“Trees that are slow to grow bear the best fruit.” ― Molière
Chalmers University of Technology, Sweden
Universitat Autonoma de Barcelona, Spain
One of the enabling technologies of the fifth generation of mobile networks (5G) is the millimeter waves technology (mm-wave). By their nature, mm-waves allow packing high number of antenna elements in a relatively small area. In addition, the massively available spectrum of mm-waves would easily enable the transmission with extremely high data rates. These two reasons nominate the mm-wave systems to play a significant role in 5G.
On the other hand, location knowledge is expected to be instrumental in the design and optimization of the 5G networks. In this project, we intend to combine location estimation with mm-wave technology to contribute to the currently highly debated topic of 5G network design. Among different approaches localization is achieved, localization based on angle estimation is the most reliable as shown in the prior art. Thus, in this work, we will look into localization solutions based on the estimation of DOAs and DODs.
Over the last few decades, mobile station (MS) localization has been
extensively studied under line-of-sight (LOS) conditions. However, one
major issue that limits the performance of many available methods is
the presence of a non-line-of-sight (NLOS) link between the MS and the
base station (BS). In other words, an obstacle or more interrupt the
direct path between an MS and a BS.
One of the most popular localization methods is estimating the range between the two ends by multiplying the signal speed by the time-of-arrival (TOA). In the LOS case, the measured location is only contaminated by Gaussian measurement noise, while in the NLOS case a measurement bias is added up on the measured range and its corresponding noise. Since the presence of an obstacle between the MS and BS will force the signal from one end to be reflected on these obstacles before finding its way to the other end, the measured range will always be greater than the actual distance. Therefore, the distance bias under NLOS is always positive.
In this work, we look into methods to achieve mobile localization, under the challenge of NLOS.
Over the past decade, satellite broadcast services including, direct-to-home, have shown significant growth and are expected to continue to represent a principal sector of the overall satellite business in the future. To meet the needs of satellite broadcast market, more satellites are launched and typically stationed in the geostationary orbit (GEO). As a result of this higher satellite density and use of common frequency bands amongst these satellites, e.g., the Ku-band, the receivers are more susceptible to adjacent satellite interference. In addition, it is commercially attractive for home users to utilize satellite receivers with small-aperture antennas due to their reduced manufacturing and mounting costs. However, it is well known that a smaller dish size has a wider radiation pattern resulting in reduced directivity and higher levels of ASI at the receiver.
These two factors have created the need for designing new algorithms that can more effectively mitigate the ASI. Such algorithms are expected to enhance the throughput of satellite receivers and provide the satellite broadcasting industry with an edge over other existing alternatives, e.g., cable and fiber optics.
We look into this problem by considering multiple noise blocks, also know as, feed, as shown in the figure, below.