1,595 research outputs found
Fast Cell Discovery in mm-wave 5G Networks with Context Information
The exploitation of mm-wave bands is one of the key-enabler for 5G mobile
radio networks. However, the introduction of mm-wave technologies in cellular
networks is not straightforward due to harsh propagation conditions that limit
the mm-wave access availability. Mm-wave technologies require high-gain antenna
systems to compensate for high path loss and limited power. As a consequence,
directional transmissions must be used for cell discovery and synchronization
processes: this can lead to a non-negligible access delay caused by the
exploration of the cell area with multiple transmissions along different
directions.
The integration of mm-wave technologies and conventional wireless access
networks with the objective of speeding up the cell search process requires new
5G network architectural solutions. Such architectures introduce a functional
split between C-plane and U-plane, thereby guaranteeing the availability of a
reliable signaling channel through conventional wireless technologies that
provides the opportunity to collect useful context information from the network
edge.
In this article, we leverage the context information related to user
positions to improve the directional cell discovery process. We investigate
fundamental trade-offs of this process and the effects of the context
information accuracy on the overall system performance. We also cope with
obstacle obstructions in the cell area and propose an approach based on a
geo-located context database where information gathered over time is stored to
guide future searches. Analytic models and numerical results are provided to
validate proposed strategies.Comment: 14 pages, submitted to IEEE Transaction on Mobile Computin
A Deep Learning Approach to Location- and Orientation-aided 3D Beam Selection for mmWave Communications
Position-aided beam selection methods have been shown to be an effective
approach to achieve high beamforming gain while limiting the overhead and
latency of initial access in millimeter wave (mmWave) communications. Most
research in the area, however, has focused on vehicular applications, where the
orientation of the user terminal (UT) is mostly fixed at each position of the
environment. This paper proposes a location- and orientation-based beam
selection method to enable context information (CI)-based beam alignment in
applications where the UT can take arbitrary orientation at each location. We
propose three different network structures, with different amounts of trainable
parameters that can be used with different training dataset sizes. A
professional 3-dimensional ray tracing tool is used to generate datasets for an
IEEE standard indoor scenario. Numerical results show the proposed networks
outperform a CI-aided benchmark such as the generalized inverse fingerprinting
(GIFP) method as well as hierarchical beam search as a non-CI-based approach.
Moreover, compared to the GIFP method, the proposed deep learning-based beam
selection shows higher robustness to different line-of-sight blockage
probability in the training and test datasets and lower sensitivity to
inaccuracies in the position and orientation information.Comment: 30 pages, 12 figure. This article was submitted to IEEE Transactions
on Wireless Communications on Oct 11 202
Taming and Leveraging Directionality and Blockage in Millimeter Wave Communications
To cope with the challenge for high-rate data transmission, Millimeter Wave(mmWave) is one potential solution. The short wavelength unlatched the era of directional mobile communication. The semi-optical communication requires revolutionary thinking. To assist the research and evaluate various algorithms, we build a motion-sensitive mmWave testbed with two degrees of freedom for environmental sensing and general wireless communication.The first part of this thesis contains two approaches to maintain the connection in mmWave mobile communication. The first one seeks to solve the beam tracking problem using motion sensor within the mobile device. A tracking algorithm is given and integrated into the tracking protocol. Detailed experiments and numerical simulations compared several compensation schemes with optical benchmark and demonstrated the efficiency of overhead reduction. The second strategy attempts to mitigate intermittent connections during roaming is multi-connectivity. Taking advantage of properties of rateless erasure code, a fountain code type multi-connectivity mechanism is proposed to increase the link reliability with simplified backhaul mechanism. The simulation demonstrates the efficiency and robustness of our system design with a multi-link channel record.The second topic in this thesis explores various techniques in blockage mitigation. A fast hear-beat like channel with heavy blockage loss is identified in the mmWave Unmanned Aerial Vehicle (UAV) communication experiment due to the propeller blockage. These blockage patterns are detected through Holm\u27s procedure as a problem of multi-time series edge detection. To reduce the blockage effect, an adaptive modulation and coding scheme is designed. The simulation results show that it could greatly improve the throughput given appropriately predicted patterns. The last but not the least, the blockage of directional communication also appears as a blessing because the geometrical information and blockage event of ancillary signal paths can be utilized to predict the blockage timing for the current transmission path. A geometrical model and prediction algorithm are derived to resolve the blockage time and initiate active handovers. An experiment provides solid proof of multi-paths properties and the numeral simulation demonstrates the efficiency of the proposed algorithm
Predictive Resource Allocation in mmWave Systems with Rotation Detection
Millimeter wave (MmWave) has been regarded as a promising technology to
support high-capacity communications in 5G era. However, its high-layer
performance such as latency and packet drop rate in the long term highly
depends on resource allocation because mmWave channel suffers significant
fluctuation with rotating users due to mmWave sparse channel property and
