Pub Date : 2025-11-10DOI: 10.1109/tsp.2025.3629732
Yunlian Tian, Wei Yi, Wujun Li, Hongbin Li
{"title":"Joint Coherent Integration and Detection of Radar Spread Targets with Range Migration","authors":"Yunlian Tian, Wei Yi, Wujun Li, Hongbin Li","doi":"10.1109/tsp.2025.3629732","DOIUrl":"https://doi.org/10.1109/tsp.2025.3629732","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"99 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-07DOI: 10.1109/tsp.2025.3630236
Guangle Jia, Yulong Huang, Henry Leung
{"title":"A Novel Robust Kalman Filter Based on Normal-Bernoulli Distribution for Non-stationary Heavy-tailed Measurement Noise","authors":"Guangle Jia, Yulong Huang, Henry Leung","doi":"10.1109/tsp.2025.3630236","DOIUrl":"https://doi.org/10.1109/tsp.2025.3630236","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"167 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145461395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satellite-integrated Internet is regarded as one of the promising frameworks for supporting massive machine type communications-satellite (mMTC-s) via code domain grant-free random access (GFRA). However, the sporadic activation and short-packet transmissions of mMTC-s user equipments (UEs) lead to pilot collisions and decoding failures, which compromise the reliability of massive access and present significant challenges in existing GFRA schemes. By combining the zero-correlation-zone shift-and-superposition pilot (ZSP) with the $ T $-order codebook, this paper proposes a $ZT$-collision resolution GFRA ($ZT$-GFRA) scheme to address these limitations. In the $ZT$-GFRA scheme, each activated UE splits its $ k $-bit message into $r + 1$ parts. The first $ r $ parts are each $ b $ bits long and are assigned to different zero-correlation-zone periodic sequences. These $ r $ sequences are then superimposed to generate a ZSP, thereby expanding the available pilot set. The remaining $k-rb$ bits are encoded using a $ T $-order codebook and concatenated with the ZSP to form a complete frame for access. Moreover, we design a successive iteration then joint ordered likelihood decoder to decode up to $ T $ UEs transmitting the same ZSP, supporting access for up to $binom{Z}{r}cdot T$ UEs. We derive the theoretical expressions for the access failure probability (AFP) of the $ZT$-GFRA scheme under a shadowed-Rician fading channel. Simulation results demonstrate that, compared to the state-of-the-art schemes, our $ZT$-GFRA scheme achieves a significantly lower pilot collision probability and AFP under the same sequence length and SNR conditions.
卫星集成互联网被认为是通过码域无授权随机接入（GFRA）支持大规模机器型卫星通信（mMTC-s）的有前途的框架之一。然而，mMTC-s用户设备（ue）的零星激活和短包传输导致导频碰撞和解码失败，影响了大规模接入的可靠性，给现有的GFRA方案带来了重大挑战。通过将零相关区偏移叠加导频（ZSP）与$ T$阶码本相结合，提出了$ZT$碰撞分辨率GFRA （$ZT$ -GFRA）方案来解决这些限制。在$ZT$ -GFRA方案中，每个激活的UE将其$ k $位消息分成$r + 1$部分。前$ r $部分各$ b $位长，并分配给不同的零相关区周期序列。然后将这些$ r $序列叠加以生成ZSP，从而扩展可用的导频集。剩余的$k-rb$位使用$ T $顺序码本进行编码，并与ZSP连接以形成一个完整的帧供访问。此外，我们设计了一个连续迭代然后联合有序似然解码器来解码多达$ T$ ue传输相同的ZSP，支持访问多达$binom{Z}{r}cdot $ T$ ue。导出了在阴影-梯度衰落信道下ZT -GFRA方案的接入失败概率（AFP）的理论表达式。仿真结果表明，与现有方案相比，在相同序列长度和信噪比条件下，我们的ZT -GFRA方案具有较低的先导碰撞概率和AFP。
{"title":"ZT-Collision Resolution Grant-Free Random Access for Satellite-Integrated Internet","authors":"Liang Xu;Xue Zhao;Yaosheng Zhang;Ye Wang;Jian Jiao;Qinyu Zhang","doi":"10.1109/TSP.2025.3628609","DOIUrl":"10.1109/TSP.2025.3628609","url":null,"abstract":"Satellite-integrated Internet is regarded as one of the promising frameworks for supporting massive machine type communications-satellite (mMTC-s) via code domain grant-free random access (GFRA). However, the sporadic activation and short-packet transmissions of mMTC-s user equipments (UEs) lead to pilot collisions and decoding failures, which compromise the reliability of massive access and present significant challenges in existing GFRA schemes. By combining the zero-correlation-zone shift-and-superposition pilot (ZSP) with the <inline-formula> <tex-math>$ T $</tex-math> </inline-formula>-order codebook, this paper proposes a <inline-formula> <tex-math>$ZT$</tex-math> </inline-formula>-collision resolution GFRA (<inline-formula> <tex-math>$ZT$</tex-math> </inline-formula>-GFRA) scheme to address these limitations. In the <inline-formula> <tex-math>$ZT$</tex-math> </inline-formula>-GFRA scheme, each activated UE splits its <inline-formula> <tex-math>$ k $</tex-math> </inline-formula>-bit message into <inline-formula> <tex-math>$r + 1$</tex-math> </inline-formula> parts. The first <inline-formula> <tex-math>$ r $</tex-math> </inline-formula> parts are each <inline-formula> <tex-math>$ b $</tex-math> </inline-formula> bits long and are assigned to different zero-correlation-zone periodic sequences. These <inline-formula> <tex-math>$ r $</tex-math> </inline-formula> sequences are then superimposed to generate a ZSP, thereby expanding the available pilot set. The remaining <inline-formula> <tex-math>$k-rb$</tex-math> </inline-formula> bits are encoded using a <inline-formula> <tex-math>$ T $</tex-math> </inline-formula>-order codebook and concatenated with the ZSP to form a complete frame for access. Moreover, we design a successive iteration then joint ordered likelihood decoder to decode up to <inline-formula> <tex-math>$ T $</tex-math> </inline-formula> UEs transmitting the same ZSP, supporting access for up to <inline-formula> <tex-math>$binom{Z}{r}cdot T$</tex-math> </inline-formula> UEs. We derive the theoretical expressions for the access failure probability (AFP) of the <inline-formula> <tex-math>$ZT$</tex-math> </inline-formula>-GFRA scheme under a shadowed-Rician fading channel. Simulation results demonstrate that, compared to the state-of-the-art schemes, our <inline-formula> <tex-math>$ZT$</tex-math> </inline-formula>-GFRA scheme achieves a significantly lower pilot collision probability and AFP under the same sequence length and SNR conditions.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"4573-4588"},"PeriodicalIF":5.8,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11229876","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-05DOI: 10.1109/tsp.2025.3628349
Christof Baeriswyl, Frédéric Waldmann, Alexander Bertrand, Reto A. Wildhaber
{"title":"Multi-Resolution Autonomous Linear State Space Filters for N-Dimensional Signals","authors":"Christof Baeriswyl, Frédéric Waldmann, Alexander Bertrand, Reto A. Wildhaber","doi":"10.1109/tsp.2025.3628349","DOIUrl":"https://doi.org/10.1109/tsp.2025.3628349","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-05DOI: 10.1109/TSP.2025.3628337
Rui Wang;Shuowen Zhang;Bruno Clerckx;Liang Liu
Beyond diagonal reconfigurable intelligent surface (BD-RIS) refers to a family of RIS architectures characterized by scattering matrices not limited to being diagonal and enables higher wave manipulation flexibility and large rate performance gain over conventional (diagonal) RIS. However, whether BD-RIS aided network is able to deliver more data volume compared to conventional RIS aided network is still questionable, because far more time may be wasted to estimate the massive channel coefficients associated with the off-diagonal entries of the BD-RIS scattering matrix. Somehow counter intuitively, for the first time in the literature, this paper rigorously proves that the channel estimation overhead in fully connected BD-RIS aided network is actually of the same order as that in the conventional RIS aided network, which was characterized in Wang et al. 2020. This amazing result stems from a key observation: for each user antenna, its cascaded channel matrix associated with one reference BD-RIS element is a scaled version of that associated with any other BD-RIS element due to the common RIS-base station (BS) channel. In other words, the number of independent unknown variables is far less than it would seem at first glance. Building upon this property, this paper manages to characterize the overhead to perfectly estimate all the channels in the ideal case without noise at the BS, and propose a two-phase estimation framework for the practical case with noise at the BS. The main message of this paper is that we can benefit from the non-diagonal scattering matrix design at a channel estimation cost similar to that in conventional RIS aided network.
