Investigations On Energy Saving Technologies For Heterogeneous Wireless Networks

While mobile communications have made outstanding contributions to the contemporary society, their energy consumption and carbon footprint also increase rapidly. Thus, the research on green communication has received widespread concern in both industry and academia in recent years. The energy efficiency and associated energy saving algorithms and strategies of wireless heterogeneous network are studied in this thesis.Firstly, energy consumption models of base station and several energy efficiency metrics from different perspectives are introduced. The impact on energy efficiency evaluation is studied using two common energy efficiency metrics(W/km2 and bits/Joule) and three typical energy consumption models. The theoretical analysis of two simple optimization problems and their corresponding simulation results show that in energy efficiency study, it’s better to take both network coverage and capacity requirements together into account so that contradictory conclusions can be avoided. Meanwhile, with regard to the energy consumption modeling of base stations, the static power and backhaul overhead may also have a significant impact to the energy efficiency results.Secondly, a sleeping strategy of pico cells is proposed in a special macro-pico two-tier heterogeneous network scenario. The uniqueness of the scenario is that there is coverage overlapping among some pico cells. The key point of the strategy is that it uses the available resources of neighbor pico cells as many as possible to help offloading the associated users of the pico cell when it is ready to be switched off. Thus, while guaranteeing the QoS of users, more pico cells could be switched off to improve energy efficiency. Simulation results show that both the offloading performance and the pico cell switch-off ability of the proposed strategy are better than the normal strategy, which only uses macro cell to offload users, thus making the network more energy efficient.Finally, the optimal energy efficiency and corresponding optimal small cell density of a two-tier heterogeneous network under coverage performance constraints in both co-frequency and anti-frequency networking are studied. Also, the impact of random sleeping strategy on energy efficiency and outage probability of dense small cell scenario is investigated. Based on the theory of stochastic geometry, the mathematical expressions of average outage probability for cell-edge users of both tiers in both co-frequency and anti-frequency networking are derived. After that, the relationship between small cell density and outage probability threshold is obtained. Then, the optimization objective to maximizing energy efficiency is formulated and the binary search algorithm is used to obtain the optimal small cell density. Simulation results show that the energy efficiency of anti-frequency networking is better than that of co-frequency networking. The results also show that the optimal small cell density for maximal energy efficiency is only dependent on the coverage performance requirement of small cells in anti-frequency networking. However, in co-frequency networking, the optimal density is jointly decided by the coverage performance requirements of both macro cell and small cells.