limited field-of-view (FoV) of antenna arrays. In this paper, downlink
transmission scheduling considering rotation of user equipments (UE) and
limited antenna FoV in an mmWave system is optimized via a novel approximate
Markov decision process (MDP) method. Specifically, we consider the joint
downlink UE selection and power allocation in a number of frames where future
orientations of rotating UEs can be predicted via embedded motion sensors. The
problem is formulated as a finite-horizon MDP with non-stationary state
transition probabilities. A novel low-complexity solution framework is proposed
via one iteration step over a base policy whose average future cost can be
predicted with analytical expressions. It is demonstrated by simulations that
compared with existing benchmarks, the proposed scheme can schedule the
downlink transmission and suppress the packet drop rate efficiently in
non-stationary mmWave links.Comment: 7 pages, 5 figures. Paper accepted for publication in IEEE
International Conference on Communications, 202
Fastening the Initial Access in 5G NR Sidelink for 6G V2X Networks
The ever-increasing demand for intelligent, automated, and connected mobility
solutions pushes for the development of an innovative sixth Generation (6G) of
cellular networks. A radical transformation on the physical layer of vehicular
communications is planned, with a paradigm shift towards beam-based millimeter
Waves or sub-Terahertz communications, which require precise beam pointing for
guaranteeing the communication link, especially in high mobility. A key design
aspect is a fast and proactive Initial Access (IA) algorithm to select the
optimal beam to be used. In this work, we investigate alternative IA techniques
to fasten the current fifth-generation (5G) standard, targeting an efficient 6G
design. First, we discuss cooperative position-based schemes that rely on the
position information. Then, motivated by the intuition of a non-uniform
distribution of the communication directions due to road topology constraints,
we design two Probabilistic Codebook (PCB) techniques of prioritized beams. In
the first one, the PCBs are built leveraging past collected traffic
information, while in the second one, we use the Hough Transform over the
digital map to extract dominant road directions. We also show that the
information coming from the angular probability distribution allows designing
non-uniform codebook quantization, reducing the degradation of the performances
compared to uniform one. Numerical simulation on realistic scenarios shows that
PCBs-based beam selection outperforms the 5G standard in terms of the number of
IA trials, with a performance comparable to position-based methods, without
requiring the signaling of sensitive information
Towards the Next Generation of Location-Aware Communications
This thesis is motivated by the expected implementation of the
next generation mobile networks (5G) from 2020, which is being
designed with a radical paradigm shift towards millimeter-wave
technology (mmWave). Operating in 30--300 GHz frequency band
(1--10 mm wavelengths), massive antenna arrays that provide a
high angular resolution, while being packed on a small area will
be used. Moreover, since the abundant mmWave spectrum is barely
occupied, large bandwidth allocation is possible and will enable
low-error time estimation. With this high spatiotemporal
resolution, mmWave technology readily lends itself to extremely
accurate localization that can be harnessed in the network design
and optimization, as well as utilized in many modern
applications. Localization in 5G is still in early stages, and
very little is known about its performance and feasibility.
In this thesis, we contribute to the understanding of 5G mmWave
localization by focusing on challenges pertaining to this
emerging technology. Towards that, we start by considering a
conventional cellular system and propose a positioning method
under outdoor LOS/NLOS conditions that, although approaches the
Cram\'er-Rao lower bound (CRLB), provides accuracy in the order
of meters. This shows that conventional systems have limited
range of location-aware applications. Next, we focus on mmWave
localization in three stages. Firstly, we tackle the initial
access (IA) problem, whereby user equipment (UE) attempts to
establish a link with a base station (BS). The challenge in this
problem stems from the high directivity of mmWave. We investigate
two beamforming schemes: directional and random. Subsequently, we
address 3D localization beyond IA phase. Devices nowadays have
higher computational capabilities and may perform localization in
the downlink. However, beamforming on the UE side is sensitive to
the device orientation. Thus, we study localization in both the
uplink and downlink under multipath propagation and derive the
position (PEB) and orientation error bounds (OEB). We also
investigate the impact of the number of antennas and the number
of beams on these bounds. Finally, the above components assume
that the system is synchronized. However, synchronization in
communication systems is not usually tight enough for
localization. Therefore, we study two-way localization as a means
to alleviate the synchronization requirement and investigate two
protocols: distributed (DLP) and centralized (CLP).
Our results show that random-phase beamforming is more
appropriate IA approach in the studied scenarios. We also observe
that the uplink and downlink are not equivalent, in that the
error bounds scale differently with the number of antennas, and
that uplink localization is sensitive to the UE orientation,
while downlink is not. Furthermore, we find that NLOS paths
generally boost localization. The investigation of the two-way
protocols shows that CLP outperforms DLP by a significant margin.
We also observe that mmWave localization is mainly limited by
angular rather than temporal estimation.
In conclusion, we show that mmWave systems are capable of
localizing a UE with sub-meter position error, and sub-degree
orientation error, which asserts that mmWave will play a central
role in communication network optimization and unlock
opportunities that were not available in the previous generation
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