Device-to-device (D2D) relaying is a concept, where some users relay data of cell-edge users (CUEs) experiencing a bad channel quality to a base station. While this research topic has received plenty of attention, a critical aspect of the D2D relaying remains a selfish nature of the users and their limited willingness to relay data for others. Thus, we propose a scheme to identify potential candidates for the relaying and provide a sound incentive to these relaying users (RUEs) to motivate them helping other users. First, we provide a detailed theoretical analysis showing when and if the relaying is beneficial for the CUE(s) and related RUE. Second, to choose among all possible incentive-compliant relaying options, we formulate the optimal CUE-to-RUE matching problem maximizing a network-wide performance. Since the optimal solution is hard to obtain for a high number of users, we propose a low-complexity greedy algorithm and prove its constant worst-case approximation guarantees to the optimum. Finally, we derive a closed-form expression for a fair allocation of the resources among the CUEs and the RUEs. The proposed framework more than doubles the users’ capacity and/or reduces the energy consumption by up to 87% comparing to existing incentive-based relaying schemes.

中文翻译：

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蜂窝网络中基于激励的D2D中继

设备到设备（D2D）中继是一个概念，其中某些用户将遇到不良信道质量的小区边缘用户（CUE）的数据中继到基站。尽管此研究主题已引起广泛关注，但D2D中继的关键方面仍然是用户的自私本性，以及他们为他人中继数据的意愿有限。因此，我们提出了一种方案，用于识别潜在的中继候选人，并为这些中继用户（RUE）提供合理的激励，以激励他们帮助其他用户。首先，我们提供了详细的理论分析，显示了中继何时以及是否对CUE和相关RUE有益。其次，要在所有可能的激励合规中继选项中进行选择，我们制定了最佳的CUE到RUE匹配问题，以最大化网络范围的性能。由于难以为大量用户获得最优解，因此我们提出了一种低复杂度的贪心算法，并证明了其恒定的最坏情况下近似保证了最优。最后，我们得出一个封闭形式的表达式，用于在CUE和RUE之间公平分配资源。与现有的基于激励的中继方案相比，所提出的框架将用户的容量增加了一倍以上和/或将能耗降低了多达87％。