| With the rapid development of modern wireless communication technology and the explosive growth in recent decades,the B5 G era,which is different from the previous generations of traditional communication technology,has arrived.B5 G is an extension of5 G technology,which is no longer the name of a specific technology,but a representative of multi-technology and business integration and a perfect process to solve some application scenarios and technologies.Higher transmission rates and more real-time,more accurate location services also make it a key driver to build intelligent networks.New technologies are proposed in 5G network,such as mm-Wave communication,Multi-user Massive MIMO transmission,etc.Mm-wave spectrum ranges from 30 GHz to300GHz,providing extremely high data rates through rich spectrum resources.High resolution and highly directional transmitting beams produced by MIMO systems using large-scale antenna arrays can also provide extremely accurate positioning information.Therefore,the research of communication positioning integration based on the combination of mm-Wave and MU-MIMO technology has strong practical significance.However,providing communication and positioning functions at the same time will face the challenge of sharing limited wireless resources(such as frequency,power and space beam resources).When communication signals and positioning signals are orthogonal transmitted under different time frequency resources,the increase of communication data rate will lead to the decrease of positioning accuracy,and vice versa.Then,how to allocate these multi-dimensional resources in the integrated communication positioning network is the main research problem of this thesis.The main contributions of this thesis are as follows:1.In this thesis,the multi-dimensional resource allocation of mm-Wave time division OFDMA communication location is decomposed into two parts: communication performance and location performance.In the communication problem,the total rate of multi-user system is derived as the measurement index of communication performance based on user signal-to-noise ratio.For the positioning problem,FIM and CRLB theories are used to deduce the positioning error,PEB and OEB under multi-carrier,and the overall positioning error combined with square PEB and square OEB is used as the measurement index of positioning performance.The multi-dimensional resource allocation problem is divided into beam resource allocation problem and power and subcarrier resource allocation problem.The idea of solving the beam resource allocation problem is to use a low complexity beam allocation algorithm and solve the problem.The idea of solving the power and subcarrier resource allocation problem is to transform the problem into a convex optimization problem based on DCFA,and solve the problem.The multi-dimensional resource allocation problem is divided into beam resource allocation and power and subcarrier resource allocation.The idea of solving the beam resource allocation problem is to use a low complexity beam allocation algorithm and solve the problem.The idea of solving the power and subcarrier resource allocation problem is to transform the problem into a convex optimization problem based on DCFA,and solve the problem.2.In this thesis,we analyze the shortcomings of traditional grouping algorithm in MU-MIMO downlink user grouping.In order to improve the existing multi-user grouping algorithm based on channel main path,we take the power status information of each path(eigenvalue)as a weighting factor,and sum the status information of each path(eigenvector)as the improved user channel vector,so as to improve the accuracy of user grouping.In the design of multi-user grouping algorithm,the highly correlated users are divided into different groups by the user channel vector,and the grouping process depends on finding the correlation coefficient greater than a certain threshold value and separating the corresponding users into different groups.The threshold value is variable and can be adjusted to achieve the best performance compared to the non grouping scenario.Under the conditions of power,minimum communication rate and user grouping,an optimization model of integrated resource allocation for communication positioning is constructed.Finally,under the conditions of minimum communication rate,peak power and user grouping,an optimization model of integrated resource allocation for communication and positioning is established,and the influence of different number of users,different number of transmitting antennas and different reference thresholds on positioning and communication performance is verified by simulation. |
