Research On Energy Efficiency,asynchronous Reception And Covariance Estimation Of C-RAN Systems

The development of mobile Internet has promoted the development of 5G(the Fifth Generation Mobile Communication System).C-RAN(Cloud-Radio Access Network),as a promising antenna deployment architecture in 5G,has great advantages in terms of energy efficiency,transmission rate,system capacity,and operation and maintenance costs.With the rise of green communications,energy efficiency has become an important indicator of the quality of communication systems.OFDM(Orthogonal frequency division multiplexing),as one of the key technologies of 4G(the Forth Generation Mobile Communication System),has a unique advantage in combating frequency-selective fading channels,which also makes it one of the research hotspots in industry and academia.In a real wireless transmission system,there will be various problems.On the one hand,because multiple base stations(BS)cooperate to serve users,the issue of asynchronous reception has to be considered.On the other hand,how to obtain CSI(channel state information)is an old question,and it is also the key to exert the great advantages of C-RAN architecture.In practical transmission systems,obtaining large-scale fading information is as important as small-scale fading information.Based on the OFDM transmission system under the C-RAN architecture,the energy efficiency,asynchronous reception effect,and large-scale estimation techniques are studied.Firstly,the related history and basis of wireless communication are introduced,and the C-RAN system architecture and OFDM modulation technology are briefly introduced,which lays the foundation for subsequent research.Subsequently,in order to solve the problem of system energy efficiency,an energy consumption optimization algorithm for MIMO(multiple-input multiple-output)-OFDM system under C-RAN architecture is proposed.This algorithm aims to give full play to the C-RAN architecture's control capabilities under the conditions of Qo S(users' quality of service)constraints and RAU(remote antenna unit)transmit power constraints,and optimize system energy consumption while allowing partial RAUs to be turned off.In order to solve the complex combinatorial optimization problem,the group sparse beamforming framework is extended to the downlink C-RAN system based on MIMO-OFDM,and the related conditions are transformed by DC programming(Difference of Convex).Then an iterative algorithm is finally proposed.Simulation results show that the algorithm can effectively reduce system transmit power and total network power consumption,and the number of RAUs in working mode is well controlled.Then,in response to the effect of the asynchronous reception effect,an asynchronous transmission model of a MIMO-OFDM system under the C-RAN architecture is established,and the user rate expression under the influence of the asynchronous reception effect is derived from the signal.The impact resulted from the destruction of the orthogonality of subcarriers is very small.Therefore,only considering the phase noise due to the asynchronous reception effect with imperfect CSI and channel estimation,the closed form expression of users reachable rate is derived with the maximum ratio transmission(MRT)beamforming.The simulation shows that the closed form expression matches the simulation value well,and the asynchronous reception effect does affect the system performance.Finally,for imperfect large-scale fading information,the related channel estimation techniques in the C-RAN system architecture are explored.Based on the criterion that the large-scale fading information is invariable within certain coherent blocks,the covariance estimation technology is introduced into the C-RAN architecture.The large-scale fading information is estimated by allocating more pilots in different coherent blocks to achieve better system performance.Then,the spectrum efficiency of the system is analyzed,and the closed form expression of user rates based on the maximum ratio combining(MRC)receiver is derived.Simulations show that the closed expression matches the simulation value well,and large-scale fading estimation techniques can improve the system performance.