IEEE Open Journal of the Communications Society最新文献

{"title":"State-of-the-Art Security Schemes for the Internet of Underwater Things: A Holistic Survey","authors":"Nadir Adam;Mansoor Ali;Faisal Naeem;Abdallah S. Ghazy;Georges Kaddoum","doi":"10.1109/OJCOMS.2024.3474290","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3474290","url":null,"abstract":"With the growing interest that is being shown in marine resources, the concept of the Internet of Things (IoT) has been extended to underwater scenarios, which has given rise to the Internet of Underwater Things (IoUT). The IoUT encompasses a network of interconnected intelligent underwater devices that can be used to monitor underwater environments and support various applications, such as underwater exploration, disaster prevention, and environmental monitoring. Advances in underwater wireless communication and sensor technologies have propelled the IoUT concept forward. However, the IoUT faces significant challenges. The harsh and vast underwater environment makes information sensing particularly difficult and leads to insufficient or inaccurate data being collected. Additionally, underwater conditions like pressure variation, hydrological characteristics, temperature changes, water currents, and topography hinder conventional communication models and make data transmission difficult and inefficient. Security in IoUT networks is a critical concern due to hardware limitations and seawater channel imperfections. Constrained sensor nodes and spatial-temporal uncertainty introduced by node mobility further complicate security provisioning. This survey paper addresses these challenges by offering a comprehensive overview of IoUT security. The investigation thoroughly examines both traditional and classic machine learning techniques and focuses on deploying advanced technologies such as federated learning and digital twin. The study effectively addresses integration challenges and open issues and provides a roadmap for future directions to play a pivotal role in formulating robust security mechanisms for IoUT networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6561-6592"},"PeriodicalIF":6.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705129","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142517969","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}

{"title":"Blockchain-Based Decentralized Federated Learning With On-Chain Model Aggregation and Incentive Mechanism for Industrial IoT","authors":"Qing Yang;Wei Xu;Taotao Wang;Hao Wang;Xiaoxiao Wu;Bin Cao;Shengli Zhang","doi":"10.1109/OJCOMS.2024.3471621","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3471621","url":null,"abstract":"Federated learning (FL) is an emerging machine learning paradigm that enables the participants to train a global model without sharing the training data. Recently, FL has been widely deployed in industrial IoT scenarios because of its data privacy and scalability. However, the current FL architecture relies on a central server to orchestrate the FL process, thus incurring a risk of privacy leakage and single-point failure. To address this issue, we propose a fully decentralized FL architecture based on blockchain technology. Unlike existing blockchain-based FL systems that use blockchain for coordination or storage, we use blockchain as a trustable computing platform for model aggregation. Furthermore, we model the interaction between the FL task publisher and participants as a Stackelberg game and design a rewarding mechanism to incentivize participants to contribute to the FL task. We build a prototype system of the proposed decentralized FL architecture and implement an FL-based damaged package detection application to evaluate the proposed approach. Experimental results show that the blockchain-based decentralized FL is feasible in a practical industrial IoT scenario, and the incentive mechanism performs well with real application data.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6420-6429"},"PeriodicalIF":6.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447092","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}

{"title":"Recent Advances in Deep Learning for Channel Coding: A Survey","authors":"Toshiki Matsumine;Hideki Ochiai","doi":"10.1109/OJCOMS.2024.3472094","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3472094","url":null,"abstract":"This paper provides a comprehensive survey of recent advances in deep learning (DL) techniques for channel coding problems. Inspired by the recent successes of DL in a variety of research domains, its applications to physical layer technologies have been extensively studied in recent years, and they are expected to be a potential breakthrough in supporting the emerging use cases of the next generation wireless communication systems such as 6G. In this paper, we focus exclusively on channel coding problems and review existing approaches that incorporate advanced DL techniques into code design and channel decoding. After briefly introducing the background of recent DL techniques, we categorize and summarize a variety of approaches, including model-free and model-based DL, for the design and decoding of modern error-correcting codes, such as low-density parity check (LDPC) codes and polar codes, to highlight their potential advantages and challenges. Finally, the paper concludes with a discussion of open issues and future research directions in channel coding.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6443-6481"},"PeriodicalIF":6.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10702508","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447136","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}