超对角线可重构智能表面（BD-RIS）是指一系列RIS架构，其特点是散射矩阵不限于对角线，与传统（对角线）RIS相比，具有更高的波操作灵活性和更高的速率性能增益。然而，与传统的RIS辅助网络相比，BD-RIS辅助网络是否能够提供更多的数据量仍然值得怀疑，因为可能会浪费更多的时间来估计与BD-RIS散射矩阵的非对角线条目相关的大量通道系数。与直觉相反的是，本文在文献中首次严格证明了完全连接BD-RIS辅助网络的信道估计开销实际上与传统RIS辅助网络的信道估计开销相同，Wang et al. 2020对其进行了表征。这个惊人的结果源于一个关键的观察：对于每个用户天线，其与一个参考BD-RIS单元相关联的级联信道矩阵是由于公共ris基站（BS）信道而与任何其他BD-RIS单元相关联的级联信道矩阵的缩放版本。换句话说，独立未知变量的数量比乍一看要少得多。基于这一特性，本文设法描述了在没有BS噪声的理想情况下完美估计所有信道的开销，并为具有BS噪声的实际情况提出了一个两阶段估计框架。本文的主要信息是，我们可以从非对角散射矩阵设计中获益，而通道估计成本与传统RIS辅助网络相似。
{"title":"Low-Overhead Channel Estimation Framework for Beyond Diagonal Reconfigurable Intelligent Surface Assisted Multi-User MIMO Communication","authors":"Rui Wang;Shuowen Zhang;Bruno Clerckx;Liang Liu","doi":"10.1109/TSP.2025.3628337","DOIUrl":"10.1109/TSP.2025.3628337","url":null,"abstract":"Beyond diagonal reconfigurable intelligent surface (BD-RIS) refers to a family of RIS architectures characterized by scattering matrices not limited to being diagonal and enables higher wave manipulation flexibility and large rate performance gain over conventional (diagonal) RIS. However, whether BD-RIS aided network is able to deliver more data volume compared to conventional RIS aided network is still questionable, because far more time may be wasted to estimate the massive channel coefficients associated with the off-diagonal entries of the BD-RIS scattering matrix. Somehow counter intuitively, for the first time in the literature, this paper rigorously proves that the channel estimation overhead in fully connected BD-RIS aided network is actually of the same order as that in the conventional RIS aided network, which was characterized in Wang et al. 2020. This amazing result stems from a key observation: for each user antenna, its cascaded channel matrix associated with one reference BD-RIS element is a scaled version of that associated with any other BD-RIS element due to the common RIS-base station (BS) channel. In other words, the number of independent unknown variables is far less than it would seem at first glance. Building upon this property, this paper manages to characterize the overhead to perfectly estimate all the channels in the ideal case without noise at the BS, and propose a two-phase estimation framework for the practical case with noise at the BS. The main message of this paper is that we can benefit from the non-diagonal scattering matrix design at a channel estimation cost similar to that in conventional RIS aided network.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"4700-4717"},"PeriodicalIF":5.8,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145447585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-03DOI: 10.1109/TSP.2025.3627779
Marc Vilà-Insa;Jaume Riba
This paper extends various theoretical results from stationary data processing to cyclostationary (CS) processes under a unified framework. We first derive their asymptotic eigenbasis, which provides a link between their Fourier and Karhunen-Loève (KL) expansions, through a unitary transformation dictated by the cyclic spectrum. By exploiting this connection and the optimalities offered by the KL representation, we study the asymptotic performance of smoothing, filtering and prediction of CS processes, without the need for deriving explicit implementations. We obtain minimum mean squared error expressions that depend on the cyclic spectrum and include classical limits based on the power spectral density as particular cases. We conclude this work by applying the results to a practical scenario, in order to quantify the achievable gains of synchronous signal processing.
