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        <title>Frontiers in Signal Processing | Signal Processing for Communications section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/signal-processing/sections/signal-processing-for-communications</link>
        <description>RSS Feed for Signal Processing for Communications section in the Frontiers in Signal Processing journal | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-05-12T06:24:07.622+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2026.1827692</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2026.1827692</link>
        <title><![CDATA[Editorial: Emerging optimization, learning and signal processing for next-generation wireless communications and networking]]></title>
        <pubdate>2026-04-09T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Dionysis Kalogerias</author><author>Le Liang</author><author>Mark Eisen</author><author>Athina Petropulu</author><author>Leandros Tassiulas</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2026.1764383</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2026.1764383</link>
        <title><![CDATA[Airborne IMT users in precision agriculture: Monte-Carlo analysis of UAV interference in 694–2690 bands]]></title>
        <pubdate>2026-03-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Alexandr Solochshenko</author><author>Karina Turzhanova</author><author>Alexander Pastukh</author><author>Valery Tikhvinskiy</author><author>Yelizaveta Vitulyova</author>
        <description><![CDATA[The integration of unmanned aerial vehicles (UAVs) into precision agriculture, as envisioned in the agricultural systems, promises significant gains in crop monitoring, yield forecasting, and targeted agro-technical interventions. However, the use of IMT frequency bands for real-time UAV communications introduces new spectrum sharing and compatibility challenges. Unlike terrestrial user equipment, airborne agricultural drones operate always outdoors, above the base-station downtilt, with predominantly line-of-sight (LoS) propagation to multiple cells, drastically altering compatibility conditions and potentially increasing interference to other operators. This paper proposes a Monte Carlo-based simulation framework analysis of interference generated by such UAVs in IMT frequency allocations across 694–2690 MHz. Simulations model rural and urban macrocell deployments typical of large-scale farmlands, incorporating 3D antenna patterns, altitude-dependent air-to-ground channel models, realistic LTE/NR power-control schemes, and UAV operational patterns. Key metrics include aggregate uplink interference at victim cells, downlink degradation at UAVs, and cross-link interference in TDD systems. Results show that even low-power UAV transmissions can exceed harmful interference thresholds in multiple adjacent-channel cells. Operational recommendations are provided to ensure coexistence of precision-agriculture UAVs with terrestrial IMT networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2026.1783015</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2026.1783015</link>
        <title><![CDATA[Correction: Convergence analysis of hyperparameter-free MCC-based channel-estimation for mmWave MIMO systems]]></title>
        <pubdate>2026-02-03T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Vimal Bhatia</author><author>Rajat Kumar</author><author>Rangeet Mitra</author><author>Sandesh Jain</author><author>Vidya Bhasker Shukla</author><author>K. Venkateswaran</author><author>Ondrej Krejcar</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2025.1709070</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2025.1709070</link>
        <title><![CDATA[Convergence analysis of hyperparameter-free MCC-based channel estimation for mmWave MIMO systems]]></title>
        <pubdate>2026-01-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Vimal Bhatia</author><author>Rajat Kumar</author><author>Rangeet Mitra</author><author>Sandesh Jain</author><author>Vidya Bhasker Shukla</author><author>K. Venkateswaran</author><author>Ondrej Krejcar</author>
        <description><![CDATA[Accurate channel-estimation algorithms are critical for enhancing the throughput of wireless communication systems, including millimetre wave (mmWave) multiple-input multiple-output (MIMO) systems, where precise channel knowledge enables reliable signal detection and beamforming. In practical wireless environments, impulsive non-Gaussian noise with unknown statistics often occurs due to electromagnetic interference and harsh propagation conditions, significantly degrading estimation accuracy and overall system performance. In this context, the maximum correntropy criterion (MCC) has emerged as an attractive solution for robust channel estimation that outperforms state-of-the-art algorithms. However, the MCC-based algorithm’s performance is sensitive to the tuning of hyperparameters, which is challenging in the presence of non-Gaussian noise, such as impulsive noise (IN). Furthermore, a recent genre of kernel width sampling methods makes MCC hyperparameter-free and allows for asymptotic convergence to the squared-error performance of MCC with the ideal kernel width. To ensure their practical applicability, convergence analysis is essential to theoretically guarantee stability and performance under various IN scenarios. This study presents convergence analysis of hyperparameter-free MCC-based channel estimation for mmWave MIMO systems considering various IN scenarios. To validate the theoretical analysis, simulations are conducted on practical mmWave MIMO system models. Simulation results closely match the analytical findings, which confirms the accuracy and effectiveness of the analysis we here present.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2025.1700979</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2025.1700979</link>
