14 research outputs found
Bandwidth Partitioning and Downlink Analysis in Millimeter Wave Integrated Access and Backhaul for 5G
With the increasing network densification, it has become exceedingly
difficult to provide traditional fiber backhaul access to each cell site, which
is especially true for small cell base stations (SBSs). The increasing maturity
of millimeter wave (mm-wave) communication has opened up the possibility of
providing high-speed wireless backhaul to such cell sites. Since mm-wave is
also suitable for access links, the third generation partnership project (3GPP)
is envisioning an integrated access and backhaul (IAB) architecture for the
fifth generation (5G) cellular networks in which the same infrastructure and
spectral resources will be used for both access and backhaul. In this paper, we
develop an analytical framework for IAB-enabled cellular network using which
its downlink rate coverage probability is accurately characterized. Using this
framework, we study the performance of three backhaul bandwidth (BW) partition
strategies: 1) equal partition: when all SBSs obtain equal share of the
backhaul BW; 2) instantaneous load-based partition: when the backhaul BW share
of an SBS is proportional to its instantaneous load; and 3) average load-based
partition: when the backhaul BW share of an SBS is proportional to its average
load. Our analysis shows that depending on the choice of the partition
strategy, there exists an optimal split of access and backhaul BW for which the
rate coverage is maximized. Further, there exists a critical volume of
cell-load (total number of users) beyond which the gains provided by the
IAB-enabled network disappear and its performance converges to that of the
traditional macro-only network with no SBSs.Comment: A part of this paper was presented at IEEE ICC 2018. It is available
at arXiv:1710.0625
Ray Tracing Analysis for UAV-assisted Integrated Access and Backhaul Millimeter Wave Networks
The use of Millimeter-wave (mmWave) spectrum in cellular communications has
recently attracted growing interest to support the expected massive increase in
traffic demands. However, the high path-loss at mmWave frequencies poses severe
challenges. In this paper, we analyze the potential coverage gains of using
unmanned aerial vehicles (UAVs), as hovering relays, in integrated access and
backhaul (IAB) mmWave cellular scenarios. Specifically, we utilize the WinProp
software package, which employs ray tracing methodology, to study the
propagation characteristics of outdoor mmWave channels at 30 and 60 GHz
frequency bands in a Manhattan-like environment. In doing so, we propose the
implementation of amplify-and-forward (AF) and decode-and-forward (DF) relaying
mechanisms in the WinProp software. We show how the 3D deployment of UAVs can
be defined based on the coverage ray tracing maps at access and backhaul links.
Furthermore, we propose an adaptive UAV transmission power for the AF relaying.
We demonstrate, with the aid of ray tracing simulations, the performance gains
of the proposed relaying modes in terms of downlink coverage, and the received
signal to interference and noise ratio (SINR).Comment: in Proc. IEEE WoWMoM Workshop Wireless Netw. Planning Comput. UAV
Swarms, Washington, DC, USA, Jun.201
Throughput Analysis in Cache-enabled Millimeter Wave HetNets with Access and Backhaul Integration
Recently, a mmWave-based access and backhaul integration heterogeneous
networks (HetNets) architecture (mABHetNets) has been envisioned to provide
high wireless capacity.Since the access link and the backhaul link share the
same mmwave spectral resource, a large spectrum bandwidth is occupied by the
backhaul link, which hinders the wireless access capacity improvement. To
overcome the backhaul spectrum occupation problem and improve the network
throughput in the existing mABHetNets, we introduce the cache at base stations
(BSs). In detail, by caching popular files at small base stations
(SBSs),mABHetNets can offload the backhaul link traffic and transfer the
redundant backhaul spectrum to the access link to increase the network
throughout. However, introducing cache in SBSs will also incur additional power
consumption and reduce the transmission power, which can lower the network
throughput.In this paper, we investigate spectrum partition between the access
link and the backhaul link as well as cache allocation to improve the network
throughput in mABHetNets. With the stochastic geometry tool, we develop an
analytical framework to characterize cache-enabled mABHetNets and obtain the
signal-to-interference-plus-noise ratio (SINR) distributions in line-of-sight
(LoS) and non-line-of-sight (NLoS) paths. Then we utilize the SINR distribution
to derive the average potential throughput(APT). Extensive numerical results
show that introducing cache can bring up to 80% APT gain to the existing
mABHetNets.Comment: 7 pages,6 figures,conference. arXiv admin note: substantial text
overlap with arXiv:1911.0116
Reliability and Local Delay in Wireless Networks: Does Bandwidth Partitioning Help?
