Enhanced LBT algorithm for LTE-LAA in unlicensed band

Tao, Tao; Han, Feng; Liu, Yong

doi:10.1109/pimrc.2015.7343610

Cited by 65 publications

(38 citation statements)

References 6 publications

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“…Simulation results obtained from our simulation setup depict the performance of the proposed approach to solve MINLP problem in Equation (12). Performance is portrayed in terms of network throughput and user distribution among BSs with licensed and unlicensed band.…”

Section: Resultsmentioning

confidence: 99%

“…LBT is also a regulatory requirement in many regions such as Japan, India, and Europe. In other works, [12][13][14][15][16][17][18] authors propose an enhancement to basic LBT operation for fair coexistence of LTE-U and WiFi. Tao et al 12 proposed enhancement to LBT by adaptively adjusting size of contention window for LTE-U, which resulted in QoS fairness for coexistence of WiFi and LTE-U.…”

Section: Literature Reviewmentioning

confidence: 99%

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Resource allocation for licensed and unlicensed spectrum in 5G heterogeneous networks

Ali

Qaisar

Naeem

et al. 2018

Trans Emerging Tel Tech

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The foresighted enormous increase in mobile traffic over the coming years will result in severe congestion on available radio spectrum. The use of additional spectrum in future fifth‐generation mobile networks will be inevitable. Long‐Term Evolution Unlicensed (LTE‐U) is an evolving technology, which effectively utilizes available unlicensed spectrum to increase the capacity of unified fifth‐generation network. However, LTE‐U causes severe interference to existing WiFi networks, which needs to be addressed to take full advantage of LTE‐U. In this paper, we thrive to provide a suboptimal resource allocation for coexisting LTE‐U and WiFi networks to maximize throughput and, hence, minimize the interference. We formulated an optimization problem for joint user association and power allocation for licensed and unlicensed spectrum with objective to maximize sum rate of LTE‐U/WiFi heterogeneous network in a multioperator scenario, subject to minimum rate guarantee and cochannel interference threshold. We propose mesh adaptive direct search algorithm as solution to optimization problem to obtain ϵ‐optimal results. The performance of proposed algorithm is shown in terms of network key performance indicators such as throughput and number of users accommodated. We also benchmark the results from mesh adaptive direct search against outer approximation algorithm.

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Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Resource allocation for licensed and unlicensed spectrum in 5G heterogeneous networks

Ali

Qaisar

Naeem

et al. 2018

Trans Emerging Tel Tech

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“…plain coexistence [123], [124], [126], [129], [132], [133], [135], [136], [142], [145], [155] −vs. coexistence with itself [123], [136], [150], [154], [158], [159], [161] −vs. standalone [124], [135], [145], [157] −vs.…”

Section: -30 Stations Of Each Technologymentioning

confidence: 99%

“…duty cycle variants [124], [132], [133], [145], [146], [153], [155], [157] −vs. other LBT variants [124], [136], [147], [150]- [152], [154], [158]- [162] Other −fairness (implicitly) for Wi-Fi vs. coexistence with itself [136], [147], [149], [150], [153], [155]- [157], [159] −proportional fair rate allocation for Wi-Fi and LTE [143] −fairness as same Wi-Fi/LTE airtime [152] −proportional fair channel switch [158] −fairness as minimization of collision probability to Wi-Fi [160] −fairness as constant aggregate Wi-Fi throughput [161] −airtime fairness for Wi-Fi based on altruistic gains [162] −maximize aggregate LTE capacity in presence of Wi-Fi [144] −enable different levels of protection for Wi-Fi [148] −maximize total throughput given requirements of each technology [147] −simulations [123], [124], [129], [132], [133], [135], [136], [143]- [146], [148]- ...…”

Section: -30 Stations Of Each Technologymentioning

confidence: 99%

“…− 10-90 APs, or 400-5000 APs/km 2 of each technology: [123], [129], [132], [133], [136], [144], [145], [150], [155]- [157], [159] blocking and ordering of contention slots was proposed for IEEE 802.16, in order to reserve the channel before 802.11a and thus to guarantee QoS for 802.16. However, no performance evaluation results were presented.…”

Section: -30 Stations Of Each Technologymentioning

confidence: 99%

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Survey of Spectrum Sharing for Inter-Technology Coexistence

Voicu

Simić

Petrova

2019

IEEE Commun. Surv. Tutorials

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Increasing capacity demands in emerging wireless technologies are expected to be met by network densification and spectrum bands open to multiple technologies. These will, in turn, increase the level of interference and also result in more complex inter-technology interactions, which will need to be managed through spectrum sharing mechanisms. Consequently, novel spectrum sharing mechanisms should be designed to allow spectrum access for multiple technologies, while efficiently utilizing the spectrum resources overall. Importantly, it is not trivial to design such efficient mechanisms, not only due to technical aspects, but also due to regulatory and business model constraints. In this survey we address spectrum sharing mechanisms for wireless inter-technology coexistence by means of a technology circle that incorporates in a unified, system-level view the technical and nontechnical aspects. We thus systematically explore the spectrum sharing design space consisting of parameters at different layers. Using this framework, we present a literature review on intertechnology coexistence with a focus on wireless technologies with equal spectrum access rights, i.e. (i) primary/primary, (ii) secondary/secondary, and (iii) technologies operating in a spectrum commons. Moreover, we reflect on our literature review to identify possible spectrum sharing design solutions and performance evaluation approaches useful for future coexistence cases. Finally, we discuss spectrum sharing design challenges and suggest future research directions.

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