{"title":"CoCo: A CBOW-Based Framework for Synergistic Vulnerability Detection in Partial and Discontinuous Logs for NextG Communications","authors":"Yifeng Peng;Xinyi Li;Sudhanshu Arya;Ying Wang","doi":"10.1109/OJCOMS.2024.3471709","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3471709","url":null,"abstract":"With the development of communication technology, protocol design, and infrastructure implementation have become more complex, bringing significant security challenges to 5G and NextG systems. Fuzz testing is widely used to detect system vulnerabilities and the health status under the condition of abnormal input. In this paper, we generate fuzz testing via the Man In The Middle Model (MITM) at various locations of the time sequence in the 5G authentication and authorization process and analyze the communication state transitions, which are recorded in the log files of fuzz testing cases. CoCo introduces a novel CBOW-based framework for synergistic vulnerability detection, addressing the challenge of partial log data and scalability in real-time environments, a significant advancement in the field of NextG communication security. CoCo can be applied to identifying the type of attacks or abnormal inputs from partial system profiling for the impacted behaviors. In particular, we show, for the first time, that by utilizing the CoCo, we can precisely detect the fuzzed layer using only a partial segment of the log file in real-time and identify the root cause of vulnerabilities with high accuracy. The results show that when we get only 40% portion of the entire log file, applying convolutional neural network (CNN) in the machine learning models can reach the Area under Curve (AUC) value of 92%. Furthermore, by strategically combining these segments, we enhanced the efficacy of vulnerability detection, demonstrating a synergistic effect where the combined impact is greater than the sum of individual parts, meanwhile reducing the time complexity by 6%.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6381-6403"},"PeriodicalIF":6.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10701039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447137","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}

{"title":"Near-Field Integrated Sensing and Communication: Performance Analysis and Beamforming Design","authors":"Kaiqian Qu;Shuaishuai Guo;Nasir Saeed;Jia Ye","doi":"10.1109/OJCOMS.2024.3470844","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3470844","url":null,"abstract":"This paper explores the potential near-field beamforming (NFBF) in integrated sensing and communication (ISAC) systems with extremely large-scale arrays (XL-arrays). The large-scale antenna arrays increase the possibility of having communication users and targets of interest in the near field of the base station (BS). The paper first establishes the models of near-field spherical waves and far-field plane waves. With the models, we analyze the near-field beam focusing ability and the far-field beam steering ability by finding the gain-loss mathematical expression caused by the far-field steering vector mismatch in the near-field case. Subsequently, we analyzed the performance degradation caused by traditional far-field beamforming in the near field for both communication and sensing. We formulate the transceiver NFBF design problem as maximizing the sensing signal-to-interference-plus-noise ratio (SINR) while ensuring the required communication quality-of-service (QoS) and total power constraint. We decompose it into two subproblems and solve them using the generalized Rayleigh entropy theory and the Semi-Definite Relaxation (SDR) technique. Additionally, we prove the attainability of the optimal solution for SDR. Additionally, a low-complexity design scheme is proposed as an alternative to the SDR approach for obtaining transmit beamforming. The simulation results validate the effectiveness of the proposed NFBF scheme, demonstrating its capability to manage co-angle interference and enhance both communication and sensing performance.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6353-6366"},"PeriodicalIF":6.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700785","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408930","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}

{"title":"An Efficient Spectral Approach for JCR Narrow Band Signals in Presence of Multipath and Noise","authors":"Salem Titouni;Idris Messaoudene;Yassine Himeur;Massinissa Belazzoug;Boualem Hammache;Shadi Atalla;Wathiq Mansoor","doi":"10.1109/OJCOMS.2024.3470689","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3470689","url":null,"abstract":"Joint Communication Radar (JCR) systems have garnered significant attention due to their ability to simultaneously perform communication and radar sensing tasks. However, in challenging environments, JCR signals are vulnerable to multipath propagation, resulting in signal degradation, interference, and reduced system performance. This paper explores the challenges posed by multipath effects on JCR signals and proposes novel mitigation techniques to enhance their robustness and reliability. The suggested method involves employing a spectral transformation to enhance the JCR-emitted signal, resulting in a significant improvement in the overall effectiveness of JCR systems. Consequently, the numerical implementation of the JCR system integrated with the proposed technique leads to improved performance metrics, including Multipath Error Envelope (MEE), Root Mean Square Error (RMSE), and Standard Deviation (STD). By effectively mitigating the adverse impacts of multipath propagation, the proposed methodologies enhance the robustness and accuracy of JCR systems, leading to improved communication reliability and radar sensing capabilities. Notably, the proposed method achieved a minimal Root Mean Square Error (RMSE) of just 0.05, marking a substantial enhancement in performance compared to existing methods.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6343-6352"},"PeriodicalIF":6.3,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408890","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}

