Transmission Design And Performance Analysis For Massive MIMO Wireless Communication Systems

To satisfy the requirement of 5th generation mobile communication systems(5G)on peakrate,user-experience-rate,mobility,end-to-end latency,connection density,traffic density and energy efficiency,the industry is embarking researching and standardization of 5G which tends to be commercialized beyond 2020.Some emerging technologies,e.g.,massive multiple-inputmultiple-output(MIMO),full spectrum access,ultra-dense networks,new multiple access and new network architectures,have received a lot of attention.Massive MIMO can largely improve the spectrum efficiency,multiuser multiplexing capability and power efficiency via exploiting the spatial degrees of freedom sufficiently,and has been considered as the key 5G physicallayer technology.Focusing on the effect of practical non-ideal system and channel factors on the massive MIMO gain,the significant increase of analog/digital processing complexity and channel estimation overhead due to the system dimension increment,the efficient beamforming design of both data and public channel under the constraint of practical channel state information(CSI)and system architectures,this dissertation studies transmission design and performance analysis for massive MIMO wireless communication systems.Main work and contributions are briefly summarized as follows.1.For multicell multiuser massive MIMO downlink systems with linear precodings,we provide a comprehensive scaling law of system rate performance with respect to important system parameters where typical practical non-ideal factors,e.g.,imperfect CSI,pilot contamination,and channel spatial correlation are all considered.And we also discuss the applicability of the derived scaling law in systems with finite base station(BS)antennas.First,a sum-rate lower bound is derived by exploiting the asymptotically deterministic property of the received signal power,while keeping the random nature of other components in the signal-to-interferenceplus-noise-ratio(SINR)intact.Via a general scaling model on important network parameters,including the number of users,the channel training energy and the data transmission power,with respect to the number of BS antennas,the asymptotic scaling law of the effective SINR is obtained,which reveals quantitatively the tradeoff of the network parameters.Pilot contamination and pilot contamination elimination are considered in the analytical framework.In addition,the applicability of the derived asymptotic scaling law in practical systems with large but finite antenna numbers are discussed and some applicable parameter ranges are given.Finally,sufficient conditions on the parameter scalings for the SINR to be asymptotically deterministic in the sense of mean square convergence are provided,which covers existing results on such analysis as special cases and shows the effect of pilot contamination elimination explicitly.2.For the complexity problem of ZF precoding in multiuser massive MIMO downlink systems,we propose a first-order Neumann series(NS)based low complexity approximate ZF precoding design along with its sum-rate analysis and comparison with existing schemes.Among typical massive MIMO downlink linear precodings,ZF precoding draws much attention due to its good performance in interference cancellation.However,the high computation cost of the involved matrix inversion may hinder its application in practical massive MIMO systems.In this dissertation,we adopt the first-order NS for a low-complexity approximation.By introducing a relaxation parameter jointly with the channel non-orthogonality between one selected user and others into the precondition matrix,we propose the identity-plus-column NS(ICNS)method.By further choosing the user with least channel orthogonality with others,the ordered ICNS method is also proposed.Moreover,via large-scale asymptotic analysis,the sum-rate approximations of the proposed ICNS method and the most competitive existing identity matrix based NS(INS)method in the sense of performance-complexity tradeoff are derived in closedform.Based on these results,the performance loss of ICNS due to inversion approximation compared with ideal ZF and its performance gain over INS are explicitly analyzed for three typical massive MIMO scenarios.Finally,simulations verify our analytical results and also show that the proposed two designs achieve better performance-complexity tradeoff than ideal ZF and existing low-complexity ZF precodings for practical large antenna number,correlated channels and not-so-small loading factor.3.For the difficulty of obtaining instantaneous CSI at the BS in multiuser massive MIMO downlink systems,based on sum-rate analysis and the metric of signal-to-leakage-and-noiseratio(SLNR),we propose a joint statistical beamforming and user scheduling design.The asymptotic sum-rate behavior of the proposed scheme and the effect of important system parameters on it are studied as well.The acquisition of instantaneous CSI for BS in massive MIMO downlink costs huge training-overhead and feedback-overhead,thus it is highly potential to use the channel statistics varying in relatively long time-scale for massive MIMO transmission design.In this dissertation,we first derive an explicit analytical sum-rate expression for generic channel covariance-based beamforming scheme.Then,a low-complexity joint statistical beamforming and user scheduling algorithm via greedy search is proposed,where the beamforming is to maximize average SLNR for closed-form design and tractable analysis,while the user scheduling is based on the derived sum-rate expression.Further,with the help of large-scale asymptotic simplifications and the introduction of the interference user number(IUN)parameter,a simple analytical sum-rate expression of the joint algorithm is derived for channels with flat power beam spectrum.The expression explicitly exhibits the sum-rate behavior with respect to different network parameters and captures the effect of sum-rate-based user scheduling.Finally,simulation results are provided to verify our analytical results and to show the advantage of the proposed joint design compared with existing schemes.4.For hybrid analog/digital massive antenna single-user(SU)and multiuser(MU)downlink systems,we propose two joint beam-based training and transmission designs,respectively.The analytical average training length and outage probability are derived for the proposed scheme for SU systems as well.Hybrid analog/digital beamforming is a practical massive MIMO implementation structure.For SU systems,we propose an interleaved training design to concatenate the feedback and training procedures,thus making the training length adaptive to the channel realization.Exact analytical expressions and simple explicit expressions for special cases are derived for the average training length and the outage probability of the proposed interleaved training.For MU systems,we propose a joint design for the beam-based interleaved training,beam assignment,and MU data transmissions.Two solutions for the beam assignment are provided with different complexity-performance tradeoff.Analytical results and simulations show that for both SU and MU hybrid massive antenna systems,the proposed joint training and transmission designs achieve the same outage performance as the traditional full-training scheme but with significant saving in the training overhead.5.For massive MIMO public channel with any sector size,we propose a power efficient beamforming design to minimize the transmit power while guaranteeing the quality of service for randomly deployed users in the sector.We consider the worst-case CSI assumption,i.e,no CSI is assumed at the BS.First the ideal beampattern is derived via Parseval Identity.Then,by drawing lessons from the finite impulse response(FIR)filter design,we formulate the beamforming design as an optimization problem which aims to minimize the maximum gap with the idea beampattern under the constraint of certain inter-sector interference level.The problem is transformable to a multiconvex one and an iterative optimization algorithm is used to obtain the full-digital beamformer.In addition,with the help of same beampattern theorem,the power amplifier efficiency of the beamformer is improved with unchanged beampattern.Finally,the practical hybrid implementation is obtained that achieves the full-digital beamformer solution.Simulations verify the advantages of the proposed scheme over existing ones.