58 research outputs found
A Genetic Algorithm-based Beamforming Approach for Delay-constrained Networks
In this paper, we study the performance of initial access beamforming schemes
in the cases with large but finite number of transmit antennas and users.
Particularly, we develop an efficient beamforming scheme using genetic
algorithms. Moreover, taking the millimeter wave communication characteristics
and different metrics into account, we investigate the effect of various
parameters such as number of antennas/receivers, beamforming resolution as well
as hardware impairments on the system performance. As shown, our proposed
algorithm is generic in the sense that it can be effectively applied with
different channel models, metrics and beamforming methods. Also, our results
indicate that the proposed scheme can reach (almost) the same end-to-end
throughput as the exhaustive search-based optimal approach with considerably
less implementation complexity
An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications
The millimeter wave (mmWave) frequencies offer the potential of orders of
magnitude increases in capacity for next-generation cellular systems. However,
links in mmWave networks are susceptible to blockage and may suffer from rapid
variations in quality. Connectivity to multiple cells - at mmWave and/or
traditional frequencies - is considered essential for robust communication. One
of the challenges in supporting multi-connectivity in mmWaves is the
requirement for the network to track the direction of each link in addition to
its power and timing. To address this challenge, we implement a novel uplink
measurement system that, with the joint help of a local coordinator operating
in the legacy band, guarantees continuous monitoring of the channel propagation
conditions and allows for the design of efficient control plane applications,
including handover, beam tracking and initial access. We show that an
uplink-based multi-connectivity approach enables less consuming, better
performing, faster and more stable cell selection and scheduling decisions with
respect to a traditional downlink-based standalone scheme. Moreover, we argue
that the presented framework guarantees (i) efficient tracking of the user in
the presence of the channel dynamics expected at mmWaves, and (ii) fast
reaction to situations in which the primary propagation path is blocked or not
available.Comment: Submitted for publication in IEEE Transactions on Wireless
Communications (TWC
Statistical Approaches for Initial Access in mmWave 5G Systems
mmWave communication systems overcome high attenuation by using multiple
antennas at both the transmitter and the receiver to perform beamforming. Upon
entrance of a user equipment (UE) into a cell a scanning procedure must be
performed by the base station in order to find the UE, in what is known as
initial access (IA) procedure. In this paper we start from the observation that
UEs are more likely to enter from some directions than from others, as they
typically move along streets, while other movements are impossible due to the
presence of obstacles. Moreover, users are entering with a given time
statistics, for example described by inter-arrival times. In this context we
propose scanning strategies for IA that take into account the entrance
statistics. In particular, we propose two approaches: a memory-less random
illumination (MLRI) algorithm and a statistic and memory-based illumination
(SMBI) algorithm. The MLRI algorithm scans a random sector in each slot, based
on the statistics of sector entrance, without memory. The SMBI algorithm
instead scans sectors in a deterministic sequence selected according to the
statistics of sector entrance and time of entrance, and taking into account the
fact that the user has not yet been discovered (thus including memory). We
assess the performance of the proposed methods in terms of average discovery
time
Context Information Based Initial Cell Search for Millimeter Wave 5G Cellular Networks
Millimeter wave (mmWave) communication is envisioned as a cornerstone to
fulfill the data rate requirements for fifth generation (5G) cellular networks.
In mmWave communication, beamforming is considered as a key technology to
combat the high path-loss, and unlike in conventional microwave communication,
beamforming may be necessary even during initial access/cell search. Among the
proposed beamforming schemes for initial cell search, analog beamforming is a
power efficient approach but suffers from its inherent search delay during
initial access. In this work, we argue that analog beamforming can still be a
viable choice when context information about mmWave base stations (BS) is
available at the mobile station (MS). We then study how the performance of
analog beamforming degrades in case of angular errors in the available context
information. Finally, we present an analog beamforming receiver architecture
that uses multiple arrays of Phase Shifters and a single RF chain to combat the
effect of angular errors, showing that it can achieve the same performance as
hybrid beamforming
Improved User Tracking in 5G Millimeter Wave Mobile Networks via Refinement Operations
The millimeter wave (mmWave) frequencies offer the availability of huge
bandwidths to provide unprecedented data rates to next-generation cellular
mobile terminals. However, directional mmWave links are highly susceptible to
rapid channel variations and suffer from severe isotropic pathloss. To face
these impairments, this paper addresses the issue of tracking the channel
quality of a moving user, an essential procedure for rate prediction, efficient
handover and periodic monitoring and adaptation of the user's transmission
configuration. The performance of an innovative tracking scheme, in which
periodic refinements of the optimal steering direction are alternated to
sparser refresh events, are analyzed in terms of both achievable data rate and
energy consumption, and compared to those of a state-of-the-art approach. We
aim at understanding in which circumstances the proposed scheme is a valid
option to provide a robust and efficient mobility management solution. We show
that our procedure is particularly well suited to highly variant and unstable
mmWave environments.Comment: Accepted for publication to the 16th IEEE Annual Mediterranean Ad Hoc
Networking Workshop (MED-HOC-NET), Jun. 201
Genetic Algorithm-Based Beam Refinement for Initial Access in Millimeter Wave Mobile Networks
Initial access (IA) is identified as a key challenge for the upcoming 5G mobile communication system operating at high carrier frequencies, and several techniques are currently being proposed. In this paper, we extend our previously proposed efficient genetic algorithm-(GA-) based beam refinement scheme to include beamforming at both the transmitter and the receiver and compare the performance with alternative approaches in the millimeter wave multiuser multiple-input-multiple-output (MU-MIMO) networks. Taking the millimeter wave communications characteristics and various metrics into account, we investigate the effect of different parameters such as the number of transmit antennas/users/per-user receive antennas, beamforming resolutions, and hardware impairments on the system performance employing different beam refinement algorithms. As shown, our proposed GA-based approach performs well in delay-constrained networks with multiantenna users. Compared to the considered state-of-the-art schemes, our method reaches the highest service outage-constrained end-to-end throughput with considerably less implementation complexity. Moreover, taking the users\u27 mobility into account, our GA-based approach can remarkably reduce the beam refinement delay at low/moderate speeds when the spatial correlation is taken into account. Finally, we compare the cases of collaborative users and noncollaborative users and evaluate their difference in system performance
- …