{"title":"Asymptotic Analysis of Synchronous Signal Processing","authors":"Marc Vilà-Insa;Jaume Riba","doi":"10.1109/TSP.2025.3627779","DOIUrl":"10.1109/TSP.2025.3627779","url":null,"abstract":"This paper extends various theoretical results from stationary data processing to cyclostationary (CS) processes under a unified framework. We first derive their asymptotic eigenbasis, which provides a link between their Fourier and Karhunen-Loève (KL) expansions, through a unitary transformation dictated by the cyclic spectrum. By exploiting this connection and the optimalities offered by the KL representation, we study the asymptotic performance of smoothing, filtering and prediction of CS processes, without the need for deriving explicit implementations. We obtain minimum mean squared error expressions that depend on the cyclic spectrum and include classical limits based on the power spectral density as particular cases. We conclude this work by applying the results to a practical scenario, in order to quantify the achievable gains of synchronous signal processing.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"5032-5046"},"PeriodicalIF":5.8,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145434158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1109/tsp.2025.3626934
Shanshan Zou, Ziping Zhao
{"title":"Factor-Based Large Covariance Matrix Estimation: Nonconvex Optimization and Statistical Guarantees","authors":"Shanshan Zou, Ziping Zhao","doi":"10.1109/tsp.2025.3626934","DOIUrl":"https://doi.org/10.1109/tsp.2025.3626934","url":null,"abstract":"","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"32 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1109/TSP.2025.3627602
Fengdeng Gu;Chang Gao;Rongrong Wang;Pramod K. Varshney;Junkun Yan;Hongwei Liu
Distributed detection methods based on local observation censoring are widely employed in systems with asynchronous sensors owing to their low communication costs and high surveillance efficiency. However, the incomplete utilization of Doppler information along with the deficient modeling of the track distribution exposes conventional methods to performance degradation of both correlation and detection. To enhance the correlation performance subject to the above issues, an efficient plot-correlation module aided by Location-Doppler coupling is proposed. Based on the search procedure in the Doppler domain and the generalized likelihood ratio test, this module can simultaneously align the plots originating from the target and disambiguate the Doppler velocity measured by each sensor. Then, by modeling the distribution of the tracks from the plot-correlation module, two advanced detectors for the tracks based on parameter priors are derived using likelihood ratio test to overcome the detection performance degradation. Additionally, the signal-to-noise ratio is decoupled from the detectors via approximation algorithms to assure their practicability. Finally, extensive simulations are performed under different conditions and the results demonstrate the superiority of the proposed methods.