        <title><![CDATA[MI-based beamforming optimization framework for integrated sensing and communication]]></title>
        <pubdate>2025-11-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhiwei Pu</author><author>Fan Chen</author>
        <description><![CDATA[This article proposes a novel mutual information (MI)-based beamforming framework for integrated sensing and communication (ISAC) systems in the Internet of Vehicles (IoV). The framework addresses the challenges posed by diverse optimization criteria and the suboptimal performance degradation often resulting from normalization methods. We first analyze a time-division multiplexing (TDM) signal model that facilitates both target detection and communication. Subsequently, we introduce a general signal model with integrated beamforming, where communication users simultaneously function as sensing targets. For each model, we formulate an optimization problem to maximize the system MI under a total power constraint. For the TDM model, we propose a Joint Optimization Dual Gradient Ascent algorithm. This method involves constructing an augmented Lagrangian function, computing the gradients for sensing and communication MI separately, and iteratively updating the beamforming vectors using gradient ascent. For the more complex general model, which presents an NP-hard problem, we tackle the non-convex objective function via the Minorization–Maximization (MM) algorithm, obtaining a solution through numerical optimization. Numerical results demonstrate that the proposed framework effectively evaluates the system’s sensing-communication performance trade-off and outperforms classical water-filling algorithms. This work thus provides a new and effective paradigm for ISAC system optimization.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2025.1608347</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2025.1608347</link>
        <title><![CDATA[Reinforcement learning, rule-based, or generative AI: a comparison of model-free Wi-Fi slicing approaches]]></title>
        <pubdate>2025-05-26T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Rafael Rosales</author><author>Dave Cavalcanti</author>
        <description><![CDATA[Resource allocation techniques are key to providing Quality-of-Service guarantees. Wi-Fi standards define features enabling the allocation of radio resources across time, frequency, and link band. However, radio resource slicing, as implemented in 5G cellular networks, is not native to Wi-Fi. A few reinforcement learning (RL) approaches have been proposed for Wi-Fi resource allocation and demonstrated using analytical models where the reward gradient with respect to the model parameters is accessible—i.e., with a differentiable Wi-Fi network model. In this work, we implement—and release under an Apache 2.0 license—a state-of-the-art, state-augmented constrained optimization method using a policy-gradient RL algorithm that does not require a differentiable model, to assess model-free RL-based slicing for Wi-Fi frequency resource allocation. We compare this with six model-free baselines: three RL algorithms (REINFORCE, A2C, PPO), two rule-based heuristics (Uniform, Proportional), and a generative AI policy using a commercial foundational Large Language Model (LLM). For rapid RL training, a simple, non-differentiable network model was used. To evaluate the policies, we use an ns-3-based Wi-Fi 6 simulator with a slice-aware MAC. Evaluations were conducted in two traffic scenarios: A) a periodic pattern with one constant low-throughput slice and two high-throughput slices toggled sequentially, and B) a random walk scenario for realism. Results show that, on average—in terms of the trade-off between total throughput and a packet-latency-based metric—the uniform split and LLM-based policy perform best, appearing on the Pareto front in both scenarios. The proportional policy only appears on the front in the periodic case. Our state-augmented constrained approach based on REINFORCE (SAC-RE) is on the second Pareto front for the random walk case, outperforming vanilla REINFORCE. In the periodic scenario, vanilla REINFORCE achieves better throughput—with a latency trade-off—and is co-located with SAC-RE on the second front. Interestingly, the LLM-based policy—neither trained nor fine-tuned on any custom data—consistently appears on the first Pareto front, offering higher objective values at some latency cost. Unlike uniform slicing, its behavior is dynamically adjustable via prompt engineering.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2023.1297945</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2023.1297945</link>
        <title><![CDATA[A mini-review of signal processing techniques for RIS-assisted near field THz communication]]></title>
        <pubdate>2024-01-08T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Vaishali Sharma</author><author>Navneet Garg</author><author>Sanjeev Sharma</author><author>Vimal Bhatia</author>
