Research On Energy-saving Wireless Transmission Technologies In Distributed Antenna Systems

In recent years,energy crisis and environmental problems have become the bottleneck of human sustain-able development.At the same time,the rapid development of IoT(Internet of Things)and mobile internet has promoted the research of the fifth generation(5G)mobile communication system.Huge data transmission and energy consumption are an urgent problem to be solved.In this context,the research of energy-saving transmission technology has been proposed in 5G wireless communications field.DAS(Distributed Antenna Systems)reduces the transmission power of the system by reducing the average access distance between the users and RAU.At the same time,in the large-scale distributed antenna systems,it significantly improves the coverage area of cellular system.Therefore,it is meaningful to study the technology of distributed antenna systems in energy-saving transmission.Under the background of "green communication" and 5G mobile communication systems,we first analyze the power consumption model and energy efficiency of the dis-tributed antenna systems.Then,in order to make full use of renewable energy,a novel hybrid energy supply distributed systems architecture is proposed,and the power allocation scheme of hybrid energy supply dis-tributed antenna systems under different criteria is studied.In addition,we also consider the energy-efficient large-scale distributed antenna systems combined with RAU clustering and cooperative beamforming.Firstly,we introduce the statistical characteristics of the wireless channel model.At the same time,the basic theory of massive MIMO and large-scale distributed antenna systems is given.In addition,the energy efficiency of a single-cell large-scale distributed antenna systems is analyzed in detail.Some properties of energy efficiency under the real and the ideal power consumption models are analyzed and compared with massive mimo.Finally,a energy-efficient heuristic RAU selection algorithm is proposed.Simulation results show that our heuristic algorithm is more energy effective than the traditional RAU selection algorithm.Then,a novel hybrid energy-supplied transmission model is studied for multi-user orthogonal access distributed antenna systems.The system preferentially uses the harvested energy and then uses the grid power when the harvested energy is insufficient.This strategy guarantees the user's QoS requirements.Based on the Minimizing Grid Power(MGP)and the Maximized Energy Efficiency(MEE)criteria,two different power allocation algorithms are designed.In the MGP criterion,an optimal power allocation iterative algorithm is proposed by using sub-gradient and Lagrangian dual method.In the MEE criterion,the optimization problem is non-linear nonconvex and it can not be directly solved.According to the feature of the objective function,the Dinkelbach method is used to transform the fractional optimization problem into a form of subtraction,and then an energy efficiency scheme is proposed.Simulation results show that our heuristic algorithm is more energy effective than the traditional RAU selection algorithm.Simulation results show that the power allocation algorithm under the two criteria can reduce the grid power consumption and improve the energy efficiency of hybrid energy-supplied DAS when the harvested energy is sufficient.In addition,we consider the power allocation problem in hybrid energy-supplied distributed antenna sys-tems where users are non-orthogonal access.Three criteria of power allocation are proposed based on mini-mizing the grid power,maximizing the sum rate and maximizing the energy efficiency respectively.Because of the interference between users,problems can not be directly resolved.For the problem of minimizing the grid power and maximizing the sum rate,the original problems are transformed into geometric programming problems,then the geometric programming problems are transformed into the convex optimization problems by using continuous geometric programming(SGP)method.The corresponding power allocation algorithms are proposed.For the problem of maximizing the energy efficiency,the original problem is first transformed into a fractional programming problem,and then it is transformed into a geometric programming problem.At last,we propose the energy-efficient power allocation scheme.Depending on application environments,we can use the first and second criteria to achieve the highest throughput and to save the most grid power,respectively,while we can balance throughput and energy consumption using the third criterion.Finally,we study the energy-efficient RAU clustering and cooperative beamforming in multi-cell multi-user large-scale distributed antenna systems.It mainly includes two problems:cooperative beamforming under heuristic clustering and sparse beamforming under dynamic clustering.The former problem is to se-lect a set of RAU close to the user,and then design the optimal beamforming scheme.By using the novel WMMSE method,the weighted sum energy efficiency problem is transformed into the equivalent WMMSE problem.A distributed WEEM algorithm is implemented in the large-scale MIMO system.The latter not only considers the user-centric dynamic clustering problem,but also takes the limited backhaul capacity in-to account.we first formulate the RAU clustering as a l0-norm problem.By using the weighted l0-norm technique in compressive sensing,the approximate expression of backhaul link constraint is obtained.The dynamic clustering problem is transformed into the l0-norm of sparse beamforming.Finally,the problem of maximizing weighted energy efficiency under limited RAU backhaul and transmit power is transformed into a WMMSE problem.A stationary solution is obtained by block coordinate descent method.Simulation results show that the user-centric dynamic clustering algorithm is more energy effective than the heuristic clustering algorithm.