[go: up one dir, main page]

da Cruz et al., 2024 - Google Patents

Detecting malicious pilot contamination in multiuser massive MIMO using decision trees

da Cruz et al., 2024

View PDF
Document ID
3100228858312776718
Author
da Cruz P
Leandro D
Spadini T
Suyama R
Loiola M
Publication year
Publication venue
Telecommunication Systems

External Links

Snippet

Massive multiple-input multiple-output (MMIMO) is essential to modern wireless communication systems, like 5G and 6G, but it is vulnerable to active eavesdropping attacks. One type of such attack is the pilot contamination attack (PCA), where a malicious user …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425—Traffic logging, e.g. anomaly detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/03592—Adaptation methods
    • H04L2025/03598—Algorithms
    • H04L2025/03611—Iterative algorithms
    • H04L2025/03643—Order recursive
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference induced by transmission
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W12/00—Security arrangements, e.g. access security or fraud detection; Authentication, e.g. verifying user identity or authorisation; Protecting privacy or anonymity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W28/00—Network traffic or resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATIONS NETWORKS
    • H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
    • H04W72/04—Wireless resource allocation

Similar Documents

Publication Publication Date Title
Taricco Optimization of linear cooperative spectrum sensing for cognitive radio networks
US8165235B2 (en) Interfering stream identification in wireless communication systems
Khan et al. A Genetic Algorithm‐Based Soft Decision Fusion Scheme in Cognitive IoT Networks with Malicious Users
AU2022420588B2 (en) Waveform agnostic learning-enhanced decision engine for any radio
Guimaraes Spectrum sensing: A tutorial
Balachander et al. Efficient utilization of cooperative spectrum sensing (CSS) in cognitive radio network (CRN) using non-orthogonal multiple access (NOMA)
Sun et al. Spoofing attack detection using machine learning in cross‐technology communication
Gahane et al. Performance of improved energy detector with cognitive radio mobility and imperfect channel state information
Hoang et al. Detection of spoofing attacks in aeronautical ad-hoc networks using deep autoencoders
Gouissem et al. Accelerated IoT anti-jamming: A game theoretic power allocation strategy
Nashat et al. Statistical-based detection of pilot contamination attack for NOMA in 5G networks
da Cruz et al. Detecting malicious pilot contamination in multiuser massive MIMO using decision trees
Mansukhani et al. Censored spectrum sharing strategy for MIMO systems in cognitive radio networks
Lavanis et al. Performance of p‐norm detector in cognitive radio networks with cooperative spectrum sensing in presence of malicious users
Pourgharehkhan et al. Correlated multiple antennas spectrum sensing under calibration uncertainty
Zhang et al. Adaptive jamming attack detection under noise uncertainty in mmWave massive MIMO systems
Mehrabian et al. Cooperative jamming detection using low-rank structure of received signal matrix
Emami et al. A soft cooperative spectrum sensing in the presence of most destructive smart PUEA using energy detector
Varotto et al. One-class classification as GLRT for jamming detection in private 5G networks
Khurshid et al. Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information
Liang Spectrum sensing theories and methods
Dong et al. Multiuser Covert Terahertz Communication With Outdated CSI and Data Exception
Mahmood et al. An efficient rank adaptation algorithm for cellular MIMO systems with IRC receivers
Zhang et al. STAR-RIS enabled covert integration of sensing communication and over-the-air computing with analysis and optimization
Wei et al. Spectrum sensing with Gaussian approximated eigenvalue ratio based detection