The right content for the right relay in self-organizing delay tolerant networks: A matching game perspective

Arabi, Sara; Sabir, Essaïd; Taleb, Tarik; Sadik, Mohammed

doi:10.1109/icc.2017.7997342

Cited by 5 publications

(2 citation statements)

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“…This work was extended in [26] to analysis the energy efficiency. Moreover, the stable matching algorithm can be utilized to get a sub-optimal solution more quickly, which has been applied in resource allocation in wireless networks [27]- [32]. In order to achieve a high access ratio and a short access latency, a content replication scheme using stable matching is proposed in [28].…”

Section: Introductionmentioning

confidence: 99%

“…In [30], a one-toone stable matching is considered for channel assignment in cognitive radio settings. In [32], the matching-game based scheme promises an efficient tradeoff in multi-user and multi-relay networks. To the best of our knowledge, the utility function of previous works is based on channel capacity, which leads to inaccurate utility optimization, and the stable matching for utility optimization of large scale EH relay networks with finite-alphabet inputs has never been investigated before.…”

Section: Introductionmentioning

confidence: 99%

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Utility-Based Stable Matching For Large Scale EH Relay Networks With Finite-Alphabet Inputs

Liu

Deng

et al. 2019

IEEE Access

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The computational complexity of utility optimization for a large scale energy harvesting (EH) relay network is extremely high, especially when inputting finite-alphabet signals. This paper investigates the utility optimization for large scale EH relay networks with finite-alphabet inputs by the stable matching scheme. First, we divide the nodes, which may act as a user or a relay, into multiple clusters, and perform optimization strategy within the clusters. Second, the optimal power bought from the relay node to maximize the utility of the user is derived. Then, the mutual preference matrices between the users and relays by the maximum utility criterion are established. Base on the mutual preference matrices, an improved Gale-Shapley (GS) algorithm is proposed to get a sub-optimal result. The simulation results demonstrate that the proposed algorithm can bring significant performance improvements and achieve higher energy efficiency compared with the conventional algorithms. In contrast to the exhausted Search (ES) method, it costs much less time and accomplishes an approximative utility output. Moreover, the proposed scheme incurs low signaling overhead which makes it practical to be implemented. INDEX TERMS Large scale relay networks, utility optimization, stable matching, finite-alphabet inputs, energy harvesting.

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