Hybrid light-fidelity (LiFi) and wireless-fidelity (WiFi) networks (HLWNets) provide a promising solution for the future indoor wireless communications. This network structure faces the challenge of traffic congestion since LiFi links are prone to be blocked due to angular misalignment and path obstruction while WiFi has limited capacity. In this paper, a novel network structure that enables device-to-device (D2D) technology in HLWNets is considered. Then, traffic grooming (TG) for D2D-enabled HLWNets with massive light-path blockages is researched. By jointly handling mode selection, user pairing, and resource allocation, TG is formulated as a joint optimization problem. This can efficiently groom low-speed connections from WiFi onto high-capacity LiFi when massive light-path blockages occur, thus increasing network throughput. Next, a three-stage heuristic TG algorithm is developed to reduce the computational complexity required to solve the optimization problem. Finally, by simulation, the effectiveness of the proposed algorithm has been demonstrated. The simulation results indicate that the network throughput can be increased by up to 20% with the proposed algorithm. Besides, the proposed algorithm also has significant advantages in terms of Jain's fairness index and user satisfaction.

混合光保真 (LiFi) 和无线保真 (WiFi) 网络 (HLWNets) 为未来的室内无线通信提供了一种有前途的解决方案。这种网络结构面临着流量拥塞的挑战，因为LiFi链路很容易因角度失准和路径阻塞而被阻塞，而WiFi的容量有限。在本文中，考虑了一种在 HLWNet 中实现设备到设备 (D2D) 技术的新颖网络结构。然后，研究了具有大量光路阻塞的支持 D2D 的 HLWNet 的流量疏导 (TG)。通过联合处理模式选择、用户配对和资源分配，TG被制定为联合优化问题。当发生大量光路阻塞时，这可以有效地将低速连接从 WiFi 转移到大容量 LiFi，从而提高网络吞吐量。接下来，开发了三阶段启发式TG算法来降低解决优化问题所需的计算复杂度最后通过仿真验证了所提算法的有效性。仿真结果表明，采用该算法可以将网络吞吐量提高高达20%。此外，该算法在Jain公平性指数和用户满意度方面也具有显着优势。