Pub Date : 2025-01-29DOI: 10.1109/LCOMM.2025.3535879
Yu Wang;Guan Gui
Radio Frequency Fingerprinting (RFF) is viewed as a potential strategy to enhance wireless security by utilizing inherent hardware characteristics of transmitters. Recently, Deep Learning (DL)-based RFF methods have been extensively studied and significantly improved identification performance. However, new challenges are introduced, particularly content dependency. This dependency emerges when signals contain unique transmitter identifiers (IDs), such as the ICAO addresses in Automatic Dependent Surveillance-Broadcast (ADS-B) system. In such cases, DL models may prioritize these IDs over the intrinsic hardware fingerprint information, resulting in inflated accuracy. Moreover, as these IDs are vulnerable to tampering, their reliability and robustness are substantially compromised. To overcome this, we propose a novel content-agnostic RFF method that incorporates a consistency-guided robust learning framework. The proposed method employs a masking mechanism to zero out signal segments associated with transmitter IDs and processes both original and masked signals through a shared feature embedding, ensuring minimal content dependency while thoroughly extracting fingerprint information across the entire signal. To enhance its effectiveness, we introduce semantic consistency regularization to align the feature semantics of original and masked signals. Additionally, attention consistency regularization, leveraging class activation mapping, is employed to constrain the attention distribution across the two signal variants. These complementary strategies effectively mitigate the risk of over-reliance on transmitter IDs, ensuring comprehensive extraction of fingerprint information. Simulation results demonstrate robust identification despite transmitter ID tampering, and highlight its content independence. The codes can be downloaded at https://github.com/BeechburgPieStar/ CGRL-for-Content-Agnostic-RFF.
{"title":"Consistency-Guided Robust Learning for Content-Agnostic Radio Frequency Fingerprinting","authors":"Yu Wang;Guan Gui","doi":"10.1109/LCOMM.2025.3535879","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3535879","url":null,"abstract":"Radio Frequency Fingerprinting (RFF) is viewed as a potential strategy to enhance wireless security by utilizing inherent hardware characteristics of transmitters. Recently, Deep Learning (DL)-based RFF methods have been extensively studied and significantly improved identification performance. However, new challenges are introduced, particularly content dependency. This dependency emerges when signals contain unique transmitter identifiers (IDs), such as the ICAO addresses in Automatic Dependent Surveillance-Broadcast (ADS-B) system. In such cases, DL models may prioritize these IDs over the intrinsic hardware fingerprint information, resulting in inflated accuracy. Moreover, as these IDs are vulnerable to tampering, their reliability and robustness are substantially compromised. To overcome this, we propose a novel content-agnostic RFF method that incorporates a consistency-guided robust learning framework. The proposed method employs a masking mechanism to zero out signal segments associated with transmitter IDs and processes both original and masked signals through a shared feature embedding, ensuring minimal content dependency while thoroughly extracting fingerprint information across the entire signal. To enhance its effectiveness, we introduce semantic consistency regularization to align the feature semantics of original and masked signals. Additionally, attention consistency regularization, leveraging class activation mapping, is employed to constrain the attention distribution across the two signal variants. These complementary strategies effectively mitigate the risk of over-reliance on transmitter IDs, ensuring comprehensive extraction of fingerprint information. Simulation results demonstrate robust identification despite transmitter ID tampering, and highlight its content independence. The codes can be downloaded at <uri>https://github.com/BeechburgPieStar/ CGRL-for-Content-Agnostic-RFF</uri>.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"610-614"},"PeriodicalIF":3.7,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-28DOI: 10.1109/LCOMM.2025.3535759
Yin Zhang;Liqun Zhao;Yuli Zhao;Francis C. M. Lau;Hai Yu;Zhiliang Zhu;Bin Zhang
This letter presents a novel frameless ALOHA random access scheme based on the online fountain codes. In this work, we incorporate feedback into the conventional frameless ALOHA scheme and utilize the uni-partite graph to depict the user-slot relationship. We further employ successive interference cancellation (SIC) for user resolution. We derive a formula for computing the optimal access probability, which is combined with the online fountain codes. To evaluate the throughput of our proposed scheme, we analyze it using the relevant theory of random graph. Our theoretical and simulation results are consistent, and demonstrate that our proposed scheme outperforms the traditional frameless ALOHA scheme in terms of the throughput and the packet error rate.
