Research On Resource Management In D2D Underlaying Cellular Networks

Nowadays,local communication services,such as video sharing,on-line game,and social media,have been extensively applied in wireless networks.In order to support the real time and high throughput requirement of these services,researchers and engineers have proposed the Device-to-Device(D2D)communication in cellular networks,which can increase spectral efficiency and energy efficiency,reduce transmission delay,and help offload traffic from cellular networks.However,the complex conflict of resource usage among cellular users(CUEs)and D2D pairs needs to be efficiently handled for D2D underlaying cellular networks.Taking the throughput as the optimization metric,this dissertation first investigates the optimal resource control for a single-cell D2D overlaid cellular network,then studies the joint Successive Interference Cancellation(SIC)and power control design for D2D communication underlaying a multi-cell network with hybrid energy source.In addition,future wireless networks will have a high density of communication nodes.In order to decrease the computation complexity and signaling overhead of resource control strategies,the dissertation designs a distributed resource control strategy for D2D communication underlaying large wireless networks.The main contributions of the dissertation are listed as follows:1.The second chapter studies the resource control in a D2D overlaid single-cell cellular network.Considering dynamic traffic arrival,time-varying channel fading,and coupled control variables,we design a Delay-aware Traffic admission,Mode selection,and Resource allocation(DTMR)strategy.The DTMR strategy is developed based on Lyapunov optimization,dual optimization,and ellipsoid search with polynomial time complexity.Also,the DTMR strategy aims to maximize the time-average sum-rate of the network,subject to the time-average throughput guarantee of users.Specifically,traffic admission limits queueing delay,mode selection exploits the proximity gain,and resource allocation guarantees user performance.In addition,compared to symmetric channel assumption for the two-hop links of BS-assisted D2D communication in previous works,the incorporation of real asymmetric channel state in BS-assisted D2D communication complicates the optimization problem but provides more flexibility to dynamically control resource.We also analytically derive the lower bound of the time-average sum-rate achieved by the proposed DTMR strategy.Further,we develop a heuristic strategy by decoupling the binary constraints of mode selection and channel assignment.Finally,simulation results demonstrate that the superiority of the DTMR strategy against alternative strategies.2.The third chapter investigates the power management and resource control in a D2D underlaid multi-cell cellular network with hybrid energy source.Considering dynamic traffic arrival,time-varying channel fading,random renewable generation,and multiple energy consumption,we propose a LSPSCA strategy with an optimal traffic admission scheme and a two-stage SIC-based power control method.The LSPSCA strategy is developed by the perturbed Lyapunov optimization and sequential convex programming.In addition,the LSPSCA strategy attempts to maximize the time-average total throughput of network,subject to the SIC feasibility,queueing stability,finite energy storage,and energy balance.The LSPSCA strategy appropriately balances the supply,demand,and finite storage of renewable energy based on the stabilization of renewable energy queues.Further,the traffic admission balances the tradeoff between the total throughput and queueing delay.Joint SIC scheduling and power control mitigates the intra-tier and cross-tier interference among CUEs and D2D pairs.Moreover,the two-stage SIC-based power control strategy first designs a simple SIC scheduling method according to the fact that the benefit of SIC highly depends on the strength of interfering signals at a receiver.Then,the feasible conditions of SIC scheduling are converted to a set of linear constraints on the channel fading and transmit power vector.Based on the “convex-minus-convex” property in the objective of power control problem,the LSPSCA strategy applies the sequential convex programming to obtain a local optimum with low complexity.Simulation results demonstrate that the traffic admission can balance the tradeoff between the total throughput and queueing delay,and verify the gain of joint SIC scheduling and power control.3.Considering the densification of future wireless networks,the fourth chapter investigates the distributed resource control for D2D communication underlaying large wireless networks,where the locations of base stations(BSs),CUEs,and D2D transmitters follow independent Poisson Point Process(PPPs).According to Fractional Frequency Reuse(FFR)scheme and channel fading statistics,we derive the SINR coverage probability of CUEs based on stochastic geometry tools.Under a distributed D2D power control framework,the SINR coverage probability requirement of CUEs is equivalently transformed into the time-average constraint on the transmit power of D2D transmitters,which quantifies the impact of D2D communication on the CUE uplink communication.Further,this D2D power constraint is defined as the individual budget of interference from each D2D pair to CUEs,which is related to the density of both BSs and D2D pairs,CUE requirements,the radius of an interior circle,and channel parameters.The D2D Individual Interference Budget(IIB)may be calculated and broadcast by BSs to each D2D pair at the initial stage.Based on the D2D individual interference budget,accounting for time-varying channel fading and dynamic D2D traffic arrival,we design a distributed interference-and-delay-aware(DIDA)traffic admission and power allocation strategy based on Lyapunov optimization and several interference estimation methods.By applying the DIDA strategy,the D2D pairs individually attempt to maximize their own time-average throughput utility,while collectively guaranteeing the time-average SINR coverage probability of CUEs in multiple cells.Moreover,we also analytically derive the performance bounds of D2D pairs and prove that the SINR coverage probability of CUEs can be guaranteed regardless of the interference estimation error at D2D receivers.Finally,simulation results suggest that adaptive interference estimation methods are preferred and demonstrate that the DIDA strategy achieves substantial performance improvement against alternative strategies.