This paper studies the effect of bandwidth partitioning (BWP) on the
reliability and delay performance in infrastructureless wireless networks. The
reliability performance is characterized by the density of concurrent
transmissions that satisfy a certain reliability (outage) constraint and the
delay performance by so-called local delay, defined as the average number of
time slots required to successfully transmit a packet. We concentrate on the
ultrareliable regime where the target outage probability is close to 0. BWP has
two conflicting effects: while the interference is reduced as the concurrent
transmissions are divided over multiple frequency bands, the
signal-to-interference ratio (SIR) requirement is increased due to smaller
allocated bandwidth if the data rate is to be kept constant. Instead, if the
SIR requirement is to be kept the same, BWP reduces the data rate and in turn
increases the local delay. For these two approaches with adaptive and fixed SIR
requirements, we derive closed-form expressions of the local delay and the
maximum density of reliable transmissions in the ultrareliable regime. Our
analysis shows that, in the ultrareliable regime, BWP leads to the
reliability-delay tradeoff.Comment: Accepted in IEEE Globecom 2019. 6 pages, 2 figure
Integrated Access and Backhaul in 5G mmWave Networks: Potentials and Challenges
Integrated Access and Backhaul (IAB) is being investigated as a means to
overcome deployment costs of ultra-dense 5G millimeter wave (mmWave) networks
by realizing wireless backhaul links to relay the access traffic. For the
development of these systems, however, it is fundamental to validate the
performance of IAB in realistic scenarios through end-to-end system level
simulations. In this paper, we shed light on the most recent standardization
activities on IAB, and compare architectures with and without IAB in mmWave
deployments. While it is well understood that IAB networks reduce deployment
costs by obviating the need to provide wired backhaul to each cellular
base-station, in this paper we demonstrate the cell-edge throughput advantage
offered by IAB using end-to-end system level simulations. We further highlight
some research challenges associated with this architecture that will require
further investigations.Comment: Submitted to IEEE Communications Magazine, 7 pages, 4 figure
Designing Cost- and Energy-Efficient Cell-Free Massive MIMO Network with Fiber and FSO Fronthaul Links
The emerging cell-free massive multiple-input multiple-output (CF-mMIMO) is a
promising scheme to tackle the capacity crunch in wireless networks. Designing
the optimal fronthaul network in the CF-mMIMIO is of utmost importance to
deploy a cost- and energy-efficient network. In this paper, we present a
framework to optimally design the fronthaul network of CF-mMIMO utilizing
optical fiber and free space optical (FSO) technologies. We study an uplink
data transmission of the CF-mMIMO network wherein each of the distributed
access points (APs) is connected to a central processing unit (CPU) through a
capacity-limited fronthaul, which could be the optical fiber or FSO. Herein, we
have derived achievable rates and studied the network's energy efficiency in
the presence of power consumption models at the APs and fronthaul links.
Although an optical fiber link has a larger capacity, it consumes less power
and has a higher deployment cost than that of an FSO link. For a given total
number of APs, the optimal number of optical fiber and FSO links and the
optimal capacity coefficient for the optical fibers are derived to maximize the
system's performance. Finally, the network's performance is investigated
through numerical results to highlight the effects of different types of
optical fronthaul links.Comment: 10 pages, 5 figures, This work has been accepted to be published in
the AUT Journal of Electrical Engineerin
Multiple-Association Supporting HTC/MTC in Limited-Backhaul Capacity Ultra-Dense Networks
Coexistence of Human-Type Communications (HTCs) and Machine-Type
Communications (MTCs) is inevitable. Ultra-Dense Networks (UDNs) will be
efficacious in supporting both types of communications. In a UDN, a massive
number of low-power and low-cost Small Cells (SCs) are deployed with density
higher than that of the HTC users. In such a scenario, the backhaul capacities
constitute an intrinsic bottleneck for the system. Hence, we propose a multiple
association scheme where each HTC user associates to and activates multiple SCs
to overcome the backhaul capacity constraints. In addition, having more active
cells allows for more MTC devices to be supported by the network. Using tools
from stochastic geometry, we formulate a novel mathematical framework
investigating the performance of the limited-backhaul capacity UDN in terms of
Area Spectral Efficiency (ASE) for both HTC and MTC and the density of
supported MTC devices. Extensive simulations were conducted to verify the
accuracy of the mathematical analysis under different system parameters.