        <description><![CDATA[Reflecting Intelligent Surfaces (RISs) are reshaping the landscape of wireless communications, particularly in the terahertz (THz) frequency bands, offering promising solutions to inherent challenges in the bands. THz communication boasts bandwidths exceeding 100 GHz, leading to data rates potentially in the terabits per second (Tbps) range, thereby making it an attractive proposition for wireless communications, imaging, and sensing. However, benefits come with challenges, including significant molecular absorption, scattering, diffraction, and hardware limitations. Moreover, as bandwidth in the THz range increases, so does the difficulty of signal processing at Nyquist rate. RIS emerges as a game-changer for 6G and beyond by providing programmable reflecting elements that can adaptively modify the phases and amplitudes of incident signals, enabling precision in directing THz waves and enhancing received signal strength. Such capabilities can significantly mitigate path loss and atmospheric absorption challenges. Furthermore, inherent pencil beamforming capabilities of RIS lead to optimized energy utilization. Major challenge in THz communications is the pressing needs for efficient algorithms for robust THz transceivers and optimizing RIS elements. This review describes the integration of RIS and near-field THz communications, highlighting their future potential and challenges for the next-generation wireless networks. In this article, a comprehensive understanding of the complexities and nuances of near-field propagation in 6G networks, especially as the technology shifts towards extremely large-scale antenna arrays (ELAA). Additionally, it will introduce the transformative potential of sub-Nyquist rate signal processing and artificial intelligence (AI) offering innovative solutions to address the inherent challenges of 6G communication, especially in channel estimation and beamforming strategies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.1067055</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.1067055</link>
        <title><![CDATA[Performance analysis of code division multiplexing communication under evaporation duct environment]]></title>
        <pubdate>2022-11-22T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Wenjing Liu</author><author>Xiqing Liu</author><author>Shi Yan</author><author>Linglan Zhao</author><author>Mugen Peng</author>
        <description><![CDATA[The evaporation duct is an effective means for realizing non-line-of-sight (NLOS) wireless transmission over the sea. However, the effects of marine weather conditions on electromagnetic propagation have rarely been studied. In this study, the influence of the marine atmospheric environment on electromagnetic propagation was analyzed through numerical simulation. Additionally, the impacts of antenna height, transmission distance, and electromagnetic wave frequency on path loss were studied. Finally, the link capacity of the code division multiplexing (CDM) communication system in the evaporation duct environment was studied via numerical analysis and simulations. Simulation results demonstrated that CDM communication technology can improve the link capacity under an evaporation duct compared with that of the spread-spectrum communication technology.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.965551</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.965551</link>
        <title><![CDATA[Pseudo-doppler aided cancellation of self-interference in full-duplex communications]]></title>
        <pubdate>2022-08-16T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Dongsheng Zheng</author><author>Yuli Yang</author>
        <description><![CDATA[In this work, a novel scheme is proposed to enhance the self-interference (SI) cancellation in full-duplex communications. Beyond conventional SI cancellation schemes that rely on the SI suppression, our proposed scheme exploits periodic antenna switching to generate the pseudo-Doppler effect, thus completely removing the SI at the fundamental frequency. In this way, the desired signal is readily obtained through a low-pass filter. For the purpose of performance evaluation, the SI cancellation capability is defined as the difference between the output signal-to-interference-plus-noise ratio (SINR) and the input SINR. Theoretical formulations and numerical results validate that our pseudo-Doppler aided scheme has higher SI cancellation capability than the conventional SI suppression schemes. Moreover, the impact of the SI suppression achieved by conventional schemes and the influence of antenna switching timing difference on the practical implementation of the proposed scheme are investigated, to further substantiate the validity of our pseudo-Doppler aided SI cancellation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.915567</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.915567</link>
        <title><![CDATA[Deep Reinforcement Learning-Based Optimization for RIS-Based UAV-NOMA Downlink Networks (Invited Paper)]]></title>
        <pubdate>2022-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Shiyu Jiao</author><author>Ximing Xie</author><author>Zhiguo Ding</author>
