Multiantenna Techniques

Zaidi, Ali A.; Athley, Fredrik; Medbo, Jonas; Gustavsson, Ulf; Durisi, Giuseppe; Chen, Xiaoming

doi:10.1016/b978-0-12-814578-4.00012-6

Cited by 18 publications

(34 citation statements)

References 23 publications

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“…In order to use the SSB in the passive radar processing chain, it has to be decoded and its signal has to be reconstructed. The structure of the SSB is specified in [8], [32], [33]. It is composed of Primary and Secondary Synchronization Signals (PSS and SSS), Demodulation Reference Signals (DM-RS) and the Physical Broadcast Channel (PBCH).…”

Section: G Nr and Ssb Detectionmentioning

confidence: 99%

“…The SSB synchronization block is sent in 5G NR by a base transceiver station (BTS) independently whether the content is present or not [8]. The SSB is the only always-on signal in the 5G network.…”

mentioning

confidence: 99%

“…Each of them is a beam-specific signal. Together they form a synchronization signal burst (SS Burst) [8]. Therefore, one can implement the PCL using the 5G SSB pulse also, which makes the 5G-based radar system robust and capable of working all the time, not only during slots with dense downlink content.…”

mentioning

confidence: 99%

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SSB-Based Signal Processing for Passive Radar Using a 5G Network

Abratkiewicz

Płotka

Samczyński

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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This paper presents an alternative processing chain for the passive radar using fifth-generation (5G) standard technology for broadband cellular networks as illuminators of opportunity. The proposition is to use a 5G synchronization signal block's (SSB) periodically transmitted modulated pulse in 5G-based passive coherent location (PCL) system processing. Although the SSB periodicity limits the velocity ambiguity, the paper describes a solution to tackle this problem in a single target scenario. The method is advantageous when there is a lack of transmission in the telecommunication channel, and the 5G SSB is the only existing signal. The paper proposes a signal processing pipeline for 5G-based PCL that is inspired by passive radars using non-cooperative pulse radar as an illumination source. The method has been validated using simulated and real-life 5G data measurements. The results presented in the paper show the possibility of detecting a moving target with a lack of data transmission in the 5G network, using only the SSB when the classical passive radar signal processing fails. The presented results prove the possibility for a significant increase of 5G network-based PCL utilization in short-range applications.

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Section: G Nr and Ssb Detectionmentioning

confidence: 99%

mentioning

confidence: 99%

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SSB-Based Signal Processing for Passive Radar Using a 5G Network

Abratkiewicz

Płotka

Samczyński

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…• Diversity gain, which measures the increase in the error rate slope as a function of the SNR. In other words, array gain increases the average SNR, whereas diversity gain makes the probability density function of the instantaneous SNR more concentrated around its average [19]. Two types of diversity could be realized via MIMO: receive diversity and transmit diversity.…”

Section: Related Workmentioning

confidence: 99%

Leveraging Multiple Transmissions and Receptions for Channel-Agnostic Deep Learning-Based Network Device Classification

Basha,

Hamdaoui

2021

Preprint

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The accurate identification of wireless devices is critical for enabling automated network access monitoring and authenticated data communication in large-scale networks; e.g., IoT. RF fingerprinting has emerged as a solution for device identification by leveraging the transmitter unique manufacturing impairments. Although deep learning is proven efficient in classifying devices based on the hardware impairments fingerprints, DL models perform poorly due to channel variations. That is, although training and testing neural networks using data generated during the same period achieve reliable classification, testing them on data generated at different times degrades the accuracy substantially, an already well recognized problem within the community. To the best of our knowledge, we are the first to propose to leverage MIMO capabilities to mitigate the channel effect and provide a channel-resilient device classification. We show that for AWGN channels, combining multiple received signals improves the testing accuracy by up to 30%. We also show that for Rayleigh channels, blind channel estimation enabled by MIMO increases the testing accuracy by up to 40% when the models are trained and tested over the same channel, and by up to 60% when the models are tested on a channel that is different from that used for training.

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“…It can also support various other 5G applications such as automotive and health care. 3GPP defined two frequency ranges: FR1 (below 6 GHz) and FR2 (above 24 GHz) [7,8].…”

Section: Development Of Wireless Networkmentioning

confidence: 99%

Convergence of Wireless and Optical Network in Future Communication Network

Mahapatra¹

2021

Wireless Power Transfer – Recent Development, Applications and New Perspectives

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The requirement of data increases many-fold in recent years to support the newest technologies in B5G and 6G. Wireless is the last mile solution as access with an optical network as the backbone in future communication systems. Over the years in every new generation, the distance between the base station and the user is decreasing and the optical node is coming closer to the user. There are several technologies like AR/VR, AI, holographic communication, holographic telepresence, etc. are the main candidates in B5G and 6G, which are required high-speed connection with low latency. To support these services, it is almost mandatory that transmit data across the network should be smooth and seamless to provide successful communication. Providing a successful and appropriate wireless link among the users simultaneously to achieve the requirements is becoming more complex, hence challenging. The optical backbone of all wireless access networks requires supporting these user’s requirements, needs to evolve continuously with wireless network evolution. This chapter will study the evolution of both networks to understand their cooperation, alignment, and support.

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Multiantenna Techniques

Cited by 18 publications

References 23 publications

SSB-Based Signal Processing for Passive Radar Using a 5G Network

SSB-Based Signal Processing for Passive Radar Using a 5G Network

Leveraging Multiple Transmissions and Receptions for Channel-Agnostic Deep Learning-Based Network Device Classification

Convergence of Wireless and Optical Network in Future Communication Network

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