Doctoral Thesis: Massive MIMO in Real Propagation Environments

Mobile communications are now evolving towards the fifth generation (5G). In the near future, we expect an explosive increase in the number of connected devices, such as phones, tablets, sensors, connected vehicles and so on. Much higher data rates than in today's 4G systems are required. In the 5G visions, better coverage in remote regions is also included, aiming for bringing the current "4 billion unconnected" population into the online world. There is also a great interest in "green communications", for less energy consumption in the ICT (information and communication technology) industry. Massive MIMO is a potential technology to fulfill the requirements and visions. By equipping a base station with a large number, say tens to hundreds, of antennas, many terminals can be served in the same time-frequency resource without severe inter-user interference. Through "aggressive" spatial multiplexing, higher data rates can be achieved without increasing the required spectrum. Processing efforts can be made at the base station side, allowing terminals to have simple and cheap hardware. By exploiting the many spatial degrees of freedom, linear precoding/detection schemes can be used to achieve near-optimal performance. The large number of antennas also brings the advantage of large array gain, resulting in an increase in received signal strength. Better coverage is thus achieved. On the other hand, transmit power from base stations and terminals can be scaled down to pursue energy efficiency. In the last five years, a lot of theoretical studies have been done, showing the extraordinary advantages of massive MIMO. However, the investigations are mainly based on theoretical channels with independent and identically distributed (i.i.d.) Gaussian coefficients, and sometimes assuming unlimited number of antennas. When bringing this new technology from theory to practice, it is important to understand massive MIMO behavior in real propagation channels using practical antenna arrays. Not much has been known about real massive MIMO channels, and whether the claims about massive MIMO still hold there, until the studies in this thesis were done. The thesis study connects the "ideal" world of theory to the "non-ideal" reality. Channel measurements for massive MIMO in the 2.6 GHz band were performed, in different propagation environments and using different types of antenna arrays. Based on obtained real-life channel data, the studies include • channel characterization to identify important massive MIMO properties, • evaluation of propagation conditions in real channels and corresponding massive MIMO performance, • channel modeling for massive MIMO to capture the identified channel properties, and • reduction of massive MIMO hardware complexity through antenna selection. The investigations in the thesis conclude that massive MIMO works efficiently in real propagation environments. The theoretical advantages, as observed in i.i.d. Rayleigh channels, can also be harvested in real channels. Important propagation effects are identified for massive MIMO scenarios, including channel variations over large arrays, multipath-component (MPC) lifetime, and 3D propagation. These propagation properties are modeled and included into the COST 2100 MIMO channel model as an extension for massive MIMO. The study on antenna selection shows that characteristics in real channels allow for significant reductions of massive MIMO complexity without significant performance loss. As one of the world's first research work on massive MIMO behavior in real propagation channels, the studies in this thesis promote massive MIMO as a practical technology for future communication systems

Millimeter wave and UWB propagation for high throughput indoor communications

Millimeter-wave systems at 60 GHz and ultra-wideband (UWB) systems in the microwave range of 3-10 GHz have been received with great interest for their high data rate wireless communications. In design, test and optimization of future wireless systems, channel models featuring the relevant characteristics of radiowave propagation are required. Furthermore, detailed understanding of the propagation channel and its interaction with system, creates insights into possible solutions. In this work, both theoretical (ray-tracing) and statistical models of the 60 GHz and UWB channels are studied. Propagation characteristics of the 60 GHz and UWB indoor channels are also compared for providing useful information on design of radio systems. More specifically, based on real-time channel sounder measurements performed in the 60 GHz band, propagation mechanisms including person blocking effect are concluded. Ray-based models in LOS and NLOS indoor corridors are proposed. Multipath power distributions in the 60 GHz band are studied first time. Moreover, propagation interdependencies of path loss, shadowing, number of paths, Rice K-factor and cross polarization discrimination (XPD) with channel delay spread are established. In the UWB propagation channel, frequency- and bandwidth- dependencies are investigated. Multipath and clustering propagation characteristics are analyzed. A new cluster model is proposed and compared with the classical Saleh-Valenzuela model for gaining more understanding of channel general properties. Finally, the performance and capacities of the 60 GHz UWB and MIMO (multiple-in and multiple-out) systems are analyzed for providing reliable parameters for system design and useful information for standardization groups

Millimeter wave wearable communication networks : analytic modeling and MIMO support