{"title":"New Systematic MDS Array Codes With Two Parities","authors":"Lan Ma;Liyang Zhou;Shaoteng Liu;Xiangyu Chen;Qifu Sun","doi":"10.1109/OJCOMS.2024.3468873","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3468873","url":null,"abstract":"Row-diagonal parity (RDP) code is a classical \u0000<inline-formula> <tex-math>$(k+2,~k)$ </tex-math></inline-formula>\u0000 systematic maximum distance separable (MDS) array code with \u0000<inline-formula> <tex-math>$k leq L-1$ </tex-math></inline-formula>\u0000 under sub-packetization level \u0000<inline-formula> <tex-math>$l = L-1$ </tex-math></inline-formula>\u0000, where L is a prime integer. When \u0000<inline-formula> <tex-math>$k = L-1$ </tex-math></inline-formula>\u0000, its encoding requires \u0000<inline-formula> <tex-math>$2-{}frac {2}{k}$ </tex-math></inline-formula>\u0000 XORs per original data bit, which exactly achieves theoretical optimal lower bound. In this paper, we present three new constructions of \u0000<inline-formula> <tex-math>$(k+2,~k)$ </tex-math></inline-formula>\u0000 systematic MDS array codes. First, under sub-packetization level \u0000<inline-formula> <tex-math>$l = 4$ </tex-math></inline-formula>\u0000, we novelly design a \u0000<inline-formula> <tex-math>$(17,~15)$ </tex-math></inline-formula>\u0000 array code \u0000<inline-formula> <tex-math>${mathcal {C}}_{1}$ </tex-math></inline-formula>\u0000, where k can reach the largest possible value to satisfy the MDS property. Moreover, when \u0000<inline-formula> <tex-math>$k leq 7$ </tex-math></inline-formula>\u0000, the encoding complexity of its subcodes can exactly achieve the theoretical optimal \u0000<inline-formula> <tex-math>$2-{}frac {2}{k}$ </tex-math></inline-formula>\u0000 XORs per original data bit, and likewise, the decoding complexity of the subcodes with \u0000<inline-formula> <tex-math>$k leq 4$ </tex-math></inline-formula>\u0000 is also exactly optimal. Under sub-packetization level \u0000<inline-formula> <tex-math>$l = L-1$ </tex-math></inline-formula>\u0000 with certain primes L, the second construction yields an MDS array code \u0000<inline-formula> <tex-math>${mathcal {C}}_{2}$ </tex-math></inline-formula>\u0000 with \u0000<inline-formula> <tex-math>$k leq {}frac {L(L-1)}{2}$ </tex-math></inline-formula>\u0000, and the encoding complexity of \u0000<inline-formula> <tex-math>${mathcal {C}}_{2}$ </tex-math></inline-formula>\u0000 is also exactly optimal for \u0000<inline-formula> <tex-math>$k = L-1$ </tex-math></inline-formula>\u0000, \u0000<inline-formula> <tex-math>$2L-3$ </tex-math></inline-formula>\u0000. Furthermore, based on bit permutation, the third MDS array code \u0000<inline-formula> <tex-math>${mathcal {C}}_{3}$ </tex-math></inline-formula>\u0000 is obtained with \u0000<inline-formula> <tex-math>$k leq L(L-1)$ </tex-math></inline-formula>\u0000 under sub-packetization level \u0000<inline-formula> <tex-math>$l = 2(L-1)$ </tex-math></inline-formula>\u0000 with certain primes L. In particular, as an extension of \u0000<inline-formula> <tex-math>${mathcal {C}}_{2}$ </tex-math></inline-formula>\u0000, \u0000<inline-formula> <tex-math>${mathcal {C}}_{3}$ </tex-math></inline-formula>\u0000 exactly achieves the optimal encoding complexity for \u0000<inline-formula> <tex-math>$k = 2(2L-3)$ </tex-math></inline-formula>\u0000, which does not hold for other array codes in the literature.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6329-6342"},"PeriodicalIF":6.3,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10695780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142408889","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}

