A Hierarchical Game Approach for Multi-Operator Spectrum Sharing in LTE Unlicensed

Zhang, Huaqing; Xiao, Yong; Cai, Lin; Niyato, Dusit; Song, Lingyang; Han, Zhu

doi:10.1109/glocom.2014.7417784

Cited by 6 publications

(8 citation statements)

References 13 publications

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“…Many research works have been triggered to study the coexistence of LTE and WLAN in unlicensed spectrum. A few studies have examined the impact of LBT strategies on the coexistence of cellular and WLAN in unlicensed spectrum [10]- [15]. These studies confirm that appropriate LBT schemes help ensure fair sharing of unlicensed spectrum.…”

Section: Introductionmentioning

confidence: 88%

Throughput optimal listen-before-talk for cellular in unlicensed spectrum

Wei

Lin

et al. 2017

2017 IEEE International Conference on Communications (ICC)

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The effort to extend cellular technologies to unlicensed spectrum has been gaining high momentum. Listenbefore-talk (LBT) is enforced in the regions such as European Union and Japan to harmonize coexistence of cellular and incumbent systems in unlicensed spectrum. In this paper, we study throughput optimal LBT transmission strategy for load based equipment (LBE). We find that the optimal rule is a pure threshold policy: The LBE should stop listening and transmit once the channel quality exceeds an optimized threshold. We also reveal the optimal set of LBT parameters that are compliant with regulatory requirements. Our results shed light on how the regulatory LBT requirements can affect the transmission strategies of radio equipment in unlicensed spectrum.

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Section: Introductionmentioning

confidence: 88%

Throughput optimal listen-before-talk for cellular in unlicensed spectrum

Wei

Lin

et al. 2017

2017 IEEE International Conference on Communications (ICC)

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“…Guan et al in [28] investigated the LTE provider's joint channel selection and fractional spectrum access problem with the consideration of the fairness between LTE and Wi-Fi. Zhang et al in [29] analyzed the spectrum sharing among multiple LTE providers in the unlicensed spectrum through a hierarchical game. However, these studies did not consider the cooperation between LTE and Wi-Fi.…”

Section: Related Workmentioning

confidence: 99%

“…To compute the maximum social welfare for a particular set of APOs, we assume that there is a centralized decision maker, who allocates K channels to the LTE provider and the K APOs in a manner that maximizes the social welfare. 29 For each experiment, we randomly pick a set of APOs and record the social welfare achieved by the centralized decision maker. We run the experiment 20, 000 times, and obtain the average value of the maximum social welfare.…”

Section: B Comparison With the Benchmark Schemementioning

confidence: 99%

Auction-Based Coopetition between LTE Unlicensed and Wi-Fi

Iosifidis²,

Huang

2016

IEEE J. Select. Areas Commun.

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Abstract-Motivated by the recent efforts in extending LTE to the unlicensed spectrum, we propose a novel spectrum sharing framework for the coopetition (i.e., cooperation and competition) between LTE and Wi-Fi in the unlicensed band. Basically, the LTE network can choose to work in one of the two modes: in the competition mode, it randomly accesses an unlicensed channel, and interferes with the Wi-Fi access point using the same channel; in the cooperation mode, it delivers traffic for the Wi-Fi users in exchange for the exclusive access of the corresponding channel. Because the LTE network works in an interference-free manner in the cooperation mode, it can achieve a much larger data rate than that in the competition mode, which allows it to effectively serve both its own users and the Wi-Fi users. We design a second-price reverse auction mechanism, which enables the LTE provider and the Wi-Fi access point owners (APOs) to effectively negotiate the operation mode. Specifically, the LTE provider is the auctioneer (buyer), and the APOs are the bidders (sellers) who compete to sell their channel access opportunities to the LTE provider. In Stage I of the auction, the LTE provider announces a reserve rate, which is the maximum data rate that it is willing to allocate to the APOs in the cooperation mode. In Stage II of the auction, the APOs submit their bids, which indicate the data rates that they would like the LTE provider to offer in the cooperation mode. We show that the auction involves allocative externalities, i.e., the cooperation between the LTE provider and one APO benefits other APOs who are not directly involved in this cooperation. As a result, a particular APO's willingness to cooperate is affected by its belief about other APOs' willingness to cooperate. This makes our analysis much more challenging than that of the conventional second-price auction, where bidding truthfully is a weakly dominant strategy. We show that the APOs have a unique form of the equilibrium bidding strategies in Stage II, based on which we analyze the LTE provider's optimal reserve rate in Stage I. Numerical results show that our framework improves the payoffs of both the LTE provider and the APOs comparing with a benchmark scheme. In particular, our framework increases the LTE provider's payoff by 70% on average when the LTE provider has a large throughput and a small data rate discounting factor. Moreover, our framework leads to a close-to-optimal social welfare under a large LTE throughput.Index Terms-Coexistence of LTE and Wi-Fi in unlicensed band, auction with allocative externalities, symmetric Bayesian Nash equilibrium.

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“…• Utility functions of advanced games and emerging networks architectures: We concentrated on the utility function of the simple strategic game formulations; however, more advanced game models, eg, differential, Markovian, and Bayesian games are employed in wireless community, which need more complex utility function design with variety of features. There also exist some other kinds of game models, eg, repeated game, 95,96 Stackelberg game, [97][98][99][100][101][102] and evolutionary game. 103,104 Defining utility function is key to game formulation because it eventually determines the properties and performance of the game-theoretic models.…”

Section: Open Research Topicsmentioning

confidence: 99%

Utility function design for strategic radio resource management games: An overview, taxonomy, and research challenges

Yang

Ejaz

et al. 2016

Trans. Emerging Tel. Tech.

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Radio resource management is important for wireless communication networks. Game theory has been extensively used to model, analyze, and design interactive behaviors and the strategic decision‐making for radio resource management. It is known that utility function is one of the critical elements in a game, which characterizes the preferred relationship of the rational players and is a function of the action of players and their opponents. We first overview the basics of game theory and utility functions. We then present a taxonomy of utility functions with respect to different types of players, the nature of actions, and preferences in terms of the fairness, quality of service, and quality of experience. We provide some insights based on the taxonomy of utility functions, which provides the readers with a comprehensive view. Following that, we also discuss other types of traffic‐aware utility functions with different fairness and the potential and super modular game‐theoretic utility functions. In addition, we summarize the desired properties and observations for the design of suitable utility functions. Finally, we investigate impacts of the pricing in utility functions. This article ends with the conclusions and a promising view on open problems and challenges with possible future research directions.

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A Hierarchical Game Approach for Multi-Operator Spectrum Sharing in LTE Unlicensed

Cited by 6 publications

References 13 publications

Throughput optimal listen-before-talk for cellular in unlicensed spectrum

Throughput optimal listen-before-talk for cellular in unlicensed spectrum

Auction-Based Coopetition between LTE Unlicensed and Wi-Fi

Utility function design for strategic radio resource management games: An overview, taxonomy, and research challenges

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