Achievable Rates of Opportunistic Cognitive Radio Systems Using Reconfigurable Antennas With Imperfect Sensing and Channel Estimation

Yazdani, Hassan; Vosoughi, Azadeh; Gong, Xun

doi:10.1109/tccn.2021.3056691

Cited by 14 publications

(5 citation statements)

References 45 publications

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“…When the transmission beam of the PU is well identified, SU may exploit the remaining space in order to transmit the data on a non-overlapping beams base [125,199,200]. SUs, in this case, should be equipped with a multi-antenna system in order to adjust their beam far from the primary receiver to avoid interference.…”

Section: Beamforming-based Communicationmentioning

confidence: 99%

“…SUs, in this case, should be equipped with a multi-antenna system in order to adjust their beam far from the primary receiver to avoid interference. In this context, joint sensing and localization of PU becomes of high importance since the localization of PU transmitter may facilitate the mission of SUs in identifying the beam and thus to diagnose the spatiotemporal availability of the spectrum [200,201]. Recently, some work has been introduced to enable spatial SS by identifying the PU's location and adjusting the SU's beam using the received power at SUs surrounding the PU [200,202].…”

Section: Beamforming-based Communicationmentioning

confidence: 99%

“…In this context, joint sensing and localization of PU becomes of high importance since the localization of PU transmitter may facilitate the mission of SUs in identifying the beam and thus to diagnose the spatiotemporal availability of the spectrum [200,201]. Recently, some work has been introduced to enable spatial SS by identifying the PU's location and adjusting the SU's beam using the received power at SUs surrounding the PU [200,202]. In this regard, estimation techniques have to be more developed in order to estimate the PU beam blindly or in the case where little information about PU transmission is available [203][204][205].…”

Section: Beamforming-based Communicationmentioning

confidence: 99%

“…Sensing the Spatial Dimension for CR Beam-based sensing of PUs becomes more and more important for SUs since it provides the SU with the spatial availability of the spectrum. However, the PU's transmission beam estimation remains challenging for SU especially where no cooperation is available with PU [200,215]. Even when the PU beam is known, adjusting the SU beam is challenging too due to the inevitable interference caused by the SU transmitter to the SU receiver.…”

mentioning

confidence: 99%

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Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge

Nasser

Hassan

Chaaya

et al. 2021

Sensors

108

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Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth survey on the most recent advances in SS for CR. We start by explaining the Half-Duplex and Full-Duplex paradigms, while focusing on the operating modes in the Full-Duplex. A thorough discussion of Full-Duplex operation modes from collision and throughput points of view is presented. Then, we discuss the use of learning techniques in enhancing the SS performance considering both local and cooperative sensing scenarios. In addition, recent SS applications for CR-based Internet of Things and Wireless Sensors Networks are presented. Furthermore, we survey the latest achievements in Spectrum Sensing as a Service, where the Internet of Things or the Wireless Sensor Networks may play an essential role in providing the CR network with the SS data. We also discuss the utilisation of CR for the 5th Generation and Beyond and its possible role in frequency allocation. With the advancement of telecommunication technologies, additional features should be ensured by SS such as the ability to explore different available channels and free space for transmission. As such, we highlight important future research axes and challenging points in SS for CR based on the current and emerging techniques in wireless communications.

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Section: Beamforming-based Communicationmentioning

confidence: 99%

Section: Beamforming-based Communicationmentioning

confidence: 99%

Section: Beamforming-based Communicationmentioning

confidence: 99%

mentioning

confidence: 99%

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Spectrum Sensing for Cognitive Radio: Recent Advances and Future Challenge

Nasser

Hassan

Chaaya

et al. 2021

Sensors

108

View full text Add to dashboard Cite

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“…The aforementioned studies assume that the FA-based systems have perfect knowledge of the channel state information (CSI) for all the FA-associated links. In practice, such CSI needs to be acquired in each channel coherence interval by the transmitter at the cost of channel training overhead that increases with the number of FA ports [7]. In the context of limited coherence interval scenario, this inevitably results in a reduced data transmission duration and, consequently, in an alleviated overall network performance.…”

Section: Introductionmentioning

confidence: 99%

Large-Scale Fluid Antenna Systems With Linear MMSE Channel Estimation

Skouroumounis

Krikidis

2022

ICC 2022 - IEEE International Conference on Communications

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In this paper, we investigate the outage performance of fluid antenna (FA)-based user equipments (UEs) in the context of large-scale downlink cellular networks, where all UEs employ linear minimum mean-squared error (LMMSE) channel estimation method. In contrast to existing studies, which assume the existence of perfect channel state information, we develop a novel mathematical framework that accurately captures the channel estimation errors on the performance of the considered network deployment. Specifically, we focus on the limited coherence interval scenario, where a sequential LMMSE-based channel estimation procedure is performed for all FA ports, followed by data reception from the port with the strongest estimated channel. By using stochastic geometry tools, we derive both analytical and closed-form expressions for the achieved outage probability, highlighting the impact of channel estimation on the performance of FA-based UEs. Our results reveal the trade-off imposed between improving the network's outage performance and reducing the channel estimation quality, indicating new insights for the design of FA-based wireless systems.

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