Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks

Yang Yang; Ying Cui; Zhehan Cao; Zitian Wang

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Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks

Zitian Wang, Zhehan Cao, Ying Cui, Yang Yang

Information Theory · Submitted 24 Jun 2017

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The authors' main claim Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.

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arXiv ID1706.07903 (version 1)

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CitationYang Yang, Ying Cui, Zhehan Cao, Zitian Wang. "Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks." arXiv:1706.07903 (2017). https://pith.science/paper/FN3W2XZZ

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Caching and multicasting are two promising methods to support massive content delivery in multi-tier wireless networks. In this paper, we consider a random caching and multicasting scheme with caching distributions in the two tiers as design parameters, to achieve efficient content dissemination in a two-tier large-scale cache-enabled wireless multicasting network. First, we derive tractable expressions for the successful transmission probabilities in the general region as well as the high SNR and high user density region, respectively, utilizing tools from stochastic geometry. Then, for the case of a single operator for the two tiers, we formulate the optimal joint caching design problem to maximize the successful transmission probability in the asymptotic region, which is nonconvex in general. By using the block successive approximate optimization technique, we develop an iterative algorithm, which is shown to converge to a stationary point. Next, for the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region. We show that the game has a unique Nash equilibrium (NE) and develop an iterative algorithm, which is shown to converge to the NE under a mild condition. Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.

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What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Caching and multicasting are two promising methods to support massive content delivery in multi-tier wireless networks.	background 1.00	0.04	0.03	asserted 0.85
s1	In this paper, we consider a random caching and multicasting scheme with caching distributions in the two tiers as design parameters, to achieve efficient content dissemination in a two-tier large-scale cache-enabled wireless multicasting network.	contribution 0.79	0.62	0.04	asserted 0.87
s2	First, we derive tractable expressions for the successful transmission probabilities in the general region as well as the high SNR and high user density region, respectively, utilizing tools from stochastic geometry.	method 0.45	0.96	0.03	asserted 1.00
s3	Then, for the case of a single operator for the two tiers, we formulate the optimal joint caching design problem to maximize the successful transmission probability in the asymptotic region, which is nonconvex in general.	contribution 0.74	0.92	0.04	asserted 1.00
s4	By using the block successive approximate optimization technique, we develop an iterative algorithm, which is shown to converge to a stationary point.	method 0.90	0.96	0.05	asserted 1.00
s5	Next, for the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region.	contribution 0.69	0.86	0.04	asserted 0.91
s6	We show that the game has a unique Nash equilibrium (NE) and develop an iterative algorithm, which is shown to converge to the NE under a mild condition.	result 0.70	0.97	0.12	asserted 1.00
s7	Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.	result 0.99	0.96	0.74	asserted 1.00

What kind of paper the classifier reports this is: method or tool 0.51 · evidence from proof or derivation 0.88.

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The paper

Original abstract

Caching and multicasting are two promising methods to support massive content delivery in multi-tier wireless networks. In this paper, we consider a random caching and multicasting scheme with caching distributions in the two tiers as design parameters, to achieve efficient content dissemination in a two-tier large-scale cache-enabled wireless multicasting network. First, we derive tractable expressions for the successful transmission probabilities in the general region as well as the high SNR and high user density region, respectively, utilizing tools from stochastic geometry. Then, for the case of a single operator for the two tiers, we formulate the optimal joint caching design problem to maximize the successful transmission probability in the asymptotic region, which is nonconvex in general. By using the block successive approximate optimization technique, we develop an iterative algorithm, which is shown to converge to a stationary point. Next, for the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region. We show that the game has a unique Nash equilibrium (NE) and develop an iterative algorithm, which is shown to converge to the NE under a mild condition. Finally, by numerical simulations, we show that the proposed designs achieve significant gains over existing schemes.

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Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

What it cites · 26 sentences without a confident label

Contests 1 paper

In contrast, [ref] simplifies the nonconvex problem to a convex one, and uses the optimal solution to the simplified problem as a sub-optimal solution to the original problem, which may not provide performance guarantee.

Cache-Enabled Heterogeneous Cellular Networks: Optimal Tier-Level Content Placement · Optimization Problem Formulation · contest 0.73

Builds on 1 paper

In addition, in the special case of the same cache size, we develop a low-complexity algorithm to obtain a globally optimal solution by extending the method in [ref] . * For the case of two different operators, one for each tier, we formulate the competitive caching design game where each tier maximizes its successful transmission probability in the asymptotic region.

Cache-Enabled Heterogeneous Cellular Networks: Optimal Tier-Level Content Placement · Introduction · 0.99

Uses the method or tool of 1 paper

This stage is the same as that in [ref] , and is included for completeness.

Cache-Enabled Heterogeneous Cellular Networks: Optimal Tier-Level Content Placement · Algorithm Design · 0.87

Compares with 2 papers

In addition, the asymptotic successful transmission probability in Corollary [ref] and the performance metric in [ref] have different meanings, although they share similar forms.

Optimization and Analysis of Probabilistic Caching in $N$-tier Heterogeneous Networks · Performance Analysis in Asymptotic Region · 0.97
In addition, the asymptotic successful transmission probability in Corollary [ref] and the performance metric in [ref] have different meanings, although they share similar forms.

Cache-Enabled Heterogeneous Cellular Networks: Optimal Tier-Level Content Placement · Performance Analysis in Asymptotic Region · 0.97

Cites as background 5 papers

In [ref] , the authors consider random caching and focus on the analysis and optimization of the probability that the signal-to-interference plus noise ratio (SINR) of a typical user is above a threshold, in a large-scale cache-enabled multi-tier wireless network.

Optimization and Analysis of Probabilistic Caching in $N$-tier Heterogeneous Networks · Introduction · 0.86
In [ref] , the authors consider random caching and focus on the analysis and optimization of the probability that the signal-to-interference plus noise ratio (SINR) of a typical user is above a threshold, in a large-scale cache-enabled multi-tier wireless network.

Cache-Enabled Heterogeneous Cellular Networks: Optimal Tier-Level Content Placement · Introduction · 0.86
In [ref] , the authors consider random caching and focus on the analysis and optimization of the probability that the signal-to-interference plus noise ratio (SINR) of a typical user is above a threshold, in a large-scale cache-enabled multi-tier wireless network.

Random Caching Based Cooperative Transmission in Heterogeneous Wireless Networks · Introduction · 0.86

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