Research On Resource Allocation Techniques For Cell-Free Massive MIMO Systems

For cellular network structure,cell edge effect is the main factor limiting its network performance.In the communication era of 4G and before,because of the low density of base stations and UEs(User Equipments),edge effect is not the primary factor limiting network performance.However,with the increase of the density of base stations/APs(Access Points),the intensive trend of wireless communication in the future will bring more inter cell interference,and the edge effect will also become a bottleneck limiting the network performance.De-cellular is an inevitable trend of the evolution of access network architecture.Cell-Free massive MIMO(Multiple Input and Multiple Output,MIMO)has the characteristics of massive MIMO and distributed antenna systems.It can obtain the gain of the above two systems at the same time,and is a promising network structure.In a Cell-Free massive MIMO system,AP selection,power control/allocation,pilot allocation and precoding are the keys to improve system performance.Based on this network architecture,this thesis studies the resource allocation technology in the Cell-Free massive MIMO system,mainly including the following three aspects:Firstly,the spectral efficiency(SE)optimization of the user-centric Cell-Free massive MIMO system is studied,and a transmission scheme of joint power allocation and AP selection is proposed.By introducing parameters representing the UE-AP connection relationship,aiming at maximizing the UEs’ sum-rate,the Lagrange dual function method is used to jointly optimize the AP selection and downlink power.Compared with solving the power allocation problem based on convex optimization,the method proposed in this thesis has less restrictions on the characteristics of the objective function,and is less difficult to solve,while making up for the performance loss of the step-by-step algorithm.The simulation results show that when the maximum transmission power per AP is 1W,the proposed joint power allocation and AP selection transmission scheme in this thesis improves spectral efficiency by 1.8%and energy efficiency by 2.1%compared to the AP selection algorithm based on large-scale fading coefficients using partial power allocation.Secondly,the energy efficiency(EE)optimization problem of the group-user-centric Cell-Free massive MIMO system is studied.Considering the interaction between AP selection and pilot allocation,a transmission method combining AP selection and pilot allocation is proposed.Pilot allocation is performed on the selected active AP set,and the result of pilot allocation will affect the update of AP selection and power allocation results.The optimization is repeated until the energy efficiency converges.The pilot allocation method adopts the grouping sorting pilot allocation algorithm based on channel similarity and geographical location proposed in[3 1],which reduces pilot contamination by allocating orthogonal pilots to UEs with high channel similarity and close geographical location;AP selection and power allocation are based on convex optimization with minimum power consumption.The simulation results show that when the maximum transmission power per AP is 2W,compared to existing transmission schemes that only combine AP selection and power allocation,the joint AP selection and pilot allocation transmission method reduces total power consumption by 18.5%and can improve energy efficiency by 24.0%.Thirdly,the role of pilot power control in suppressing pilot contamination and improving system performance under the condition of limited orthogonal pilot resources is studied,and a pilot power control optimization scheme is proposed,aiming at maximizing the sum of channel estimation variances,and the pilot power control coefficient is optimized based on Lagrange dual function method.Compared with the original sequential convex approximation method,the method proposed in this thesis does not need to solve the original non-convex problem after complex transformation,and the calculation complexity is low.The simulation results show that optimizing the pilot power control coefficient based on the first research point can increase spectral efficiency by 1.5%and energy efficiency by 3.4%.Moreover,in the case of more limited orthogonal pilots,the improvement in spectral efficiency and energy efficiency is more significant;Based on the second research point,optimizing the pilot power control coefficient can improve energy efficiency by 35.5%.