{"title":"An Improved Frameless ALOHA Scheme With Feedback Strategy","authors":"Yin Zhang;Liqun Zhao;Yuli Zhao;Francis C. M. Lau;Hai Yu;Zhiliang Zhu;Bin Zhang","doi":"10.1109/LCOMM.2025.3535759","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3535759","url":null,"abstract":"This letter presents a novel frameless ALOHA random access scheme based on the online fountain codes. In this work, we incorporate feedback into the conventional frameless ALOHA scheme and utilize the uni-partite graph to depict the user-slot relationship. We further employ successive interference cancellation (SIC) for user resolution. We derive a formula for computing the optimal access probability, which is combined with the online fountain codes. To evaluate the throughput of our proposed scheme, we analyze it using the relevant theory of random graph. Our theoretical and simulation results are consistent, and demonstrate that our proposed scheme outperforms the traditional frameless ALOHA scheme in terms of the throughput and the packet error rate.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"605-609"},"PeriodicalIF":3.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1109/LCOMM.2025.3532638
Shih Yu Chang;Hsiao-Hwa Chen
This letter explores the applications of fluid antenna in wireless semantic communications, aiming to fill up a gap in existing research. In particular, this letter applies Fluid Antenna for Importance-based Ranking (FAIR) systems, which can reconfigure communication encoders and fluid antenna parameters dynamically based on the significance of individual words in a sentence. A reconfiguration and power optimization algorithm is proposed to enhance transmission efficiency. The system’s performance is evaluated using Word Error Rate (WER) and ROUGE metrics, demonstrating its potential to improve the performance of semantic communications, particularly in dynamic and resource-constrained environments.
{"title":"Fluid Antenna for Importance-Based Ranking (FAIR) Semantic Communications","authors":"Shih Yu Chang;Hsiao-Hwa Chen","doi":"10.1109/LCOMM.2025.3532638","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3532638","url":null,"abstract":"This letter explores the applications of fluid antenna in wireless semantic communications, aiming to fill up a gap in existing research. In particular, this letter applies Fluid Antenna for Importance-based Ranking (FAIR) systems, which can reconfigure communication encoders and fluid antenna parameters dynamically based on the significance of individual words in a sentence. A reconfiguration and power optimization algorithm is proposed to enhance transmission efficiency. The system’s performance is evaluated using Word Error Rate (WER) and ROUGE metrics, demonstrating its potential to improve the performance of semantic communications, particularly in dynamic and resource-constrained environments.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"567-571"},"PeriodicalIF":3.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1109/LCOMM.2025.3534520
Kenan Turbic;Martin Kasparick;Sławomir Stańczak
This letter presents an analytical analysis of the Doppler spectrum in von Mises-Fisher (vMF) scattering channels. A simple closed-form expression for the Doppler spectrum is derived and used to investigate the impact of the vMF scattering parameters, i.e., the mean direction and the degree of concentration of scatterers. The spectrum is observed to exhibit exponential behavior for mobile antenna motion parallel to the mean direction of scatterers, while conforming to a Gaussian-like shape for the perpendicular motion. The validity of the obtained results is verified by comparison against the results of Monte Carlo simulations, where an exact match is observed.