        <description><![CDATA[This study investigates the application of deep deterministic policy gradient (DDPG) to reconfigurable intelligent surface (RIS)-based unmanned aerial vehicles (UAV)-assisted non-orthogonal multiple access (NOMA) downlink networks. The deployment of UAV equipped with a RIS is important, as the UAV increases the flexibility of the RIS significantly, especially for the case of users who have no line-of-sight (LoS) path to the base station (BS). Therefore, the aim of this study is to maximize the sum-rate by jointly optimizing the power allocation of the BS, the phase shifting of the RIS, and the horizontal position of the UAV. The formulated problem is non-convex, the DDPG algorithm is utilized to solve it. The computer simulation results are provided to show the superior performance of the proposed DDPG-based algorithm.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.867388</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.867388</link>
        <title><![CDATA[Adaptive Discrete Motion Control for Mobile Relay Networks]]></title>
        <pubdate>2022-07-06T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Spilios Evmorfos</author><author>Dionysios Kalogerias</author><author>Athina Petropulu</author>
        <description><![CDATA[We consider the problem of joint beamforming and discrete motion control for mobile relaying networks in dynamic channel environments. We assume a single source-destination communication pair. We adopt a general time slotted approach where, during each slot, every relay implements optimal beamforming and estimates its optimal position for the subsequent slot. We assume that the relays move in a 2D compact square region that has been discretized into a fine grid. The goal is to derive discrete motion policies for the relays, in an adaptive fashion, so that they accommodate the dynamic changes of the channel and, therefore, maximize the Signal-to-Interference + Noise Ratio (SINR) at the destination. We present two different approaches for constructing the motion policies. The first approach assumes that the channel evolves as a Gaussian process and exhibits correlation with respect to both time and space. A stochastic programming method is proposed for estimating the relay positions (and the beamforming weights) based on causal information. The stochastic program is equivalent to a set of simple subproblems and the exact evaluation of the objective of each subproblem is impossible. To tackle this we propose a surrogate of the original subproblem that pertains to the Sample Average Approximation method. We denote this approach as model-based because it adopts the assumption that the underlying correlation structure of the channels is completely known. The second method is denoted as model-free, because it adopts no assumption for the channel statistics. For the scope of this approach, we set the problem of discrete relay motion control in a dynamic programming framework. Finally we employ deep Q learning to derive the motion policies. We provide implementation details that are crucial for achieving good performance in terms of the collective SINR at the destination.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.864392</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.864392</link>
        <title><![CDATA[A Tutorial on Bandit Learning and Its Applications in 5G Mobile Edge Computing (Invited Paper)]]></title>
        <pubdate>2022-05-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sige Liu</author><author>Peng Cheng</author><author>Zhuo Chen</author><author>Branka Vucetic</author><author>Yonghui Li</author>
        <description><![CDATA[Due to the rapid development of 5G and Internet-of-Things (IoT), various emerging applications have been catalyzed, ranging from face recognition, virtual reality to autonomous driving, demanding ubiquitous computation services beyond the capacity of mobile users (MUs). Mobile cloud computing (MCC) enables MUs to offload their tasks to the remote central cloud with substantial computation and storage, at the expense of long propagation latency. To solve the latency issue, mobile edge computing (MEC) pushes its servers to the edge of the network much closer to the MUs. It jointly considers the communication and computation to optimize network performance by satisfying quality-of-service (QoS) and quality-of-experience (QoE) requirements. However, MEC usually faces a complex combinatorial optimization problem with the complexity of exponential scale. Moreover, many important parameters might be unknown a-priori due to the dynamic nature of the offloading environment and network topology. In this paper, to deal with the above issues, we introduce bandit learning (BL), which enables each agent (MU/server) to make a sequential selection from a set of arms (servers/MUs) and then receive some numerical rewards. BL brings extra benefits to the joint consideration of offloading decision and resource allocation in MEC, including the matched mechanism, situation awareness through learning, and adaptability. We present a brief tutorial on BL of different variations, covering the mathematical formulations and corresponding solutions. Furthermore, we provide several applications of BL in MEC, including system models, problem formulations, proposed algorithms and simulation results. At last, we introduce several challenges and directions in the future research of BL in 5G MEC.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.788943</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.788943</link>
        <title><![CDATA[A Robust Security Task Offloading in Industrial IoT-Enabled Distributed Multi-Access Edge Computing]]></title>
        <pubdate>2022-04-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Eric Gyamfi</author><author>Anca Jurcut</author>
