In this paper, a Device-to-Device communication on unlicensed bands (D2D-U) enabled network is studied. To improve the spectrum efficiency (SE) on the unlicensed bands and fit its distributed structure while ensuring the fairness among D2D-U links and the harmonious coexistence with WiFi networks, a distributed joint power and spectrum scheme is proposed. In particular, a parameter, named as price, is defined, which is updated at each D2D-U pair by a online trained Neural network (NN) according to the channel state and traffic load. In addition, the parameters used in the NN are updated by two ways, unsupervised self-iteration and federated learning, to guarantee the fairness and harmonious coexistence. Then, a non-convex optimization problem with respect to the spectrum and power is formulated and solved on each D2D-U link to maximize its own data rate. Numerical simulation results are demonstrated to verify the effectiveness of the proposed scheme.

在本文中，研究了启用了免许可频段（D2D-U）的网络上的设备到设备通信。为了提高免许可频段上的频谱效率（SE）并适应其分布式结构，同时确保D2D-U链路之间的公平性以及与WiFi网络的和谐共存，提出了一种分布式联合功率和频谱方案。特别是，定义了一个称为价格的参数，该参数通过在线训练的神经网络在每个D2D-U对上进行更新。（NN）根据频道状态和流量负载。另外，通过两种方式更新NN中使用的参数：无监督的自我迭代和联合学习，以确保公平和和谐共存。然后，在每个D2D-U链路上制定和解决关于频谱和功率的非凸优化问题，以最大化其自身的数据速率。数值仿真结果证明了所提方案的有效性。