Wireless sensor networks (WSNs) and power line communications (PLCs) are used in this work to implement a smart home control network. The goals are to reduce the impact of wireless interference on a smart home control network and unnecessary energy consumption of a smart home. An isolated WSN with one coordinator, which is integrated into the PLC transceiver, is established in each room. The coordinator is responsible for transferring environmental parameters obtained by WSNs to the management station via PLCs. The control messages for home appliances are directly transferred using PLCs rather than WSNs. According to the experimental results, the impact of wireless interference on the proposed smart home control network is substantially mitigated. Additionally, a smart control algorithm for lighting systems and an analysis of the illumination of a fluorescent lamp were presented. The energy saving of lighting systems relative to those without smart control was evaluated. Numerical results indicate that the electricity consumption on a sunny or cloudy day can be reduced by at least 40% under the smart control. Moreover, a prototype for the proposed smart home control network with the smart control algorithm was implemented. Experimental tests demonstrate that the proposed system for smart home control networks is practically feasible and performs well.

To reduce the peak load and electricity bill while preserving the user comfort, a quality of experience (QoE)-aware smart appliance control algorithm for the smart home energy management system (sHEMS) with renewable energy sources (RES) and electric vehicles (EV) was proposed. The proposed algorithm decreases the peak load and electricity bill by deferring starting times of delay-tolerant appliances from peak to off-peak hours, controlling the temperature setting of heating, ventilation, and air conditioning (HVAC), and properly scheduling the discharging and charging periods of an EV. In this paper, the user comfort is evaluated by means of QoE functions. To preserve the user’s QoE, the delay of the starting time of a home appliance and the temperature setting of HVAC are constrained by a QoE threshold. Additionally, to solve the trade-off problem between the peak load/electricity bill reduction and user’s QoE, a fuzzy logic controller for dynamically adjusting the QoE threshold to optimize the user’s QoE was also designed. Simulation results demonstrate that the proposed smart appliance control algorithm with a fuzzy-controlled QoE threshold significantly reduces the peak load and electricity bill while optimally preserving the user’s QoE. Compared with the baseline case, the proposed scheme reduces the electricity bill by 65% under the scenario with RES and EV. Additionally, compared with the method of optimal scheduling of appliances in the literature, the proposed scheme achieves much better peak load reduction performance and user’s QoE.

To reduce power consumption of smartphones, this work proposes a novel discontinuous reception (DRX)-based power saving mechanism for LTE-A networks supporting multi-services. The novel designs of the proposed mechanism mainly include the highest priority-controlled DRX (HPC-DRX) and traffic regulation plus time slicing (TRTS) schemes. In our proposed HPC-DRX/TRTS, lower priority traffic never wakes user equipments (UEs) up and all incoming traffic for UEs is temporarily buffered at the evolved Node B (eNB) and then transmitted in bursts using the overall bandwidth, yielding much better power saving performance. To support multiple users with multi-services, this paper proposes the resource allocation and burst scheduling algorithms for the HPC-DRX/TRTS. The power saving ratios of the proposed mechanisms were theoretically analyzed based on an M/G/1 busy period model. Both the percentage of sleep period and actual power consumption model were used in calculating the power saving ratio. Numerical results show that our analytical results are accurate and the proposed HPC-DRX/TRTS significantly outperforms the conventional DRX, dynamic and adjustable DRX (DADRX), and coalesced DRX in terms of power saving ratio. In addition to significantly reducing power consumption of UEs with video streaming services and diverse data applications (DDA), the proposed HPC-DRX/TRTS preserves the video playout quality at UEs as well.

Unicast Internet protocol television (IPTV) services that can support live TV, video-on-demand, video conferencing, and online gaming applications over broadband wireless cellular networks have been becoming popular for many years. However, video streaming services significantly impact the performance of wireless cellular networks because they are bandwidth hogs. To maintain the system performance, effective admission control and resource allocation mechanisms based on an accurate mathematical analysis are required. On the other hand, the quality of a wireless link usually changes with time because of user mobility or time-varying channel characteristics. To counteract such time-varying channels and improve the spectral efficiency, an adaptive modulation and coding (AMC) scheme is adopted in offering unicast IPTV services for mobile users. In this paper, closed-form solutions for the bandwidth usage, blocking rate, and dropping rate of unicast IPTV services over wireless cellular networks were derived based on the novel queueing model that considers AMC. Simulations were also conducted to validate the accuracy of analytical results. Numerical results demonstrate that the presented analytical results are accurate. Based on the accurate closed-form solutions, network providers can implement precise admission control and resource allocation for their networks to enhance the system performance.