        <description><![CDATA[The rapid increase in the Industrial Internet of Things (IIoT) use cases plays a significant role in Industry 4.0 development. However, IIoT systems face resource constraints problems and are vulnerable to cyberattacks due to their inability to implement existing sophisticated security systems. One way of alleviating these resource constraints is to utilize multi-access edge computing (MEC) to provide computational resources at the network edge to execute the security applications. To provide resilient security for IIoT using MEC, the offloading latency, synchronization time, and turnaround time must be optimized to provide real-time attack detection. Hence, this paper provides a novel adaptive machine learning–based security (MLS) task offloading (ASTO) mechanism to ensure that the connectivity between the MEC server and IIoT is secured and guaranteed. We explored the trade-off between the limited computing capacity and high cloud computing latency to propose an ASTO, where MEC and IIoT can collaborate to provide optimized MLS to protect the network. In the proposed system, we converted the MLS task offloading and synchronization problem into an equivalent mathematical model, which can be solved by applying Markov transition probability and clock offset estimation using maximum likelihood. Our extensive simulations show that the proposed algorithm provides robust security for the IIoT network with low latency, synchronization accuracy, and energy efficiency.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2022.837870</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2022.837870</link>
        <title><![CDATA[Compressive Sensing-Based Secure Uplink Grant-Free Systems]]></title>
        <pubdate>2022-02-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuanchen Wang</author><author>Eng Gee Lim</author><author>Yanfeng Zhang</author><author>Bowen Zhong</author><author>Rui Pei</author><author>Xu Zhu</author>
        <description><![CDATA[Compressive sensing (CS) has been extensively employed in uplink grant-free communications, where data generated from different active users are transmitted to a base station (BS) without following the strict access grant process. Nevertheless, the state-of-the-art CS algorithms rely on a highly limited category of measurement matrix, that is, pilot matrix, which may be analyzed by an eavesdropper (Eve) to infer the user’s channel information. Thus, the physical layer security becomes a critical issue in uplink grant-free communications. In this article, the channel reciprocity in time-division duplex systems is utilized to design environment-aware (EA) pilots derived from transmission channels to prevent eavesdroppers from acquiring users’ channel information. The simulation results show that the proposed EA-based pilot approach possesses a high level of security by scrambling the Eve’s normalized mean square error performance of channel estimation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.820617</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.820617</link>
        <title><![CDATA[Beamspace ESPRIT for mmWave Channel Sensing: Performance Analysis and Beamformer Design]]></title>
        <pubdate>2022-02-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sina Shahsavari</author><author>Pulak Sarangi</author><author>Piya Pal</author>
        <description><![CDATA[In this paper, we consider the beamspace ESPRIT algorithm for Millimeter-Wave (mmWave) channel sensing. We provide a non-asymptotic analysis of the beamspace ESPRIT algorithm. We derive a deterministic upper bound for the matching distance error between the true angle of arrival (AoA) of the channel paths and the estimated AoA considering a bounded noise model. Additionally, we leverage the insight obtained from our theoretical analysis to propose a novel max-min criterion for beamformer design which can enhance the performance of mmWave channel estimation algorithms, including beamspace ESPRIT. We consider a family of multi-resolution beamformers which can be implemented using phase shifters and introduce a design scheme for the optimal beamformers from this family with respect to the proposed max-min criteria. We can guarantee a minimum beamforming gain uniformly over a region of possible multipath directions, which can lead to more robust channel estimation. We provide several numerical experiments to verify our theoretical claims and demonstrate the superior performance of the proposed beamformers compared to existing beamformer design criteria.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.776825</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.776825</link>
        <title><![CDATA[Distributed Proximal Splitting Algorithms with Rates and Acceleration]]></title>
        <pubdate>2022-01-25T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Laurent Condat</author><author>Grigory Malinovsky</author><author>Peter Richtárik</author>
        <description><![CDATA[We analyze several generic proximal splitting algorithms well suited for large-scale convex nonsmooth optimization. We derive sublinear and linear convergence results with new rates on the function value suboptimality or distance to the solution, as well as new accelerated versions, using varying stepsizes. In addition, we propose distributed variants of these algorithms, which can be accelerated as well. While most existing results are ergodic, our nonergodic results significantly broaden our understanding of primal–dual optimization algorithms.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.814129</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.814129</link>
