This paper proposes a new #reconfigurable #intelligent #surface (#RIS)-aided #differential #chaos #shift #keying (#DCSK) (#RIS-#DCSK) scheme in this letter. The proposed scheme deploys an RIS close to the transmitter antenna to enhance the #signal-#to-#noise ratio (#SNR) of the received signal, significantly improving the BER performance. They analyze the #bit-#error-#rate (#BER) performance of the RIS-DCSK scheme and demonstrate its superiority. Furthermore, they propose two #performance-#enhanced #algorithms to further improve the BER performance, though with increased computational complexity. ----@Xiangming Cai, Chongwen Huang, Jiancheng An, @Weikai Xu, @Lin Wang, Chau Yuen More details can be found at this link: https://lnkd.in/gQQsQ-2h
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This page aims to share the latest research in wireless communications.
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This channel aims to share the latest research in wireless communications. We look forward to exploring these topics together and welcoming your feedback. Please feel free to like, retweet, comment or favorite to stay engaged in the discussion.
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This work provides a #statistical #fading #model that describes user-induced changes in received power specifically for #multipath #components (#MPCs). The model is derived and validated empirically using an extensive set of #wideband and #ultra-#wideband measurement data. Since the localization performance of #multipath-#enhanced #device-#free #localization (#MDFL) systems strongly depends on the information about the propagation paths within the wireless network, they further propose a #Bayesian #calibration #approach that estimates the location of the reflection points of MPCs caused by #single-#bounce #reflections. For MPCs caused by single-bounce reflections, the solution space of possible locations of reflection points is constrained to the delay ellipse, which allows the formulation of a computationally efficient one-dimensional estimation problem.----Martin Schmidhammer, Christian Gentner, @Michael Walter, Stephan Sand, @Benjamin Siebler, @Uwe-Carsten Fiebig More details can be found at this link: https://lnkd.in/gVaABDMn
Empirical Fading Model and Bayesian Calibration for Multipath-Enhanced Device-Free Localization
ieeexplore.ieee.org
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This paper proposes a #coded #reactive #straggler #mitigation with an #uncoded and a #coded #phase for #distributed #matrix-#matrix #multiplications. Specifically, in the uncoded phase of the proposed strategy, the master distributes the computational job without redundancy among the workers. After a predetermined waiting time, the master cancels the remaining tasks. It then encodes the remaining tasks and distributes them among the workers. In the #uncoded #phase, in addition to the #conventional #erasure #model, where workers can communicate only once, we consider #multi-#message #communication (#MMC) model to exploit the partial works done by workers. The optimum waiting time for the uncoded phase and the optimum code rate for the coded phase are also obtained. ----Maryam Haghighi Ardakani, Masoud Ardakani, Chintha Tellambura More details can be found at this link: https://lnkd.in/gDWM-pYc
Coded Reactive Stragglers Mitigation in Distributed Computing Systems
ieeexplore.ieee.org
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This article aim to unfold the opportunities that can be reaped from integrating large #generative #artificial #intelligence (#GenAI) models into the #Telecom domain. In particular, the authors first highlight the applications of #large #GenAI models in #future #wireless #networks, defining potential use-cases and revealing insights on the associated theoretical and practical challenges. Furthermore, they unveil how #6G can open up new opportunities through connecting #multiple #on-#device large GenAI models, and hence, paves the way to the collective intelligence paradigm. Finally, they put a forward-looking vision on how large GenAI models will be the key to realizing #self-#evolving #networks.----Lina Bariah, @Qiyang Zhao, @Hang Zou, @Yu Tian, Faouzi Bader, Merouane Debbah More details can be found at this link: https://lnkd.in/gnpUuacK
Large Generative AI Models for Telecom: The Next Big Thing?