{"title":"Doppler Power Spectrum in Channels With von Mises-Fisher Distribution of Scatterers","authors":"Kenan Turbic;Martin Kasparick;Sławomir Stańczak","doi":"10.1109/LCOMM.2025.3534520","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3534520","url":null,"abstract":"This letter presents an analytical analysis of the Doppler spectrum in von Mises-Fisher (vMF) scattering channels. A simple closed-form expression for the Doppler spectrum is derived and used to investigate the impact of the vMF scattering parameters, i.e., the mean direction and the degree of concentration of scatterers. The spectrum is observed to exhibit exponential behavior for mobile antenna motion parallel to the mean direction of scatterers, while conforming to a Gaussian-like shape for the perpendicular motion. The validity of the obtained results is verified by comparison against the results of Monte Carlo simulations, where an exact match is observed.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"596-599"},"PeriodicalIF":3.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1109/LCOMM.2025.3534320
Jiaying Zhang;Qiushuo Hou;Guanding Yu
In recent years, machine learning (ML) tasks have been widely deployed at the edge of wireless networks, e.g., autonomous cars and tactile robots. However, the impairments of wireless channels between devices, such as fading and noise, deteriorate the effectiveness of ML inference tasks. In this work, we propose an efficient framework with an adaptive power control mechanism, which considers the constraint of the limited energy budget of edge devices. To guarantee the inference performance of ML tasks that are transmitted through wireless channels, we design hypernetworks with meta-parameters. The hypernetwork takes the context, such as the network condition, as the input and outputs the parameters of the power control network and artificial intelligence (AI) model. The training loss is designed by minimizing the trade-off between inference performance and energy consumption. Simulation results verify the effectiveness of the proposed adaptive inference framework on energy saving while ensuring the accuracy of inferring ML tasks.
{"title":"Power Control for Edge ML Inference With Hypernetwork Meta-Parameters","authors":"Jiaying Zhang;Qiushuo Hou;Guanding Yu","doi":"10.1109/LCOMM.2025.3534320","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3534320","url":null,"abstract":"In recent years, machine learning (ML) tasks have been widely deployed at the edge of wireless networks, e.g., autonomous cars and tactile robots. However, the impairments of wireless channels between devices, such as fading and noise, deteriorate the effectiveness of ML inference tasks. In this work, we propose an efficient framework with an adaptive power control mechanism, which considers the constraint of the limited energy budget of edge devices. To guarantee the inference performance of ML tasks that are transmitted through wireless channels, we design hypernetworks with meta-parameters. The hypernetwork takes the context, such as the network condition, as the input and outputs the parameters of the power control network and artificial intelligence (AI) model. The training loss is designed by minimizing the trade-off between inference performance and energy consumption. Simulation results verify the effectiveness of the proposed adaptive inference framework on energy saving while ensuring the accuracy of inferring ML tasks.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"591-595"},"PeriodicalIF":3.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1109/LCOMM.2025.3534858
Qiwei Huai;Weina Yuan;Yue Wu;Pingzhi Fan
Rate splitting multiple access (RSMA) is an emerging multiple access scheme that plays a significant role in improving user sum-rate. This letter proposes a downlink orthogonal time frequency space-RSMA (OTFS-RSMA) cross-domain transmission scheme based on heterogeneous mobile user grouping and multicast technology, where high-speed users are served in the delay-Doppler (DD) domain and low-speed users are served in the time-frequency (TF) domain. Specifically, the OTFS-RSMA scheme categorizes users into high-speed users group and low-speed users group based on their mobility and then uses multicast to send cross-domain signals to the respective user groups, with RSMA used for transmission within the groups. By jointly optimizing the rate allocation and power control, this letter proposes a two-stage algorithm based on the coati optimization algorithm (COA) to maximize user sum-rate under the constraints of base station transmission power and QoS rate requirements. Our simulation results show that the proposed OTFS-RSMA scheme significantly outperforms the OTFS-NOMA scheme in terms of improving sum-rate.
