## 1 Introduction  
The artificial intelligence and multimedia enabled smart home significantly facilitates our daily life [1; 2; 3]. However, high dynamic and high peak-to-average ratio traffic is generated by the above services. The explosive growth of dynamic traffic imposes great pressure on internet of things (IoT) and related networks. Furthermore, Cisco's research forecasted that billions of IoT connections will be added by 2023 [4]. The proliferation of diverse IoT devices may change the design of traditional IoT networks [5]. In smart homes, sensors (including the video surveillance system) are connected to the gateway through short distance network connections, such as Wi-Fi, ZigBee, and NB-IoT [6]. In the 5G era, the information collected by the gateway can be transmitted to cloud via 5G cellular mobile networks [6] and is stored and analyzed in cloud servers [7]. To transmit signals, the network between the baseband units (BBU) and remote radio units (RRUs) is called mobile fronthaul network in the centralized radio access network (C-RAN) architecture [8; 9]. Then, the mobile fronthaul network will be a key factor to support various smart home services [10], which is the first network segment to connect smart homes. However, facing the dynamic and busty traffic of smart homes, the energy and transmission efficiency has emerged as an important issue on fronthaul networks. Considering the progressive network evolution, the 5G non-standalone (NSA) will be widely deployed in the first stage, in which cloud radio access network (C-RAN) is still being used [11]. Thus, in this paper, we will take C-RAN based fronthaul as a typical scenario during the analysis; nevertheless, the proposed algorithms can be easily extended for 5G standalone (SA), since the topology between active antenna unit (AAU) and distributed unit (DU) is similar to that between RRUs and BBUs. The energy and transmission efficiency problems should be taken into consideration. In C-RAN, the central BBUs are responsible for coordinated signal processing based on high-performance processors. The RRUs are located at target areas to serve the access equipment [12]. The digital signal transmission between centralized BBUs and distributed RRUs is based on the low-latency and high-capacity passive optical network (PON). Based on current noted radio interface (e.g., common public radio interface (CPRI) [13], e-CPRI [14], next generation fronthaul interfaces (NGFI) [14]), oversampled in-phase/quadrature-phase (I/Q) signals are transferred via capacity-constrained fronthaul network. The transmission efficiency of the optical fronthaul is badly affected, since the CPRI bitrate is constant, independent of the traffic fluctuation [15]. Research on energy efficiency of C-RAN has been widely explored [16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41] from different perspectives, including resource allocation in BBU pool, function splitting, power control in upstream/downstream, etc. However, little attention has been focused on the energy and transmission efficiency of the reconfigurable optical fronthaul, especially for the passive optical networks based fronthaul system. In our previous works, we have discussed the efficient resource allocation algorithms for time and wavelength division multiplexing passive optical network (TWDM-PON) enabled fronthaul under different scenarios [42; 43; 44; 45], but without complete energy consumption consideration. The explosive growth of high dynamic traffic imposes great pressure on internet of things and related networks. As the first network segment to connect smart homes, the mobile fronthaul network faces the dynamic and busty traffic of smart homes. The energy and transmission efficiency has emerged as an important issue on fronthaul networks. As the strict requirement of green communication, how to achieve an energy-efficient configuration becomes more important.