Spectral And Energy Efficiency Oriented Wireless Resources Allocation In Massive MIMO Systems

Along with the rapid development of the social information process,human soci-ety has gradually entered the information age.With the access of massive terminals and the emergence of more diverse wireless services,the demand for wireless communica-tion is increasing rapidly.The existing wireless communication systems can not meet the extreme requirements for wireless communication now.However,the performance improvement of wireless communication systems faces severe challenges,including but not limited to the limited spectrum resources,increasingly serious interference,and lim-ited energy.As the latest research result of multi-input multi-output(MIMO)technology,massive MIMO technology can obtain huge degree of freedom,achieve great spatial mul-tiplexing gains and eliminate interference,thus can greatly improve spectral efficiency and energy efficiency.As as result,it is considered to be one of the key technologies of the future wireless communication systems.Therefore,massive MIMO technology will become one of the foundations of 5G communication systems and appears in a variety of wireless communication scenarios.With the objective to realize the enormous potential of massive MIMO technology,many key issues need to be addressed.Among them,how to efficiently manage and optimize the wireless resources in time domain,frequency do-main,spatial and power domain,and achieve the comprehensive improvement of system performance is a very important scientific problem in the application of massive MIMO technology.This is also the key problem of this thesis.This thesis takes the massive MIMO technology as the core,and aims to improve the spectral efficiency and energy efficiency of the system.Regarding the efficient allo-cation of resources as the key points of breaking through,the work in this thesis mainly study the resource management and optimization technologies in massive MIMO enabled scenarios.What's more,resource management and optimization are cooperated with mul-tiple technologies such user association,distributed antennas and energy harvesting.The scenarios investigated in this thesis include multi-cell multi-user massive MIMO systems,distributed massive MIMO systems,and massive MIMO enabled simultaneous wireless information and energy transmission systems.The main contributions are summarized as follows:1)The optimal pilot allocation scheme in multi-cell multi-user massive MIMO sys-tems has been investigated.Focused on multi-cell multi-user massive MIMO systems,the influence of pilot contamination has been researched,and an optimal pilot allocation scheme has been proposed to maximize the sum achievable rate of the system.The formu-lated optimization problem is of non-convex form,thus an optimize algorithm has been proposed to transfer the original problem into linear programming form.Simulation re-sults show the effectiveness of the proposed scheme in improving the systems achievable rate.This research can provide some guidances to the design of massive MIMO based cellular networks.2)The joint optimization of power allocation,antenna activation and user association in distributed massive MIMO systems has been investigated.First of all,the asymptotic expression of achievable rate in distributed massive MIMO systems has been proposed.Then an energy efficiency oriented optimization problem has been formulated.Since the formulated problem was a mixed integer programming problem,an iterative optimization algorithm has been proposed to decompose it into a series of subproblems and transform them into convex form.The convergence and computational complexity of the proposed was analyzed.Simulation results demonstrate that the proposed algorithm can efficiently improve the system energy efficiency.What's more,the proposed algorithm can reduce the number of active antennas on the base station,thus a large amount of energy can be saved.3)The achievable rate optimization theory and technology in massive MIMO en-abled SWIPT systems have been investigated.The asymptotic expressions of the harvest-ed energy and achievable rate of the system have been derived over Rician channels.With the objective to maximize the sum achievable rate,an optimization problem is formulated under the constraints of maximum transmit power and minimum transmit rate.To obtain the optimal solution,the successive convex approximation has been introduced and the original problem is solved iteratively.The power allocation,the power split coefficients and the channel estimation time are jointly optimized in the proposed algorithm.In order to ensure the fairness among users,another optimization problem is proposed and solved through a similar method.Simulations results demonstrate the effectiveness of proposed optimization algorithms.