Sensitivity of the MIMO Channel Characterization to the Modeling of the Environment

International audienceAn important factor in electromagnetic wave propagation simulation, performed by a 3D ray-tracing method is the modeling of the environment. Results being sensitive to descriptive accuracy, this paper presents a study on the effect of indoor environment modeling precision on multiple input multiple output (MIMO) channel characterization. In order to give some diversity to the results, the investigation takes into account two unfurnished indoor environments. The first environment investigated is the entrance hall of a building at the University of Poitiers, while the second is a more confined environment and is represented by the first floor of the authors' laboratory. For these two indoor environments, four levels of description are proposed in order to establish the geometrical and electrical modeling impact on MIMO channel characterization. Results are obtained by analyzing the capacity, variation in correlation, multipath richness and eigenvalues in relation to the polarization, the presence of line-of-sight (LOS) or non-LOS (NLOS) configurations. The effects of the spacing between antennas and the number of transmitter and receiver antennas are also investigated

Analysis of Channel Measurements Using a Very Large Antenna Array

Accurate wireless channel models are crucial to simulate the effect of radio wave propagation in a channel on wireless communication systems. By calculating physical processing effects that signal undergoes while traveling from transmitter to the receiver, channel models help to analyze performance of wireless systems. State of the art channel model such as WINNER and COST 2100 are able to model the characteristics of conventional MIMO (Multiple-Input Multiple-Output) systems (where moderate number of antennas is used at the two sides of the link) with sufficient accuracy. However, model extensions are needed for the current models in order to be able to capture new propagation characteristics result from having massive number of antenna elements at one or both ends of the communication link. In this thesis work, a measurement campaign is performed using very large antenna array (about 7.5m long) in order to study key propagation characteristics for massive MIMO. The channel measurements are performed using two frequency bands (2.6 GHz and 5.1 GHz), vertical and horizontal antenna polarizations, directional and omni-directional antennas. Effect of aforementioned setup parameters on cluster delay and angle spreads, power slope and shadowing, number of clusters and their observation lengths are studied in this work. Also correlation among estimated cluster parameters is presented. It was observed, that antenna polarization does not have significant effect on estimated cluster parameters. On the other hand, some estimated parameters like delay and angle spread, shadowing achieve higher values using 2.6 GHz band. Impact of antenna directivity was not very significant. Results of this thesis work are important while implementing extension for cluster-based COST 2100 channel model for massive MIMO case

Spatial Multiplexing of QPSK Signals with a Single Radio: Antenna Design and Over-the-Air Experiments

The paper describes the implementation and performance analysis of the first fully-operational beam-space MIMO antenna for the spatial multiplexing of two QPSK streams. The antenna is composed of a planar three-port radiator with two varactor diodes terminating the passive ports. Pattern reconfiguration is used to encode the MIMO information onto orthogonal virtual basis patterns in the far-field. A measurement campaign was conducted to compare the performance of the beam-space MIMO system with a conventional 2-by-?2 MIMO system under realistic propagation conditions. Propagation measurements were conducted for both systems and the mutual information and symbol error rates were estimated from Monte-Carlo simulations over the measured channel matrices. The results show the beam-space MIMO system and the conventional MIMO system exhibit similar finite-constellation capacity and error performance in NLOS scenarios when there is sufficient scattering in the channel. In comparison, in LOS channels, the capacity performance is observed to depend on the relative polarization of the receiving antennas.Comment: 31 pages, 23 figure

Performance analysis of spatially distributed MIMO systems

With the growing popularity of ad-hoc sensor networks, spatially distributed multiple-input multiple-output (MIMO) systems have drawn a lot of attention. This work considers a spatially distributed MIMO system with randomly distributed transmit and receive antennas over spatial regions. The authors use the modal decomposition of wave propagation to analyse the performance limits of such system, since the sampling of the spatial regions populated with antennas is a form of mode excitation. Specifically, they decompose signals into orthogonal spatial modes and apply concepts of MIMO communications to quantify the instantaneous capacity and the outage probability. The authors’ analysis shows that analogous to conventional point-to-point MIMO system, the instantaneous capacity of spatially distributed MIMO system over Rayleigh fading channel is equivalent to a Gaussian random variable. Afterwards, they derive an accurate closed-form expression for the outage probability of proposed system utilising the definition of instantaneous capacity. Besides, in rich scattering environment, the spatially distributed MIMO system provides best performance when the spatial regions are of same size, and each region is equipped with equal number of antennas. Furthermore, to facilitate the total transmit power allocation among the channels, they propose an algorithm which indicates a significant performance improvement over conventional equal transmit power allocation scheme, even at low signal-to-noise ratio

Urban Navigation with LTE using a Large Antenna Array and Machine Learning

Channel fingerprinting entails associating a point in space with measured properties of a received wireless signal. If the propagation environment for that point in space remains reasonably static with time, then a receiver with no knowledge of its own position experiencing a similar channel in the future might reasonably infer proximity to the original surveyed point. In this article, measurements of downlink LTE Common Reference Symbols from one sector of an eNodeB are used to generate channel fingerprints for a passenger vehicle driving through a dense urban environment without line-of-sight to the transmitter. Channel estimates in the global azimuthal-delay domain are used to create a navigation solution with meter-level accuracy around a city block