Cross-Layer Energy-Efficient Mobile Network Design

Abstract: To assure the sustainable development of mobile networks, it is crucial to improve their energy efficiency. This thesis is devoted to the design of energy-efficient mobile networks. A cross-layer design approach is adopted. The resource management at the MAC layer, the network layer as well as the service layer are optimized to improve the energy efficiency of mobile networks. The problem of optimizing the MAC-layer resource allocation of the downlink transmission in multi-carrier NOMA systems to maximize the system energy efficiency while satisfying users’ QoS requirements is firstly considered. The optimal power allocation across sub-carriers and across users sharing one sub-carrier are proposed. Furthermore, exploiting the structure of the optimal power allocation across users sharing one sub-carrier, a sub-optimal solution for sub-carrier assignment, which greedily minimizes the required power to serve all users with required QoS, is developed. Besides optimizing the channel assignment and power allocation within a single cell, the link scheduling in the multi-cell scenario to deal with inter-cell interference is also studied. A scalable distributed link scheduling solution is proposed to orchestrate the transmission and DTX micro-sleep of multiple base stations such that both the inter-cell interference and the energy consumption are reduced. At the network layer, the operation of base station sleeping is optimized to improve the energy efficiency of mobile networks without deteriorating users’ QoS. The spectral and energy efficiency of mobile networks, where base stations are enabled with DTX, under different traffic load is firstly studied. It shows that as the networks are more loaded, the link spectral efficiency reduces while the network spectral efficiency increases. Regarding the network energy efficiency, it will either firstly increase and then decrease or always increase when the network load gets higher. The optimal network load to maximize the network energy efficiency depends on the power consumption of base stations in DTX sleep mode. Based on the findings of the above study, the joint optimization of cell DTX and deep sleep to maximize the network energy efficiency is investigated. A scaling law of transmit power, which assures that the distribution of the received power remains unchanged as more base stations are switched into deep sleep, is proposed. Then the average resource utilization and overload probability of non-deep-sleep base stations are derived. Based on these results, the feasible range of the percentage of deep-sleep base stations is obtained. Finally, the optimal percentage of deep-sleep base stations to maximize the network energy efficiency while satisfying users’ QoS requirements is derived. Lastly, the service-layer resource provision of edge computing in mobile networks is optimized to improve the energy efficiency. With this work, the trade-offs on service latency and energy consumption between the computation and the communication subsystems are studied. It is shown that the load of the communication subsystem and that of the computation subsystem should be balanced. Increasing the resource of the highly loaded subsystem can significantly reduce the required resource of the other subsystem. An algorithm is proposed to find out the optimal processing speed and the optimal number of active base stations that minimizes the overall energy consumption while assuring the requirements on the mean service latency.