| In order to meet the human requirements for high speed,low latency and massive access in wireless communication,the fifth generation(5G)mobile communication with the core technology of massive multipleinput multiple-output(MIMO)has emerged and is gradually being commercialized.This is because massive MIMO has a high degree of spatial freedom and multiplexing gain,which can effectively improve the systematic spectral efficiency and energy efficiency.However,the construction of5 G is still in its early stages and faces many challenges and urgent problems to be solved.These problems may even require beyond 5G or the sixth generation mobile communication to solve it.One of the key challenges is how to fully exploit the huge potential of massive MIMO,adapt to the needs of a variety of scenarios,and optimize the allocation and scheduling of increasingly scarce resources in time,frequency,and power domains,in order to break the bottlenecks of spectral efficiency(SE)and energy efficiency.In view of this,this paper focuses on this issue,and innovations are summarized as follows:(1)A joint pilot allocation and power control optimization algorithm is proposed for time-division duplex cellular massive MIMO systems to address the problem of severe pilot massive limiting the improvement of SE for users located at the edge of the cell.Firstly,based on the system model,the problem is modeled as a multivariable highly coupled maximizing minimum SE problem.Then,in order to solve this thorny non-convex problem,the proposed algorithm decomposes the problem into two easy-to-handle sub-problems and iteratively processes them.When the power is fixed,the weight graph coloring(WGC)algorithm is used to solve the sub-problem of pilot allocation.When the pilot allocation pattern is fixed,the geometric programming(GP)is used to solve the sub-problem of power control.By analyzing the complexity of the algorithm,the proposed algorithm has a very low computational complexity compared to some solutions that require exhaustive search.Finally,the simulation results demonstrate that the proposed algorithm significantly improves the minimum SE,which is close to the ideal optimal solution.(2)The pilot contamination and active sensors(ASs)interference can seriously limit the further improvement of SE in cell-free(CF)massive MIMO internet-of-things(Io Ts).Firstly,a joint pilot and data power control optimization problem based on maximizing sum SE is modeled based on system model.Since this problem is also non-convex,a successive convex approximation iterative algorithm is proposed to solve it.The core idea of this algorithm is to convert the initial optimization problem into a manageable GP problem by approximating the objective and constraint functions during each iteration,and then use CVX tools to solve it.Finally,simulation results show that our proposed algorithm outperforms the existing algorithms related to power control optimization in terms of the sum SE performance.(3)For a CF massive MIMO Io T system with simultaneous wireless information and power transfer(SWIPT),we firstly derive the average harvesting energy(HE)and downlink SE for maximum ratio transmission(MRT)and full-pilot zero-forcing(FZF)precoders.Then,we formulate the joint power control and splitting optimization problem to maximize the sum SE while guaranteeing the minimum SE and HE requirements at each AS.Since the problem is a multivariate coupled intractable non-convex problem,we propose an algorithm to first decompose the problem into three subproblems by Lagrangian dual reformulation and quadratic transformation,and then solve it by alternating optimization.Finally,simulation results demonstrate that the proposed algorithm is convergent and can achieve a substantial improvement of sum SE.(4)Taking into account the effects of successive interference cancellation and pilot contamination for SWIPT in non-orthogonal multiple access(NOMA)-assisted CF massive MIMO Io T,we first derived the closedform expressions of HE and SE for MRT and FZF precoders,respectively.Thus,the optimization problems of joint downlink power control and splitting based on maximizing the HE and maximizing the energy harvesting efficiency are formulated while ensuring the minimum SE and HE requirements of each AS.For the first optimization problem,a series of deformations and semidefinite relaxation techniques are used to solve it.For the second optimization problem,an iterative algorithm with successive convex approximation is proposed to solve it in addition to the similar treatment of the first optimization problem.Finally,the simulations show that two proposed algorithms have significant improvement of performance and good convergence. |
