Angle Estimation And Beamforming In Massive Multiple-input Multiple-output Systems

As a key technology of fifth-generation(5G)systems,massive multi-input multi-output(Massive MIMO),where the base station(BS)is equipped with large-scale antenna arrays,can greatly enhance the spectrum efficiency of the systems.On the one hand,the directionof-arrival(DOA)estimation can be used for user localization and can provide useful information for channel estimation and precoding in massive MIMO systems;on the other hand,the system performance is limited by the effects of inter-cell interference caused by pilot contamination and the introduction of beamforming is a feasible method for reducing interference.The thesis focuses on the design and analysis of the new algorithm for DOA estimation and beamforming techniques.The main novelties and contributions are listed as follows:1.Based on the unitary estimation of signal parameters via rotational invariance techniques(Unitary ESPRIT),a novel method of joint two-dimensional(2D)DOA and channel impulse responses estimation with signal detection for URA is presented in massive MIMO system.The joint estimation scheme first estimates the combined channel impulse responses for the links between the transmitters and antenna elements using training sequences.After that,DOA's of waves are estimated based on unitary ESPRIT algorithm utilizing imperfect channel impulse responses estimation instead of accurate channel impulse responses and then the enhanced directional channel impulse responses estimation can be obtained.The proposed estimator enjoys closed-form expressions and hence it bypasses the searching and the paring process.In addition,a low complexity approach of signal detection is presented based on the orthogonality of steering vectors,which reduces the the dimension of inverse matrix in massive MIMO systems.The different cases of the proposed method have been analyzed by changing the number of the antennas.Experimental results demonstrate the validity of the proposed method.2.Based on the ESPRIT algorithm,a joint estimation of direction-of-departure(DOD)and 2D DOA is investigated.To further reduce computational complexity,a unitary ESPRIT-based technique in beamspace is proposed for joint angle estimation.The joint estimation of angles and channel gains is also proposed based on pilots.In the massive MIMO system,the transmitter is equipped with a uniform linear array(ULA)and the receiver is equipped with a uniform rectangular array(URA).An ESPRIT-based algorithm is studied to joint estimate DOD and 2D DOA.Compared with the conventional algorithms of joint estimation of DOD and one-dimensional(1D)DOA,the ESPRIT-based algorithm solves the problem of joint estimation of DOD and 2D DOA.The proposed algorithm requires pair the DOD and 2D DOA,which results in additional computational load.To further reduce the computational complexity,a unitary ESPRIT based approach in beamspace is proposed,which transforms the rotational invariance from element space to smaller beamspace and achieves the automatic pairing of angles.The proposed algorithm reduces the complexity with satisfactory performance.The joint estimation of angles and channel gains is also proposed utilizing pilots,which solves the problem of the joint estimation of three parameters,including DOD,2D DOA and channel gains.3.A simplified method inspired by the 2D unitary ESPRIT-like algorithm is proposed to estimate both the central angles and the angular spreads for coherently distributed(CD)sources in massive MIMO systems employing URA.We first approximate the 2D generalized steering vector expressed as a Schur-Hadamard product by a pair of one-dimensional generalized steering vectors.Then,we obtain two approximate rotational invariance relationships with respect to the central angles of the CD sources using a linear approximation of the individual generalized steering vectors of the azimuth and elevation subarrays.With the aid of this approximate decomposition,a new unitary ESPRITinspired algorithm is conceived to automatically pair the 2D central angle estimations,and a novel method capable of bypassing the high-complexity search process is proposed for angular spread estimation.Furthermore,the closed-form approximate Cramer-Rao lower bounds are derived for the estimators of both the central angles and the angular spreads.The complexity of the proposed estimator is also analyzed.Additionally,the orthogonality of the generalized steering vectors is proved,which enables us to propose a low-complexity method to reconstruct the signal matrix by replacing the inversion operator with the conjugate transpose operator.The simulation results demonstrate the efficiency of our proposed approach.4.The beamforming and power allocation schemes for massive MIMO systems are designed.Considering the circuit power and transmission power consumption,an energy-efficient beamforming and power allocation scheme is proposed to maximize the energy efficiency for homogeneous users and heterogeneous users,which needs to meet the QoS and total transmission power constraints.At the same time,we consider the vertical beamforming in the downlink of a three-dimensional(3D)massive MIMO system.Two beams are partitioned through dynamic vertical beamforming with two specific downtilts.Taking these users' specific downtilts into consideration,the objective of this scheme is to maximize cell spectral efficiency by adjusting the powers and downtilts of the two vertical beams,subject to BS power consumption and downtilts constraints.To solve this problem,a particle swarm optimization(PSO)based vertical beamforming optimization algorithm is proposed.