{"title":"Downlink OTFS-RSMA Cross-Domain Transmission Scheme and Sum-Rate Maximization","authors":"Qiwei Huai;Weina Yuan;Yue Wu;Pingzhi Fan","doi":"10.1109/LCOMM.2025.3534858","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3534858","url":null,"abstract":"Rate splitting multiple access (RSMA) is an emerging multiple access scheme that plays a significant role in improving user sum-rate. This letter proposes a downlink orthogonal time frequency space-RSMA (OTFS-RSMA) cross-domain transmission scheme based on heterogeneous mobile user grouping and multicast technology, where high-speed users are served in the delay-Doppler (DD) domain and low-speed users are served in the time-frequency (TF) domain. Specifically, the OTFS-RSMA scheme categorizes users into high-speed users group and low-speed users group based on their mobility and then uses multicast to send cross-domain signals to the respective user groups, with RSMA used for transmission within the groups. By jointly optimizing the rate allocation and power control, this letter proposes a two-stage algorithm based on the coati optimization algorithm (COA) to maximize user sum-rate under the constraints of base station transmission power and QoS rate requirements. Our simulation results show that the proposed OTFS-RSMA scheme significantly outperforms the OTFS-NOMA scheme in terms of improving sum-rate.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"600-604"},"PeriodicalIF":3.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-24DOI: 10.1109/LCOMM.2025.3533928
Tuna Ozates;Aykut Koç
We present deep joint source-outer channel coding (DeepJSOC), an end-to-end deep learning-based semantic communication architecture designed for channels with insertions, deletions, and substitutions (IDS). We propose a three-stage training algorithm that combines, for the first time, gated recurrent unit (GRU) networks for marker detection, transformer-based semantic communication for continuous latent space, and lookup-free quantization for binarized latent space optimization, specifically tailored to IDS channels. The proposed DeepJSOC is the first to integrate deep learning-based error correction networks into joint-source channel coding schemes for binary channels with synchronization errors. We demonstrate the effectiveness of DeepJSOC by experiments, achieving significant improvements over existing methods in text transmission.
{"title":"Semantic Communication Over Channels With Insertions, Deletions, and Substitutions","authors":"Tuna Ozates;Aykut Koç","doi":"10.1109/LCOMM.2025.3533928","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3533928","url":null,"abstract":"We present deep joint source-outer channel coding (DeepJSOC), an end-to-end deep learning-based semantic communication architecture designed for channels with insertions, deletions, and substitutions (IDS). We propose a three-stage training algorithm that combines, for the first time, gated recurrent unit (GRU) networks for marker detection, transformer-based semantic communication for continuous latent space, and lookup-free quantization for binarized latent space optimization, specifically tailored to IDS channels. The proposed DeepJSOC is the first to integrate deep learning-based error correction networks into joint-source channel coding schemes for binary channels with synchronization errors. We demonstrate the effectiveness of DeepJSOC by experiments, achieving significant improvements over existing methods in text transmission.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"586-590"},"PeriodicalIF":3.7,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1109/LCOMM.2025.3533262
Lazar S. Stojković;Velimir M. Ilić;Ivan B. Djordjevic
We derive closed-form expressions for the Gallager error function of the additive exponential noise channels and provide theoretical upper bounds on its maximum over the input probability distribution space (the cutoff rate), thus extending the previous results derived for the additive white Gaussian noise channels. Our theoretical results allow us to design constellations using simple optimization techniques that directly maximize the Gallager error function of the additive exponential noise channels. We perform simulations and show that projected gradient ascent optimization yields constellations competitive to existing ones that are optimized for Shannon information metrics, which require numerical estimation.
{"title":"Achievable Cutoff Rates of the Additive Exponential Noise Channels","authors":"Lazar S. Stojković;Velimir M. Ilić;Ivan B. Djordjevic","doi":"10.1109/LCOMM.2025.3533262","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3533262","url":null,"abstract":"We derive closed-form expressions for the Gallager error function of the additive exponential noise channels and provide theoretical upper bounds on its maximum over the input probability distribution space (the cutoff rate), thus extending the previous results derived for the additive white Gaussian noise channels. Our theoretical results allow us to design constellations using simple optimization techniques that directly maximize the Gallager error function of the additive exponential noise channels. We perform simulations and show that projected gradient ascent optimization yields constellations competitive to existing ones that are optimized for Shannon information metrics, which require numerical estimation.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"582-585"},"PeriodicalIF":3.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1109/LCOMM.2025.3533039
Rong Yang;Shuping Dang;Jia Ye;Peng Wang
Due to its outstanding mathematical tractability, the inverse gamma (InvG) distribution is used as a substitute for the lognormal distribution to characterize the random fluctuations of the wireless signal envelope caused by shadowing. In this letter, we carry out the information-theoretic study of this channel model substitution (CMS) technique in terms of feasibility, approximation accuracy, and optimality by adopting both moment matching and Kullback-Leibler divergence (KLD) minimization criteria for parametric mapping. Specifically, we derive the minimum achievable KLD by the lognormal-to-InvG CMS and the corresponding optimal parametric mapping relation. By comparing to the gamma substitute that has been widely used for approximating the lognormal shadowing model, we demonstrate that the InvG substitute is more mathematically tractable and rigorously prove that the InvG substitute, however, cannot yield a lower KLD than the gamma substitute when applying the same parametric mapping criterion.
{"title":"Information-Theoretic Analysis of Inverse Gamma Substitution for Lognormal Shadowing Models","authors":"Rong Yang;Shuping Dang;Jia Ye;Peng Wang","doi":"10.1109/LCOMM.2025.3533039","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3533039","url":null,"abstract":"Due to its outstanding mathematical tractability, the inverse gamma (InvG) distribution is used as a substitute for the lognormal distribution to characterize the random fluctuations of the wireless signal envelope caused by shadowing. In this letter, we carry out the information-theoretic study of this channel model substitution (CMS) technique in terms of feasibility, approximation accuracy, and optimality by adopting both moment matching and Kullback-Leibler divergence (KLD) minimization criteria for parametric mapping. Specifically, we derive the minimum achievable KLD by the lognormal-to-InvG CMS and the corresponding optimal parametric mapping relation. By comparing to the gamma substitute that has been widely used for approximating the lognormal shadowing model, we demonstrate that the InvG substitute is more mathematically tractable and rigorously prove that the InvG substitute, however, cannot yield a lower KLD than the gamma substitute when applying the same parametric mapping criterion.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"577-581"},"PeriodicalIF":3.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-23DOI: 10.1109/LCOMM.2025.3532952
Tianrun Qiao;Xiaojie Fang;Xuejun Sha
In this letter, a low complexity iterative block decision feedback equalization (IBDFE) algorithm is designed for single carrier frequency domain equalization (SC-FDE) systems. By identifying error peaks within the output of minimum mean square error frequency domain linear equalizer (MMSE FD-LE) and substituting them with feedback signal, a performance gain of more than 3dB compared to MMSE FD-LE can be achieved at a bit error rate (BER) of $10^{-4}$ . The proposed algorithm has a minor performance loss compared to IBDFE system based on MMSE criterion (IBDFE-MMSE), while also offering lower latency and complexity close to that of MMSE FD-LE.
{"title":"Iterative Block Decision Feedback Equalization With Near-Linear Complexity for SC-FDE Systems","authors":"Tianrun Qiao;Xiaojie Fang;Xuejun Sha","doi":"10.1109/LCOMM.2025.3532952","DOIUrl":"https://doi.org/10.1109/LCOMM.2025.3532952","url":null,"abstract":"In this letter, a low complexity iterative block decision feedback equalization (IBDFE) algorithm is designed for single carrier frequency domain equalization (SC-FDE) systems. By identifying error peaks within the output of minimum mean square error frequency domain linear equalizer (MMSE FD-LE) and substituting them with feedback signal, a performance gain of more than 3dB compared to MMSE FD-LE can be achieved at a bit error rate (BER) of <inline-formula> <tex-math>$10^{-4}$ </tex-math></inline-formula>. The proposed algorithm has a minor performance loss compared to IBDFE system based on MMSE criterion (IBDFE-MMSE), while also offering lower latency and complexity close to that of MMSE FD-LE.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 3","pages":"572-576"},"PeriodicalIF":3.7,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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