{"title":"Distributed Computing and Model-Based Estimation for Integrated Communications and Sensing: A Roadmap","authors":"Sebastian Semper;Joël Naviliat;Jonas Gedschold;Michael Döbereiner;Steffen Schieler;Reiner S. Thomä","doi":"10.1109/OJCOMS.2024.3467683","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3467683","url":null,"abstract":"The recent advances in Integrated Sensing and Communications (ICAS) essentially transform mobile radio networks into a diverse, dynamic and heterogeneous sensing network. For the application of localization, the acquired sensing data needs to be processed to estimates of the state vectors of the targets in a timely manner. This paper aims at providing a roadmap for the development of a suitable computing system for ICAS. We propose to embed the signal processing into the concept of edge computing. It provides the necessary theoretical computing framework, since it alleviates the need for communication with a remote cloud. To obtain localization information in such a distributed, asynchronous and heterogeneous scenario, we study how existing maximum likelihood estimation techniques can be transformed into algorithms that can be orchestrated close to the edge. The advantage of these approaches is that they have well studied statistical properties and efficient algorithmic implementations exist. We propose to study to derive a graph that encodes these algorithms' processing by relating individual and isolated computations in terms of the input/output-behavior of so-called compute nodes. This compute graph structure can then be flexibly distributed across multiple devices and even whole processing/sensing units. Moreover, modern computing architectures leverage such graph structures to optimize the efficient use of computing hardware. Additionally, once this graph is constructed we have laid the groundwork for the possibility to exchange certain compute steps by deep learning architectures. For instance, this allows to sidestep some costly iterative part of traditional maximum likelihood estimators, which further contributes to the low-latency of the localization task. Moreover, deep learning methods bear the promise of being more robust to model mismatches in contrast to the conventional model based approaches. As a consequence, we can then study the relation between those classical methods and the new deep learning based methods and analyze the achievable performance. One key final result will be a deeper understanding of how well the maximum likelihood approach can be applied to ICAS and how much it profits from the combination with modern deep learning techniques.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6279-6290"},"PeriodicalIF":6.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10693506","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383395","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}

{"title":"WiLO-OFDM Transmission Scheme for Simultaneous Wireless Information and Power Transfer","authors":"Steven Claessens;Prerna Dhull;Dominique Schreurs;Sofie Pollin","doi":"10.1109/OJCOMS.2024.3467680","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3467680","url":null,"abstract":"Lowering the dependency of receivers and sensors on energy supplies is a requirement for a realistic Internet of Things. This is certainly achieved when sensor nodes are powered wirelessly. Local oscillators (LOs), required to receive and transmit modern radio frequency (RF) waveforms, consume a considerable amount of the power budget. We propose a Wireless Local Oscillator (WiLO) concept to move the LO from the sensor to an external location and transmit it wirelessly to the sensor. This WiLO is modeled as a constant tone transmission. As is well known, the sensor can backscatter the constant tone, which enables uplink transmission. Our system approach allows the downconversion of any RF waveform without LO and mixer while simultaneously utilizing the same signal for power transfer. In this work, we demonstrate our approach to different types of OFDM signals, which can be considered as a general complex RF signal example to be received. Our WiLO-based technique to receive any modern communication signal without LO, in combination with harvesting energy from the tone and backscattering on that tone, results in a promising energy-efficient IoT solution. We present the performance model with design requirements for WiLO tone and amplitudes of OFDM tones for feasible reception of WiLO-OFDM. Simultaneous Wireless Information and Power Transfer (SWIPT) applications typically operate in a high SNR regime, and both energy harvesting and information transfer are equally important. The cost of 12 dB performance with an AWGN noisy channel can be acceptable by saving a significant amount of power by removing the LO.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6261-6278"},"PeriodicalIF":6.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10693571","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383392","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}

{"title":"An LLR-Based Receiver for Mitigating Bursty Impulsive Noise With Unknown Distributions","authors":"Hazem Barka;Md Sahabul Alam;Georges Kaddoum;Minh Au;Basile L. Agba","doi":"10.1109/OJCOMS.2024.3467385","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3467385","url":null,"abstract":"The rapid expansion of Internet of Things (IoT) networks has paved the way for their integration into mission-critical applications requiring secure and reliable monitoring, such as smart grid utilities. However, these advanced power grids face significant challenges in maintaining reliable wireless communication, particularly in hostile environments like high-voltage substations and power plants. These environments are characterized by intense bursts of interference, known as impulsive noise with memory. To address this problem, in this study, we introduce a two-process receiver design. The first process is a multi-step receiver parameter estimation process. The second process is a novel memory-aware log-likelihood ratio (LLR) calculation method designed to mitigate the effects of impulsive noise with memory using the parameters estimated from the first process. This method is computationally efficient, which makes it suitable for IoT devices with limited computational capabilities. Simulation results obtained show that the proposed method achieves a bit error rate (BER) similar to the corresponding BERs of the best-performing algorithms with perfect noise parameters. Furthermore, it outperforms the Viterbi algorithm amid imperfect noise parameters. Notably, it method achieves these benchmarks while substantially improving execution time.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"5 ","pages":"6166-6179"},"PeriodicalIF":6.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10693527","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142383396","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}