ieeexplore.ieee.org
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This work presents a #wireless #localization method that operates on #self-#supervised and #unlabeled #channel #estimates. Their self-supervising method learns #general-#purpose #channel #features #robust to fading and system impairments. Learned representations are easily transferable to new environments and ready to use for other wireless downstream tasks. To the best of their knowledge, the proposed method is the first #joint-#embedding self-supervised approach to forsake the dependency on #contrastive #channel #estimates. Their approach outperforms #fully-#supervised techniques in #small #data #regimes under #fine-#tuning and, in some cases, linear evaluation. They assess the performance in centralized and distributed massive #multiple-#input #multiple-#output (#MIMO) systems for multiple datasets. ----Artan Salihu, Markus Rupp, Stefan Schwarz More details can be found at this link: https://lnkd.in/gkRvksea
Self-Supervised and Invariant Representations for Wireless Localization
ieeexplore.ieee.org
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This paper investigates the problem of #reconfigurable #intelligent #surfaces (#RISs)-aided localization of a #user #equipment (#UE) under #line-#of-#sight (#LoS) blockage in the presence of #RIS #pixel #failures, considering the challenging #single-#input #single-#output (#SISO) scenario. The authors first explore the impact of such failures on accuracy through #misspecified #Cramér-#Rao #bound (#MCRB) analysis, which reveals severe performance loss with even a small percentage of pixel failures. To remedy this issue, they develop two strategies for #joint #localization #and #failure #diagnosis (#JLFD) to detect #failing #pixels while simultaneously locating the UE with high accuracy. The first strategy relies on ℓ 1 -regularization through the exploitation of failure sparsity. The second strategy detects the failures one by one by solving a multiple-hypothesis testing problem at each iteration, successively enhancing localization and diagnosis accuracy. ----Cüneyd Öztürk, Musa Furkan Keskin, Vincenzo Sciancalepore, Henk Wymeersch, Sinan Gezici More details can be found at this link: https://lnkd.in/g7MVtzvQ
RIS-aided Localization under Pixel Failures
ieeexplore.ieee.org
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This paper describes a free space #frequency #diverse #array (#FDA)-based #spatial #data #focusing (#SDF) (#FDA-#SDF) system model for #2-#dimensional range-angle-based focusing, including a generalized #multi-#purpose baseband approach for #time-#invariant #FDA, complemented by SDF processing for improved spatial focusing precision and reduced array size. Comprehensive #analytical #derivations – #general for any frequency offset configuration – describe the geographical FDA-SDF properties and design rules, such as geocast delivery zone steering, location, uniqueness, and size.----Guylian Molineaux, PhD, Francois Horlin, @Philippe De Doncker, Julien Sarrazin More details can be found at this link: https://lnkd.in/gRaZxUkY
A Spatial Data Focusing and Generalized Time-invariant Frequency Diverse Array Approach for High Precision Range-angle-based Geocasting
ieeexplore.ieee.org
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This article proposes challenges related to #multi-#connectivity (#MC) in #non-#terrestrial #networks (#NTNs) are discussed, and solutions to the identified challenges. NTNs will complement #terrestrial #networks (#TNs) in #5G and beyond, which can be attributed to recent deployment and standardization activities. Maximizing the efficiency of #NTN #communications is critical to unlock its full potential and reap its numerous benefits. One method to make communications more efficient is by the usage of #multi-#connectivity (#MC), which allows a user to connect to multiple base stations simultaneously. It is standardized and widely used for TNs, but for MC to be used in the NTN environment, several challenges must be overcome. ----Mikko Majamaa More details can be found at this link: https://lnkd.in/gcEYNcQE
Toward Multi-Connectivity in Beyond 5G Non-Terrestrial Networks: Challenges and Possible Solutions
ieeexplore.ieee.org
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Most existing adversarial attack methods generally rely on ideal assumptions, which is unreasonable for practical applications. In this letter, a practical #threat #model which utilizes #adversarial #attacks for anti-eavesdropping is proposed and a physical #intra-#class #universal #adversarial #perturbation (#IC-#UAP) crafting method against DL-based wireless signal classifiers is then presented. First, an IC-UAP algorithm is proposed based on the threat model to craft a stronger UAP attack against the samples in a given class from a batch of samples in the class. Then, the authors develop a #physical #attack #algorithm based on the IC-UAP method, in which perturbations are optimized under random shifting to enhance the robustness of IC-UAPs against the unsynchronization between adversarial attacks and attacked signals. ---- Ruiqi Li, Hongshu Liao, Jiancheng An, Chau Yuen, Lu Gan More details can be found at this link: https://lnkd.in/gPSEkGnS
Intra-Class Universal Adversarial Attacks on Deep Learning-Based Modulation Classifiers
ieeexplore.ieee.org
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This paper studies a #Reconfigurable #Intelligent #Surfaces (#RISs)-assisted #generalized #spatial #modulation (#GSM) #multiple #input #multiple #output (#MIMO) system to improve the signal quality and spectral efficiency. Due to inter-channel interference, signal detection in GSM becomes a critical issue. Therefore, the authors propose a low complexity block #deep #neural #network (#DNN) detector for the RIS-GSM MIMO system to detect the active antennas and the transmitted symbols at the receiver. In order to optimize the phase shifts at the RIS elements, they propose cosine similarity-based and #semidefinite #relaxation (#SDR)-based algorithms. ---- Keshav Singh, Ahmad Fauzi Makarim, Hasan Albinsaid, Chih-Peng Li, Zygmunt J. Haas More details can be found at this link: https://lnkd.in/eD6tdpTc
Passive Beamforming Design and DNN-Based Signal Detection in RIS-Assisted MIMO Systems With Generalized Spatial Modulation
ieeexplore.ieee.org