Evaluating Unlicensed LTE Technologies: LAA vs LTE-U

Bojović, Biljana; Giupponi, Lorenza; Ali, Zoraze; Miozzo, Marco

doi:10.1109/access.2019.2926197

Cited by 37 publications

(28 citation statements)

References 25 publications

(40 reference statements)

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“…The authors in [18] proposed an approach to disable standard LTE transmissions on specific subframes using the almost blank subframe (ABS) LTE functionality. Their results demonstrate that LTE-DC can operate harmoniously with Wi-Fi and even LTE-LAA by adequately adjusting the duty cycle [19][20][21].…”

Section: Related Workmentioning

confidence: 99%

Multi-Cell LTE-U/Wi-Fi Coexistence Evaluation Using a Reinforcement Learning Framework

Neto

Ana

et al. 2020

Sensors

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Cellular broadband Internet of Things (IoT) applications are expected to keep growing year-by-year, generating demands from high throughput services. Since some of these applications are deployed over licensed mobile networks, as long term evolution (LTE), one already common problem is faced: the scarcity of licensed spectrum to cope with the increasing demand for data rate. The LTE-Unlicensed (LTE-U) forum, aiming to tackle this problem, proposed LTE-U to operate in the 5 GHz unlicensed spectrum. However, Wi-Fi is already the consolidated technology operating in this portion of the spectrum, besides the fact that new technologies for unlicensed band need mechanisms to promote fair coexistence with the legacy ones. In this work, we extend the literature by analyzing a multi-cell LTE-U/Wi-Fi coexistence scenario, with a high interference profile and data rates targeting a cellular broadband IoT deployment. Then, we propose a centralized, coordinated reinforcement learning framework to improve LTE-U/Wi-Fi aggregate data rates. The added value of the proposed solution is assessed by a ns-3 simulator, showing improvements not only in the overall system data rate but also in average user data rate, even with the high interference of a multi-cell environment.

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Section: Related Workmentioning

confidence: 99%

Multi-Cell LTE-U/Wi-Fi Coexistence Evaluation Using a Reinforcement Learning Framework

Neto

Ana

et al. 2020

Sensors

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“…The LBT protocol for NR-U follows the LBT procedure defined in LTE-LAA, which was indeed inspired by the Wi-Fi CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) mechanism. A state machine for the LBT CCA process is presented in [28]. In particular, for NR-U, four LBT categories have been defined [16]:…”

Section: A 3gpp Nr-u Highlightsmentioning

confidence: 99%

“…In these bands, it is commonly accepted that LAA is fairer to Wi-Fi than LTE-U because it uses the LBT mechanism, and so it behaves similarly to Wi-Fi. Recently, authors in [28] have presented a detailed coexistence study and comparison of LAA and LTE-U technologies through network simulations and evaluated how the channel access procedures, besides other important aspects like the traffic patterns, simulation setup, and proprietary implementation choices, impact the coexistence performance. However, similar studies for NR-U and Wi-Fi/WiGig coexistence, are not yet available for either below 7 GHz or mmWave bands.…”

Section: Introductionmentioning

confidence: 99%

“…We believe that reproducibility and model openness are crucial to perform research in the area of coexistence of multi-RAT technologies in unlicensed spectrum. In this regard, the popular and open source ns-3 simulator provides the perfect framework for reproducible research and collaborative development, as it was already demonstrated in [28], and disposes of multi-RAT models. Notably, the ns-3 simulator has recently released novel models for NR Release-15 [30], [31] and IEEE 802.11ad [32], [33].…”

Section: Introductionmentioning

confidence: 99%

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NR-U and IEEE 802.11 Technologies Coexistence in Unlicensed mmWave Spectrum: Models and Evaluation

et al. 2020

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New Radio-based access to Unlicensed spectrum (NR-U) intends to expand the applicability of 5G NR access technology to support operation in unlicensed bands by adhering to Listen-Before-Talk (LBT) requirement for accessing the channel. As the NR-U specification is being developed, simulations to assess the performance of NR-U and IEEE 802.11 technologies coexistence in unlicensed spectrum bands are crucial. In this paper, we report on extensions to a popular and open source network simulator, ns-3, to build an NR-U system-level simulator and to model the NR-U and IEEE 802.11 technologies coexistence in the currently available unlicensed spectrum bands. The proposed NR-U model capitalizes on an NR Release-15 based model that has been extended to operate in unlicensed bands, while meeting its regulatory requirements. For the coexistence analysis, we pay particular attention to the millimeter-wave bands and provide a complete set of simulation campaigns evaluating the coexistence of NR-U and IEEE 802.11ad Wireless Gigabit (WiGig) in the 60 GHz bands. In particular, we focus on determining whether NR-U fulfills its coexistence objective in terms of a fairness criterion by testing different NR-U parameters, such as the numerology, the bandwidth, the channel access scheme, the energy detection threshold, and the beamforming method.

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“…Therefore, for better spectral efficiency, efficient allocation of licensed and unlicensed spectrum for indoor users is required [11], [12]. Furthermore, it is more challenging to maintain fair coexistence due to the close proximity between the eNB and APs [13], [14].…”

Section: Introductionmentioning

confidence: 99%

A QoE-Based Framework for Video Streaming Over LTE-Unlicensed

et al. 2020

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To improve the system capacity and accommodate the ever-increasing demand for bandwidth by the network users, LTE service providers have turned their attention to the unlicensed industrial, scientific, and medical (ISM) spectrum; currently heavily utilized by the users of the IEEE 803.11 standards or WiFi. Unfortunately, such an approach, referred to as LTE-U, causes coexistence problems which necessitates the development of effective spectrum-sharing mechanisms to mitigate the interference with WiFi users. In this work, we propose a framework for video transmission over LTE-U to achieve harmonious coexistence with WiFi systems while taking into account the quality of experience (QoE) requirements of the user equipment (UE). In the proposed scheme, the channel allocation aims to enhance the peak signalto-noise ratio (PSNR) and to reduce the end-to-end delay of video packets. We present analytical schemes for predicting PSNR and delay of the received video sequence based on video parameters transmitted by the video server and periodic feedback from the UE, which provides the signal-to-noise ratio (SNR) of the channel. In addition, the probability of causing interference to WiFi users is used to formulate the channel allocation problem as a multi-objective optimization problem. Taking into account the received video quality and the achieved inter-frame delay for both LTE-U and WiFi users, the simulation results show that the proposed scheme outperforms a reference model that employs a channel access mechanism but randomly assigns frames to the available channels.

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Evaluating Unlicensed LTE Technologies: LAA vs LTE-U

Cited by 37 publications

References 25 publications

Multi-Cell LTE-U/Wi-Fi Coexistence Evaluation Using a Reinforcement Learning Framework

Multi-Cell LTE-U/Wi-Fi Coexistence Evaluation Using a Reinforcement Learning Framework

NR-U and IEEE 802.11 Technologies Coexistence in Unlicensed mmWave Spectrum: Models and Evaluation

A QoE-Based Framework for Video Streaming Over LTE-Unlicensed

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