Error Bounds for Uplink and Downlink 3D Localization in 5G mmWave Systems

Location-aware communication systems are expected to play a pivotal part in the next generation of mobile communication networks. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Towards that, we address the uplink and downlink localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels. We also carry out a detailed analysis of the dependence of the bounds of different systems parameters. Our key findings indicate that the uplink and downlink behave differently in two distinct ways. First of all, the error bounds have different scaling factors with respect to the number of antennas in the uplink and downlink. Secondly, uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, the non-line-of-sight paths generally improve localization when a line-of-sight path exists. Finally, our numerical results show that mmWave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error.Comment: This manuscripts is updated following two rounds of reviews at IEEE Transactions on Wireless Communications. More discussion is included in different parts of the paper. Results are unchanged, and are still vali

Dynamic double directional propagation channel analysis with dual circular arrays

Dynamic double directional propagation channel analysis with dual circular arrays. (pp. 6 p). Peer reviewed versio

Multi-source parameter estimation and tracking using antenna arrays

This thesis is concerned with multi-source parameter estimation and tracking using antenna arrays in wireless communications. Various multi-source parameter estimation and tracking algorithms are presented and evaluated. Firstly, a novel multiple-input multiple-output (MIMO) communication system is proposed for multi-parameter channel estimation. A manifold extender is presented for increasing the degrees of freedom (DoF). The proposed approach utilises the extended manifold vectors together with superresolution subspace type algorithms, to achieve the estimation of delay, direction of departure (DOD) and direction of arrival (DOA) of all the paths of the desired user in the presence of multiple access interference (MAI). Secondly, the MIMO system is extended to a virtual-spatiotemporal system by incorporating the temporal domain of the system towards the objective of further increasing the degrees of freedom. In this system, a multi-parameter es- timation of delay, Doppler frequency, DOD and DOA of the desired user, and a beamformer that suppresses the MAI are presented, by utilising the proposed virtual-spatiotemporal manifold extender and the superresolution subspace type algorithms. Finally, for multi-source tracking, two tracking approaches are proposed based on an arrayed Extended Kalman Filter (arrayed-EKF) and an arrayed Unscented Kalman Filter (arrayed-UKF) using two type of antenna arrays: rigid array and flexible array. If the array is rigid, the proposed approaches employ a spatiotemporal state-space model and a manifold extender to track the source parameters, while if it is flexible the array locations are also tracked simultaneously. Throughout the thesis, computer simulation studies are presented to investigate and evaluate the performance of all the proposed algorithms.Open Acces

Characterization of Single- and Multi-antenna Wireless Channels

The wireless propagation channel significantly influences the received signal, so that it needs to be modeled effectively. Extensive measurements and analysis are required for investigating the validity of theoretical models and postulating new models based on measurements. Such measurements, analysis, and modeling are the topic of this thesis. The focus of the included contributions are Multiple-Input Multiple-Output (MIMO) propagation channels and radio channels for sensor network applications. Paper I presents results from one of the first MIMO measurements for a double-directional characterization of the outdoor-to-indoor wireless propagation channel. Such channels are of interest for both cellular and wireless LAN applications. We discuss physical aspects of building penetration, and also provide statistics of angle and delay spreads in the channel. The paper also investigates the coupling between DOD and DOA and the two spectra are found to have non-negligible dependence. We test the applicability of three analytical channel models that make different assumptions on the coupling between DODs and DOAs. Our results indicate that analytical models, that impose fewer restrictions on the DOD to DOA coupling, should be used preferrably over models such as the Kronecker model that have more restrictive assumptions. Paper II presents a cluster-based analysis of the outdoor-to-indoor MIMO measurements analyzed in Paper I. A subset of parameters of the COST 273 channel model, a generic model for MIMO propagation channels, are characterized for the outdoor-to-indoor scenario. MPC parameters are extracted at each measured location using a high-resolution algorithm and clusters of MPCs are identified with an automated clustering approach. In particular, the adopted clustering approach requires that all MPC parameters must be similar in order for the MPCs to form a cluster. A statistical analysis of the identified clusters is performed for both the intra- and inter-cluster properties. Paper III analyzes the spatial fading distribution for a range of canonical sensor deployment scenarios. The presented results are relevant to communicating within, and between, clusters of nodes. Contrary to the widely accepted assumption in published literature that the channel is AWGN at a small-enough distance, our measurements indicate that values of the Rice factor do not, in general, increase monotonically as the Tx-Rx distance is reduced. A probability mixture model is presented, with distance dependent parameters, to account for the distance dependent variations of the Rice factor. A simulation model that includes small- and large-scale fading effects is presented. According to the modeling approach, a sensor node placed anywhere within the spatial extent of a small-scale region will experience the channel statistics applicable to that region. Paper IV presents results characterizing a radio channel for outdoor short-range sensor networks. A number of antennas are placed on the ground in an open area and time-variation of the channel is induced by a person moving in the vicinity of the nodes. The channel statistics of both the LOS path and the overall narrowband signal are non-stationary. We investigate the stationarity interval length to be used for small-scale analysis. Our analysis of the various measured links shows that the Rx signal strength is significantly influenced by a moving person only when the person blocks the LOS path. We present a generic approach for modeling the LOS blockage, and also model the time-variant Doppler spectrum of the channel's scattered components

Downlink Achievable Rate Analysis for FDD Massive MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems with large-scale transmit antenna arrays, often called massive MIMO, are a very promising direction for 5G due to their ability to increase capacity and enhance both spectrum and energy efficiency. To get the benefit of massive MIMO systems, accurate downlink channel state information at the transmitter (CSIT) is essential for downlink beamforming and resource allocation. Conventional approaches to obtain CSIT for FDD massive MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for massive MIMO systems because of the large dimensionality of the channel matrix. In this dissertation, we improve the performance of FDD massive MIMO networks in terms of downlink training overhead reduction, by designing an efficient downlink beamforming method and developing a new algorithm to estimate the channel state information based on compressive sensing techniques. First, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink direction of arrivals (DoAs) and downlink direction of departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming. Second, By exploiting the sparsity structure of downlink channel matrix, we develop an algorithm that selects the best features from the measurement matrix to obtain efficient CSIT acquisition that can reduce the downlink training overhead compared with conventional LS/MMSE estimators. In both cases, we compare the performance of our proposed beamforming method with traditional methods in terms of downlink achievable rate and simulation results show that our proposed method outperform the traditional beamforming methods