Energy-Efficient Interference Management And Load Balancing In Heterogeneous Networks

With the rapid development of information technologies,such as mobile Internet,Internet of Things,cloud computing,big data and Cyber-Physical system,the appli-cation scope of cellular networks is increasing,and the number of connections and mobile data traffic in cellular networks grow explosively.In this context,the next generation wireless networks will be heterogeneous networks(HetNets)with a large number of base stations(BSs)with disparate transmission power and coverage areas,so as to provide ubiquitous wireless access.Due to the high frequency reuse and short communication distances of low-power BSs,the HetNets can significantly improve the spectral efficiency and energy efficiency at low deployment and operating cost.For both economic and environmental considerations,the energy efficiency of cellular networks has become one of the key performance indicators.However,large-scale deployment of various BSs in HetNets leads to a surge in energy consumption.At the same time,the co-channel deployment of low-power BSs and Macro-BSs result-s in serious cross-and intra-tier interference,and the large disparity of transmission power levels of different types of BSs causes extreme load imbalance.The co-channel interference and load imbalance reduce the spectral and energy efficiency of HetNets,as well the quality of service(QoS).Therefore,the research of energy-efficient inter-ference management and load balancing is of great significance for the performance improvement and QoS enhancing of HetNets.The adopt of energy-efficient power control and user association,the optimization of user association and resource allocation in the renewable energy powered HetNets,and the design of joint cell deactivation and user association,are feasible and effective measures for the energy-efficient interference management and load balancing in Het-Nets.However,unlike the centralized optimization in traditional cellular networks with a single type of BSs,the energy-efficient interference management and load balancing in HetNets with above measures facing the following technical challenges:(1)the high density distribution of different types of BSs and users makes it difficult to achieve centralized optimization of transmission power and user association;(2)the dynamic and uncertain available energy of BSs affects the user association and resource alloca-tion when BSs are powered by renewable energy and hybrid energy;(3)the stochastic optimization of joint cell deactivation and user association for energy saving facing the tradeoff between energy consumption and service delay.In this regard,the main research work and contributions of this dissertation are as follows:(1)Co-channel interference mitigation,load balancing and energy consumption reduction through energy-efficient user association and power control.Firstly,for the cross-and intra-tier interference management of two-tier femtocel-1 networks with co-channel deployment and closed access of femtocells,considering the different priorities and service requirements of users in two tiers,this dissertation develops power update rules for users based on a multi-leader and multi-follower hier-archical game,so as to energy-efficiently satisfy the desired service requirements of all the users and protect the high-priority macrocell users at the same time.In particular,taking into account the channel uncertainty,a robust hierarchical game is proposed to obtain the robust power update rules for users.Simulation results validate the fast con-vergence of the proposed power update rules,and their effectiveness in improving the QoS and reducing the power consumption of users.Then,for the interference manage-ment and load balancing in HetNets with small cells being open access,this dissertation develops energy-efficient joint uplink and downlink user association and power con-trol schemes.An iterative method is adopted to decouple and update the matching based user association and the improved Newton method based power allocation of B-Ss respectively and in turn.Simulation results show the effectiveness of the proposed algorithm in improving system energy efficiency and uplink network capacity.(2)Energy-aware joint user association and resource allocation for load balancing in the HetNets powered by renewable and hybrid energy.Firstly,for the renewable energy powered HetNets,defining the load of BSs as their radio resource consumption and taking into account the long-term rate require-ments of users,this dissertation maximizes the network-wide weighted utility of load efficiency in a time duration to optimize the use of BSs' radio resources and renewable energy.Then,the formulated non-convex and continuous problem is solved by relax-ation,discretization and dual decomposition,and an optimal offline algorithm and two sub-optimal online algorithms with low-complexity are obtained.Simulation results show the improvement of load balancing and decreasing of call blocking probability with the proposed algorithms.Then,for the hybrid energy powered HetNets,both en-ergy and backhaul constraints are taken into account,and the network utility in terms of throughput and reflecting proportional fairness is maximized so as to improve the QoS of best-effort users.Then,due to the tight coupling of user association and resource allocation on the available radio resources,energy,and backhaul of BSs,several de-composition methods are applied to develop the distributed joint strategy.Simulation results valid that the proposed joint algorithm significantly balances the load of BSs and improves both the network capacity and user fairness.(3)Reduction of energy consumption while balancing the load of BSs by queue-aware joint user association and small cell deactivation for traffic offloading of macro-cell via dual-connectivity.Based on the fact that most of mobile users in an extreme dense HetNet are likely to be located in the overlapping coverage areas of multiple radio access technologies,this dissertation studies the energy-saving traffic offloading via dual-connectivity.Consid-ering the random traffic arrivals of users and time-varying channel fading,a stochastic optimization of user association and small cell deactivation in two timescales is for-mulated.Then,the two-stage Lyapunov optimization technique is applied to design the online and queue-aware joint algorithm,which selects the active small cells and determines the user association in the large and small timescales respectively.Finally,simulation results demonstrate that the proposed joint algorithm provides a flexible and effective means to control the tradeoff between energy cost and delay.