Future high-end wearable electronic devices including virtual reality goggles and augmented reality glasses require rates of the order of gigabits-per-second and potentially very low latency. Supporting high data rate wireless connectivity for applications such as uncompressed video streaming among wearable devices in a densely crowded environment is challenging. This is primarily due to bandwidth scarcity when many users operate multiple devices simultaneously. The millimeter wave (mmWave) band has the potential to address this bottleneck, thanks to more spectrum and less interference because of signal blockage at these frequencies. This dissertation addresses key questions that need to be answered before realizing mmWave-based wearables in practice: (i) what are the expected achievable rates in a crowded user environment, with mmWave devices using a given hardware configuration? (ii) how is the wireless connectivity affected in an indoor operation, which is prone to surface reflections? (iii) can multi-stream data transmission, involving large bandwidth communication under hardware constraints be realized? To answer these, tools from stochastic geometry and compressive sensing, and architectures involving hybrid analog/digital multiple-input multiple-output (MIMO) are leveraged. The main contributions of this dissertation are 1) analytical modeling to compute average achievable rates in mmWave wearable networks consisting of finite number of user devices and human blockages, 2) characterizing the impact of reflections and non-isotropic performance of mmWave wearable networks in crowded indoor environments, 3) channel estimation to support MIMO for wideband mmWave wearable devices using hybrid architecture, and 4) designing optimal, but easy-to-implement, precoding/combining strategies in frequency-selective mmWave systems. Both analysis and numerical simulations show how the proposed evaluation methodology and solutions serve to enable mmWave based communication among next generation wearable electronic devices.Electrical and Computer Engineerin

Measurement-Based Modeling of Wireless Propagation Channels - MIMO and UWB

Future wireless systems envision higher speeds and more reliable services but at the same time face challenges in terms of bandwidth being a limited resource. Two promising techniques that can provide an increased throughput without requiring additional bandwidth allocation are multiple-input multiple-output (MIMO) systems and ultra-wideband (UWB) systems. However, the performance of such systems is highly dependent on the properties of the wireless propagation channel, and an understanding of the channel is therefore crucial in the design of future wireless systems. Examples of such systems covered by this thesis are wireless personal area networks (papers I and II), vehicle-to-vehicle communications (paper III), board-to-board communications inside computers (paper IV) and sensor networks for industrial applications (paper V). Typically, channel models are used to evaluate the performance of different transmission and reception schemes. Channel modeling is the focus of this thesis, which contains a collection of papers that analyze and model the behavior of MIMO and UWB propagation channels. Paper I investigates the fading characteristics of wireless personal area networks (PANs), networks that typically involve human influence close to the antenna terminals. Based on extensive channel measurements using irregular antenna arrays, typical properties of PAN propagation channels are discussed and a model for the complete fading of a single link is presented. Paper II extends the model from paper I to a complete MIMO channel model. The paper combines the classical LOS model for MIMO with results from paper I by prescribing different fading statistics and mean power at the different antenna elements. The model is verified against measurement data and the paper also provides a parameterization for an example of a PAN scenario. Paper III presents a geometry-based stochastic MIMO model for vehicle-to-vehicle communications. The most important propagation effects are discussed based on the results from extensive channel measurements, and the modeling approach is motivated by the non-stationary behavior of such channels. The model distinguishes between diffuse contributions and those stemming from interaction with significant objects in the propagation channel, and the observed fading characteristics of the latter are stochastically accounted for in the model. Paper IV gives a characterization of UWB propagation channels inside desktop computer chassis. By studying measurement results from two different computers, it is concluded that the propagation channel only shows minor differences for different computers and positions within the chassis. It is also found out that the interference power produced by the computer is limited to certain subbands, suggesting that multiband UWB systems are more suitable for this type of applications. Paper V describes a UWB channel model based on the first UWB measurements in an industrial environment. Analyzing results from two different factory halls, it is concluded that energy arrives at the receiver in clusters, which motivates the use of a classical multi-cluster model to describe the channel impulse response. Parts of the results from this paper were also used as input to the channel model in the IEEE 802.15.4a UWB standardization work. In summary, the work within this thesis leads to an increased understanding of the behavior of wireless propagation channels for MIMO and UWB systems. By providing three detailed simulation models, two for MIMO and one for UWB, it can thus contribute to a more efficient design of the wireless communications systems of tomorrow

Massive MIMO Channel Modeling

Massive MIMO has attracted many researchers’ attention as it is a promising technology for future 5G communication systems. To characterize the propagation channels of the massive MIMO and to evaluate system performance, it is important to develop an accurate channel model for it. In this thesis, two correlative models, i.e., the Kronecker model and the Weichselberger model, and a cluster-based model, i.e., the Random Cluster Model (RCM), have been validated based on real-life data from four measurement campaigns. These measurements were performed at Lund University using two types of base station (BS) antenna arrays, a practical and compact uniform cylindrical array (UCA) and a physically-large virtual uniform linear array (ULA), both at 2.6 GHz. For correlative models, performance metrics such as channel capacity, sum-rate and singular value spread are examined to validate the model. The random cluster model, which is constructed and evaluated on a cluster level, has been parameterized and validated using the measured channel data. The correlative models are relatively simple and are suitable for analytical study. Validation results show that correlative models can reflect massive MIMO channel capacity and singular value spread, when the compact UCA is used at the base station and when users are closely located. However, for the physically-large ULA, correlative models tend to underestimate channel capacity. The RCM is relatively complex and is usually used for simulation purpose. Validation results show that the RCM is a promising model for massive MIMO channels, however, improvements are needed

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency