access (NOMA) techniques, index modulation multiple access (IMMA)introduces an efficient methodology. By leveraging index modulation (IM), IMMA facilitates concurrent data transmission among multiple users. It enhances this process by incorporating an additional constellation diagram that conveys extra information bits per channel utilization. In this work, we conduct a comprehensive investigation. We derive the theoretical capacity of the IMMA system and analyze mutual information across receiver channel estimation scenarios—ranging from perfect to imperfect. To validate our derivations, we execute Monte Carlo simulations, affirming our theoretical results. Notably, our findings confirm that the derived theoretical capacity formula acts as an upper bound for simulated mutual information curves. Additionally, we identify conditions for achieving the derived capacity, rigorously verifying their applicability. Through compelling comparisons, we evaluate the IMMA system's performance in mutual information and capacity against sparse code multiple access (SCMA) systems. This analysis underscores the superior attributes of the IMMA system, showcasing its potential. To illuminate practical constraints, we establish a crucial bound on users effectively sharing orthogonal resources, offering deployment insights. Furthermore, we contrast IMMA systems with traditional orthogonal multiple access (OMA) counterparts, dissecting the implications of overloading. This comprehensive approach yields a holistic comprehension of the scheme's ramifications.
索引调制多路存取（IMMA）采用了最先进的非正交多路存取（NOMA）技术，是一种高效的方法。通过利用索引调制（IM），IMMA 可促进多用户之间的并发数据传输。它通过结合额外的星座图来增强这一过程，从而在每次信道利用中传递额外的信息比特。在这项工作中，我们进行了全面的研究。我们推导出 IMMA 系统的理论容量，并分析了从完美到不完美的各种接收器信道估计情况下的互信息。为了验证我们的推导，我们进行了蒙特卡罗模拟，肯定了我们的理论结果。值得注意的是，我们的研究结果证实，推导出的理论容量公式是模拟互信息曲线的上限。此外，我们还确定了实现推导容量的条件，严格验证了其适用性。通过令人信服的比较，我们评估了 IMMA 系统在互信息和容量方面与稀疏码多重存取 (SCMA) 系统的性能。这项分析强调了 IMMA 系统的优越性，展示了它的潜力。为了阐明实际限制因素，我们建立了用户有效共享正交资源的关键约束，提供了部署见解。此外，我们还将 IMMA 系统与传统的正交多址接入 (OMA) 系统进行了对比，剖析了过载的影响。通过这种综合方法，我们可以全面了解该方案的影响。
{"title":"Capacity analysis of index modulation multiple access system","authors":"Raed Mesleh;Nareeman Jibreel;Abdelhamid Younis","doi":"10.23919/JCN.2023.000048","DOIUrl":"https://doi.org/10.23919/JCN.2023.000048","url":null,"abstract":"Employing cutting-edge non-orthogonal multiple access (NOMA) techniques, index modulation multiple access (IMMA)introduces an efficient methodology. By leveraging index modulation (IM), IMMA facilitates concurrent data transmission among multiple users. It enhances this process by incorporating an additional constellation diagram that conveys extra information bits per channel utilization. In this work, we conduct a comprehensive investigation. We derive the theoretical capacity of the IMMA system and analyze mutual information across receiver channel estimation scenarios—ranging from perfect to imperfect. To validate our derivations, we execute Monte Carlo simulations, affirming our theoretical results. Notably, our findings confirm that the derived theoretical capacity formula acts as an upper bound for simulated mutual information curves. Additionally, we identify conditions for achieving the derived capacity, rigorously verifying their applicability. Through compelling comparisons, we evaluate the IMMA system's performance in mutual information and capacity against sparse code multiple access (SCMA) systems. This analysis underscores the superior attributes of the IMMA system, showcasing its potential. To illuminate practical constraints, we establish a crucial bound on users effectively sharing orthogonal resources, offering deployment insights. Furthermore, we contrast IMMA systems with traditional orthogonal multiple access (OMA) counterparts, dissecting the implications of overloading. This comprehensive approach yields a holistic comprehension of the scheme's ramifications.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"25 6","pages":"711-721"},"PeriodicalIF":3.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10387273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.23919/JCN.2023.10387283
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Pub Date : 2023-12-01DOI: 10.23919/JCN.2023.000031
Shahnila Rahim;Limei Peng;Shihyu Chang;Pin-Han Ho
This paper investigates the scenario of the Internet of things (IoT) data collection via multiple unmanned aerial vehicles (UAVs), where a novel collaborative multi-agent trajectory planning and data collection (CMA-TD) algorithm is introduced for online obtaining the trajectories of the multiple UAVs without any prior knowledge of the sensor locations. We first provide two integer linear programs (ILPs) for the considered system by taking the coverage and the total power usage as the optimization targets. As a complement to the ILPs and to avoid intractable computation, the proposed CMA-TD algorithm can effectively solve the formulated problem via a deep reinforcement learning (DRL) process on a double deep Q-learning network (DDQN). Extensive simulations are conducted to verify the performance of the proposed CMA-TD algorithm and compare it with a couple of state-of-the-art counterparts in terms of the amount of served IoT nodes, energy consumption, and utilization rates.