        <title><![CDATA[Analysis of a 2D Representation for CPS Anomaly Detection in a Context-Based Security Framework]]></title>
        <pubdate>2022-01-21T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sara Baldoni</author><author>Marco Carli</author><author>Federica Battisti</author>
        <description><![CDATA[In this contribution, a flexible context-based security framework is proposed by exploring two types of context: distributed and local. While the former consists in processing information from a set of spatially distributed sources, the second accounts for the local environment surrounding the monitored system. The joint processing of these two types of information allows the identification of the anomaly cause, differentiating between natural and attack-related events, and the suggestion of the best mitigation strategy. In this work, the proposed framework is applied the Cyber Physical Systems scenario. More in detail, we focus on the distributed context analysis investigating the definition of a 2D representation of network traffic data. The suitability of four representation variables has been evaluated, and the variable selection has been performed.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.763299</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.763299</link>
        <title><![CDATA[Static: Low Frequency Energy Harvesting and Power Transfer for the Internet of Things]]></title>
        <pubdate>2022-01-19T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ashok Samraj Thangarajan</author><author>Thien Duc Nguyen</author><author>Mengyao Liu</author><author>Sam Michiels</author><author>Fan Yang</author><author>Ka Lok Man</author><author>Jieming Ma</author><author>Wouter Joosen</author><author>Danny Hughes</author>
        <description><![CDATA[The Internet of Things (IoT) is composed of wireless embedded devices which sense, analyze and communicate the state of the physical world. To achieve truly wireless operation, today’s IoT devices largely depend on batteries for power. However, this leads to high maintenance costs due to battery replacement, or the environmentally damaging concept of disposable devices. Energy harvesting has emerged as a promising approach to delivering long-life, environmentally friendly IoT device operation. However, with the exception of solar harvesting, it remains difficult to ensure sustainable system operation using environmental power alone. This paper tackles this problem by contributing Static, a Radio Frequency (RF) energy harvesting and wireless power transfer platform. Our approach comprises autonomous energy management techniques, adaptive power transfer algorithms and an open-source hardware reference platform to enable further research. We evaluate Static in laboratory conditions and show that 1) ambient RF energy harvesting can deliver sustainable operation using common industrial sources, while 2) wireless power transfer provides a simple means to power motes at a range of up to 3 m through a variety of media.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.721682</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.721682</link>
        <title><![CDATA[Precoded Cluster Hopping for Multibeam GEO Satellite Communication Systems]]></title>
        <pubdate>2021-10-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Eva Lagunas</author><author>Mirza Golam Kibria</author><author>Hayder Al-Hraishawi</author><author>Nicola Maturo</author><author>Symeon Chatzinotas</author>
        <description><![CDATA[Beam hopping (BH) and precoding are two trending technologies for high-throughput satellite (HTS) systems. While BH enables the flexible adaptation of the offered capacity to the heterogeneous demand, precoding aims at boosting the spectral efficiency. In this study, we consider an HTS system that employs BH in conjunction with precoding in an attempt to bring the benefits of both in one. In particular, we propose the concept of cluster hopping (CH), where a set of adjacent beams are simultaneously illuminated with the same frequency resource. On this line, we propose an efficient time–space illumination pattern design, where we determine the set of clusters that shall be illuminated simultaneously at each hopping event along with the dwelling time. The CH time–space illumination pattern design formulation is shown to be theoretically intractable due to the combinatorial nature of the problem and the impact of the actual illumination design on the resulting interference. For this, we make some design decisions on the beam–cluster design that open the door to a less complex still well-performing solution. Supporting results based on numerical simulations are provided which validate the effectiveness of the proposed CH concept and a time–space illumination pattern design with respect to benchmark schemes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/frsip.2021.664331</guid>
        <link>https://www.frontiersin.org/articles/10.3389/frsip.2021.664331</link>
        <title><![CDATA[Grand Challenges in Signal Processing for Communications]]></title>
        <pubdate>2021-04-12T00:00:00Z</pubdate>
        <category>Specialty Grand Challenge</category>
        <author>Changyang She</author><author>Peng Cheng</author><author>Ang Li</author><author>Yonghui Li</author>
        <description></description>
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