{"title":"Distributed Detection for Asynchronous Sensors Aided by Location-Doppler Coupling and Track Distribution Modeling","authors":"Fengdeng Gu;Chang Gao;Rongrong Wang;Pramod K. Varshney;Junkun Yan;Hongwei Liu","doi":"10.1109/TSP.2025.3627602","DOIUrl":"10.1109/TSP.2025.3627602","url":null,"abstract":"Distributed detection methods based on local observation censoring are widely employed in systems with asynchronous sensors owing to their low communication costs and high surveillance efficiency. However, the incomplete utilization of Doppler information along with the deficient modeling of the track distribution exposes conventional methods to performance degradation of both correlation and detection. To enhance the correlation performance subject to the above issues, an efficient plot-correlation module aided by Location-Doppler coupling is proposed. Based on the search procedure in the Doppler domain and the generalized likelihood ratio test, this module can simultaneously align the plots originating from the target and disambiguate the Doppler velocity measured by each sensor. Then, by modeling the distribution of the tracks from the plot-correlation module, two advanced detectors for the tracks based on parameter priors are derived using likelihood ratio test to overcome the detection performance degradation. Additionally, the signal-to-noise ratio is decoupled from the detectors via approximation algorithms to assure their practicability. Finally, extensive simulations are performed under different conditions and the results demonstrate the superiority of the proposed methods.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"4622-4637"},"PeriodicalIF":5.8,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145412198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1109/TSP.2025.3627252
Ori Peleg;Natalie Lang;Dan Ben Ami;Stefano Rini;Nir Shlezinger;Kobi Cohen
Federated learning (FL) enables multiple edge devices to collaboratively train a machine learning model without the need to share potentially private data. Federated learning proceeds through iterative exchanges of model updates, which pose two key challenges: (i) the accumulation of privacy leakage over time and (ii) communication latency. These two limitations are typically addressed separately— (i) via perturbed updates to enhance privacy and (ii) user selection to mitigate latency—both at the expense of accuracy. In this work, we propose a method that jointly addresses the accumulation of privacy leakage and communication latency via active user selection, aiming to improve the trade-off among privacy, latency, and model performance. To achieve this, we construct a reward function that accounts for these three objectives. Building on this reward, we propose a multi-armed bandit (MAB)-based algorithm, termed privacy-aware active user selection (PAUSE) – which dynamically selects a subset of users each round while ensuring bounded overall privacy leakage. We establish a theoretical analysis, systematically showing that the regret growth rate of PAUSE follows that of the best-known rate in MAB literature. To address the complexity overhead of active user selection, we propose a simulated annealing-based relaxation of PAUSE and analyze its ability to approximate the reward-maximizing policy under reduced complexity. We numerically validate the privacy leakage, associated improved latency, and accuracy gains of our methods for the federated training in various scenarios.
{"title":"PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning","authors":"Ori Peleg;Natalie Lang;Dan Ben Ami;Stefano Rini;Nir Shlezinger;Kobi Cohen","doi":"10.1109/TSP.2025.3627252","DOIUrl":"10.1109/TSP.2025.3627252","url":null,"abstract":"Federated learning (FL) enables multiple edge devices to collaboratively train a machine learning model without the need to share potentially private data. Federated learning proceeds through iterative exchanges of model updates, which pose two key challenges: (i) the accumulation of privacy leakage over time and (ii) communication latency. These two limitations are typically addressed separately— (i) via perturbed updates to enhance privacy and (ii) user selection to mitigate latency—both at the expense of accuracy. In this work, we propose a method that jointly addresses the accumulation of privacy leakage and communication latency via active user selection, aiming to improve the trade-off among privacy, latency, and model performance. To achieve this, we construct a reward function that accounts for these three objectives. Building on this reward, we propose a multi-armed bandit (MAB)-based algorithm, termed <underline>p</u>rivacy-aware <underline>a</u>ctive <underline>u</u>ser <underline>se</u>lection (PAUSE) – which dynamically selects a subset of users each round while ensuring bounded overall privacy leakage. We establish a theoretical analysis, systematically showing that the regret growth rate of PAUSE follows that of the best-known rate in MAB literature. To address the complexity overhead of active user selection, we propose a simulated annealing-based relaxation of PAUSE and analyze its ability to approximate the reward-maximizing policy under reduced complexity. We numerically validate the privacy leakage, associated improved latency, and accuracy gains of our methods for the federated training in various scenarios.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"4556-4572"},"PeriodicalIF":5.8,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145404064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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