Results show the existence of an optimum number of SCs to which an HTC user may
connect under backhaul capacity constraints. Besides, the proposed multiple
association scheme significantly improves the performance of MTC in terms of
both ASE and density of supported devices
Deep Reinforcement Learning Based Spectrum Allocation in Integrated Access and Backhaul Networks
We develop a framework based on deep reinforce-ment learning (DRL) to solve
the spectrum allocation problem inthe emerging integrated access and backhaul
(IAB) architecturewith large scale deployment and dynamic environment. The
avail-able spectrum is divided into several orthogonal sub-channels,and the
donor base station (DBS) and all IAB nodes have thesame spectrum resource for
allocation, where a DBS utilizes thosesub-channels for access links of
associated user equipment (UE)as well as for backhaul links of associated IAB
nodes, and anIAB node can utilize all for its associated UEs. This is one ofkey
features in which 5G differs from traditional settings wherethe backhaul
networks were designed independently from theaccess networks. With the goal of
maximizing the sum log-rateof all UE groups, we formulate the spectrum
allocation probleminto a mix-integer and non-linear programming. However, itis
intractable to find an optimal solution especially when theIAB network is large
and time-varying. To tackle this problem,we propose to use the latest DRL
method by integrating anactor-critic spectrum allocation (ACSA) scheme and deep
neuralnetwork (DNN) to achieve real-time spectrum allocation indifferent
scenarios. The proposed methods are evaluated throughnumerical simulations and
show promising results compared withsome baseline allocation policies
Interference Management in UAV-assisted Integrated Access and Backhaul Cellular Networks
An integrated access and backhaul (IAB) network architecture can enable
flexible and fast deployment of next-generation cellular networks. However,
mutual interference between access and backhaul links, small inter-site
distance and spatial dynamics of user distribution pose major challenges in the
practical deployment of IAB networks. To tackle these problems, we leverage the
flying capabilities of unmanned aerial vehicles (UAVs) as hovering IAB-nodes
and propose an interference management algorithm to maximize the overall sum
rate of the IAB network. In particular, we jointly optimize the user and base
station associations, the downlink power allocations for access and backhaul
transmissions, and the spatial configurations of UAVs. We consider two spatial
configuration modes of UAVs: distributed UAVs and drone antenna array (DAA),
and show how they are intertwined with the spatial distribution of ground
users. Our numerical results show that the proposed algorithm achieves an
average of and gains in the received downlink
signal-to-interference-plus-noise ratio (SINR) and overall network sum rate,
respectively. Finally, the numerical results reveal that UAVs cannot only be
used for coverage improvement but also for capacity boosting in IAB cellular
networks.Comment: IEEE Access, Jun. 201
Unified Analysis of HetNets using Poisson Cluster Process under Max-Power Association
Owing to its flexibility in modeling real-world spatial configurations of
users and base stations (BSs), the Poisson cluster process (PCP) has recently
emerged as an appealing way to model and analyze heterogeneous cellular
networks (HetNets). Despite its undisputed relevance to HetNets -- corroborated
by the models used in industry -- the PCP's use in performance analysis has
been limited. This is primarily because of the lack of analytical tools to
characterize performance metrics such as the coverage probability of a user
connected to the strongest BS. In this paper, we develop an analytical
framework for the evaluation of the coverage probability, or equivalently the
complementary cumulative density function (CCDF) of
signal-to-interference-and-noise-ratio (SINR), of a typical user in a K-tier
HetNet under a max power-based association strategy, where the BS locations of
each tier follow either a Poisson point process (PPP) or a PCP. The key
enabling step involves conditioning on the parent PPPs of all the PCPs which
allows us to express the coverage probability as a product of sum-product and
probability generating functionals (PGFLs) of the parent PPPs. In addition to
several useful insights, our analysis provides a rigorous way to study the
impact of the cluster size on the SINR distribution, which was not possible
using existing PPP-based models