Joint Optimal Multi-connectivity Enabled User Association And Power Allocation In Mmwave Networks

The millimeter wave(mm Wave)pectrum has been involved in the fifth generation wireless systems(5G)for its enormous spectrum resources.However,signals over mm Wave band suffer from severe path loss and are vulnerable to be blocked by obstacles due to the extremely high frequency,which greatly degrades the the quality of transmission and connection reliability.One of the promising ways to overcome this problem is the multi-connectivity technology,which allows a user in a mm Wave network to associate with multiple mm Wave base stations(m BSs).And for multi-connectivity,there are two essential challenges: one is the optimal user association,that is,which are the most appropriate m BSs a user should be connected to,and the other is the optimal power allocation of each connection.In view of this,this article has carried out the following work to jointly optimize the user association and optimal power allocation for multi-connectable mm Wave networks:1.We established a model of joint optimal multi-connectivity enabled user association and power allocation(MCUA-PA)for mm Wave networks.Different from most existing works,the optimization objectives in our work are three-fold,namely maximizing the overall energy-efficiency and meanwhile balancing the achievable rates among all users and the load among all m BSs,respectively,under the Qo S constraint.This is a multi-objective optimization problem(MOPs).2.Considering that this multi-objective problems is a mixed integer programming and NP-hard,this paper proposes a method based on a new multi-objective Harris Hawk Optimization(MOHHO)algorithm to obtain the near-optimal solutions.The algorithm uses a fast non-dominated sorting method for archiving and a reference point selection method to make the population have a better uniform distribution.In order to speed up the convergence of the algorithm and jump out of the local optimum,we also introduces a logical chaotic sequence to disturb the population.We adopted 31 multi-objective benchmark functions and other common multi-objective algorithms to compare the mean and variance of the inverse generation distance(IGD),the experimental results verify the convergence,accuracy and diversity of the solution obtained by MOHHO optimal.In addition,the communication application scenario of multi-connectivity and downlink power allocation in this article have the characteristics of large-scale decision variables,and the number of decision variables increase by a corresponding multiple as the number of users and base stations increase.Therefore,we extended the decision variables of31 benchmark functions to one thousand dimensions,and compared the IGD indicators and the Wilcoxon signed-rank test.Experimental results show that the MOHHO algorithm proposed in this paper is still superior to the other seven comparison algorithms in terms of convergence,diversity and accuracy.3.Through the mathematical model established above,the MOHHO algorithm proposed in this paper is used to jointly optimize the MCUA-PA problems,and achieve the three goals of maximum system energy efficiency,user service quality balance,and m BSs service balance.The simulation results of application scenarios show that the proposed scheme enables optimal multi-connectivity enabled user associations and power allocations simultaneously in ultra-dense mm Wave networks and yields EE-fairness tradeoff.