{"title":"On collaborative multi-UAV trajectory planning for data collection","authors":"Shahnila Rahim;Limei Peng;Shihyu Chang;Pin-Han Ho","doi":"10.23919/JCN.2023.000031","DOIUrl":"https://doi.org/10.23919/JCN.2023.000031","url":null,"abstract":"This paper investigates the scenario of the Internet of things (IoT) data collection via multiple unmanned aerial vehicles (UAVs), where a novel collaborative multi-agent trajectory planning and data collection (CMA-TD) algorithm is introduced for online obtaining the trajectories of the multiple UAVs without any prior knowledge of the sensor locations. We first provide two integer linear programs (ILPs) for the considered system by taking the coverage and the total power usage as the optimization targets. As a complement to the ILPs and to avoid intractable computation, the proposed CMA-TD algorithm can effectively solve the formulated problem via a deep reinforcement learning (DRL) process on a double deep Q-learning network (DDQN). Extensive simulations are conducted to verify the performance of the proposed CMA-TD algorithm and compare it with a couple of state-of-the-art counterparts in terms of the amount of served IoT nodes, energy consumption, and utilization rates.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"25 6","pages":"722-733"},"PeriodicalIF":3.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10387274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.23919/JCN.2023.000047
Wenhao Wu;Xiaoning Zhang;Jiaming Pan;Yihui Zhou
Recently, time-sensitive services have expanded from traditional industrial control systems to more scenarios. Some time-sensitive applications, such as remote surgery, autonomous driving, augmented reality (AR), etc., require deterministic end-to-end delay and jitter in data transmission. deterministic network (DetNet) is proposed as a promising technology for providing deterministic service in wide area networks (WAN). DetNet guarantees deterministic end-to-end delay and jitter by specifying a certain routing path and transmission time-slots for timesensitive flows. However, how to efficiently steer time-sensitive flows while jointly allocating transmission time-slots is still an open problem. Existing flow scheduling algorithms are limited in the scenarios of local area networks (LAN), and do not consider the impact of propagation delay in large-scale networks. To this end, we study the joint optimization of time-slot allocation and traffic steering, while considering the propagation delay of WAN links. Our objective is to maximize the number of successfully deployed time-sensitive flows under the constraints of required end-to-end delay. Accordingly, we formulate the studied problem as an integer linear programming (ILP) model. Since it is proved to be an NP-hard problem, we design a heuristic algorithm named genetic-based deterministic network traffic scheduling (GDNTS). The solution with the largest number of deployed time-sensitive flows can be obtained from the evolution of chromosomes in GDNTS. Compared with the benchmark algorithms, extensive simulation results show that GDNTS improves the deployed time sensitive-flows number by 22.85% in average.
{"title":"Joint optimization of time-slot allocation and traffic steering for large-scale deterministic networks","authors":"Wenhao Wu;Xiaoning Zhang;Jiaming Pan;Yihui Zhou","doi":"10.23919/JCN.2023.000047","DOIUrl":"https://doi.org/10.23919/JCN.2023.000047","url":null,"abstract":"Recently, time-sensitive services have expanded from traditional industrial control systems to more scenarios. Some time-sensitive applications, such as remote surgery, autonomous driving, augmented reality (AR), etc., require deterministic end-to-end delay and jitter in data transmission. deterministic network (DetNet) is proposed as a promising technology for providing deterministic service in wide area networks (WAN). DetNet guarantees deterministic end-to-end delay and jitter by specifying a certain routing path and transmission time-slots for timesensitive flows. However, how to efficiently steer time-sensitive flows while jointly allocating transmission time-slots is still an open problem. Existing flow scheduling algorithms are limited in the scenarios of local area networks (LAN), and do not consider the impact of propagation delay in large-scale networks. To this end, we study the joint optimization of time-slot allocation and traffic steering, while considering the propagation delay of WAN links. Our objective is to maximize the number of successfully deployed time-sensitive flows under the constraints of required end-to-end delay. Accordingly, we formulate the studied problem as an integer linear programming (ILP) model. Since it is proved to be an NP-hard problem, we design a heuristic algorithm named genetic-based deterministic network traffic scheduling (GDNTS). The solution with the largest number of deployed time-sensitive flows can be obtained from the evolution of chromosomes in GDNTS. Compared with the benchmark algorithms, extensive simulation results show that GDNTS improves the deployed time sensitive-flows number by 22.85% in average.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"25 6","pages":"825-840"},"PeriodicalIF":3.6,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10387282","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139406633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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