Multi-dimensional Channel Parameter Estimation For Mmwave Cylindrical Arrays

Millimeter-wave(mmWave)large-scale antenna arrays,widely used in the fifth-generation(5G)wireless communications,have the potential to estimate channel parameters with unprecedented accuracy,due to their high temporal resolution and excellent directivity.However,most existing techniques have very high complexities in hardware and software,and they cannot effectively exploit the properties of mmWave large-array systems for channel estimation.As a result,their application in 5G mmWave large array systems is limited in practice.This thesis proposes efficient channel parameter estimation methods for 5G mmWave communications with large-scale uniform cylindrical arrays(UCyAs).Compared with linear and rectangular arrays,UCyAs are more applicable to mmWave communications,since they have stronger immunity to beam mis-alignment and are more robust to the angle variations caused by array vibrations.The key contributions of this thesis are on the following four aspects:(1)We first present a low-complexity channel estimation method for mmWave indoor scenarios.By capitalizing on the sparsity of mmWave chan-nel,a channel compression method is presented,which can effectively filter the multiple reflection and diffuse scattering components.As a result,the dimension of the element space of the received signals can be significantly reduced while the useful signals are maintained for localization estimation.We also design a beamspace-based hybrid received signal strength(RSS)-angle of arrival(AoA)algorithm.The algorithm estimates the channel parameters in the low-dimensional beamspace,so that the computational complexity can be further reduced in the process of the parameter estimation.(2)Next,we extend the channel parameter estimation to hybrid UCyAs-deployed mmWave outdoor scenarios,such as Urban Micro(UMi)and Rural Macro(RMa),and propose signal preprocessing methods for wideband com-munication systems.By employing linear transformation to design the hybrid beamformer,the recurrence relationship of the received signals can be preserved with a small number of radio frequency(RF)chains.As a result,the hardware cost is reduced.A generalized linear interpolation method is also developed,which combines the signals across the whole band.By this means,the subspace-based algorithms can exploit the high time resolution of wideband mmWave to estimate the channel parameters across the whole band,significantly improving the estimation accuracy.(3)We arrange the received signals in a tensor form and design a new tensor-based subspace algorithm to suppress the receiver noises in all dimen-sions(time,frequency,and space).We construct a truncated higher-order sin-gular value decomposition(HOS VD)model of the received signals and exploit the important shift-invariance relations in all dimensions to jointly estimate the delay and the azimuth and elevation angles of each received signal.Simulation results show that the algorithm can achieve substantially higher estimation ac-curacy than existing matrix-based techniques,with a comparable computational complexity.(4)Finally,to reduce cost and power consumption of massive Internet of Things(mIoT)networks while maintaining a high network access capability,we develop a novel nested hybrid UCy A and present the corresponding parameter estimation algorithm based on the second-order channel statistics.We employ the theory of phase-space transformation to transform the nonlinear phase of the UCyA steering vectors to be linear to the element locations,so that the inherently horizontal symmetric structure of the UCyA can be preserved to maintain a good parameter estimation accuracy.Simulation results show that by exploiting the sparse array technique to design the RF chain connection network,the base station is able to accurately estimate the angles of a large number of devices with much fewer RF chains than antennas.Overall,this thesis presents several applicable UCyA design schemes and efficient channel parameter estimation algorithms for different mm Wave com-munication scenarios,namely,indoor,UMi,RMa,and mIoT scenarios.The presented new UCyAs can significantly reduce the hardware cost of the sys-tem with a marginal accuracy loss,and the proposed algorithms are capable of accurately estimating the channel parameters with low computational com-plexities.As a result,by employing the presented UCyAs and implementing the proposed novel algorithms cohesively,we can meet the different communi-cation and deployment requirements of a variety of mmWave communication scenarios.