The Impact of Imperfect Spectrum Sensing on the Performance of LTE Licensed Assisted Access Scheme

Pei, Errong; Lu, Xiaozhi; Deng, Bingguang; Pei, Jian; Zhang, Zhizhong

doi:10.1109/tcomm.2019.2963153

Cited by 10 publications

(2 citation statements)

References 19 publications

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“…Several solutions such as offloading [9], interferences control [10], beam-based transmission using directional antennas [11], network slicing and spatial multiplexing [12], hybrid channel access mechanism [13] had been proposed. Besides, to ensure fair operation in unlicensed spectrum with the coexistence between LTE-LAA and Wi-Fi systems, we note that several works used Markov chain as their analytical models [14] [15] [16] [17]. Several researches proposed modified LBT protocols based on LAA frame structure, such as an adaptive p-persistent LBT channel access scheme [14], anti-slot-jamming LBT scheme [15], linear backoff based LAA scheme [16] and enhanced clear channel assessment (eCCA) based LAA scheme, to fulfill fairness and coexistence.…”

Section: Related Workmentioning

confidence: 99%

Applications of Intelligent Radio Technologies in Unlicensed Cellular Networks - A Survey

Huang¹,

Chen²

2021

KSII TIIS

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Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

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Section: Related Workmentioning

confidence: 99%

Applications of Intelligent Radio Technologies in Unlicensed Cellular Networks - A Survey

Huang¹,

Chen²

2021

KSII TIIS

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“…The spectrum sensing and sharing algorithms are widely used in a variety of wireless technologies, for example, DeepWiFi [2] for WiFi spectrum sensing, OutSense [3] for ZigBee spectrum sensing, and RealSense [4] for TV spectrum sensing. Spectrum sensing and sharing methods are also used in cross-technology coexisted environments, for example, literature [5][6][7][8][9][10][11] conducts the spectrum sensing and management between WiFi and LTE-U technologies, literature [12][13][14][15] introduces the spectrum sensing between ZigBee and WiFi technologies, [16][17][18][19][20][21], uses spectrum sensing method for OFDM-based heterogeneous wireless devices.…”

Section: Introductionmentioning

confidence: 99%

A Novel Subcarrier‐Level Spectrum Sensing Method by Utilizing Fine‐Grained Channel State Information in Wireless Networks

Wang

Sun

et al. 2021

Wireless Communications and Mobile Computing

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Traditionally, the channelization structures of wireless technologies (802.11/ZigBee/BLE) have been fixed. Each node content for the spectrum is assigned one channel with a specific bandwidth. However, classical channel-based spectrum sensing and sharing algorithms have great limitations to further optimize spectrum utilization when multiple IoT with different wireless technologies coexisting in the same environment. Therefore, exploring the fine-grained spectrum sensing algorithm becomes an essential work to further improve the spectrum utilization efficiency, especially in the Industrial Scientific Medical (ISM) band. This paper proposes Subcarrier-Sniffer, a novel subcarrier-level spectrum sensing and sharing method, which utilizes channel state information (CSI) to sense the fine-grained status of each subcarrier of the traditional channel. To evaluate the performance of Subcarrier-Sniffer, we implemented Subcarrier-Sniffer by USRP B200min, and the experimental results show that the accuracy of subcarrier-level spectrum sensing could achieve 100% in our settings that the distance between Subcarrier-Sniffer and the monitor is not greater than 7 m. Subcarrier-Sniffer could be applied in WiFi and ZigBee, WiFi and BLE, and WiFi and LTE-U coexisted environments for better spectrum utilization.

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Power Control Based Spatial Reuse for LAA and WiFi Coexistence

Hang

Yang

Yan

et al. 2021

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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The Impact of Imperfect Spectrum Sensing on the Performance of LTE Licensed Assisted Access Scheme

Cited by 10 publications

References 19 publications

Applications of Intelligent Radio Technologies in Unlicensed Cellular Networks - A Survey

Applications of Intelligent Radio Technologies in Unlicensed Cellular Networks - A Survey

A Novel Subcarrier‐Level Spectrum Sensing Method by Utilizing Fine‐Grained Channel State Information in Wireless Networks

Power Control Based Spatial Reuse for LAA and WiFi Coexistence

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