58 research outputs found
Distributed Cloud Association in Downlink Multicloud Radio Access Networks
This paper considers a multicloud radio access network (M-CRAN), wherein each
cloud serves a cluster of base-stations (BS's) which are connected to the
clouds through high capacity digital links. The network comprises several
remote users, where each user can be connected to one (and only one) cloud.
This paper studies the user-to-cloud-assignment problem by maximizing a
network-wide utility subject to practical cloud connectivity constraints. The
paper solves the problem by using an auction-based iterative algorithm, which
can be implemented in a distributed fashion through a reasonable exchange of
information between the clouds. The paper further proposes a centralized
heuristic algorithm, with low computational complexity. Simulations results
show that the proposed algorithms provide appreciable performance improvements
as compared to the conventional cloud-less assignment solutions
Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks
In the context of resource allocation in cloud-radio access networks, recent
studies assume either signal-level or scheduling-level coordination. This
paper, instead, considers a hybrid level of coordination for the scheduling
problem in the downlink of a multi-cloud radio-access network, as a means to
benefit from both scheduling policies. Consider a multi-cloud radio access
network, where each cloud is connected to several base-stations (BSs) via high
capacity links, and therefore allows joint signal processing between them.
Across the multiple clouds, however, only scheduling-level coordination is
permitted, as it requires a lower level of backhaul communication. The frame
structure of every BS is composed of various time/frequency blocks, called
power-zones (PZs), and kept at fixed power level. The paper addresses the
problem of maximizing a network-wide utility by associating users to clouds and
scheduling them to the PZs, under the practical constraints that each user is
scheduled, at most, to a single cloud, but possibly to many BSs within the
cloud, and can be served by one or more distinct PZs within the BSs' frame. The
paper solves the problem using graph theory techniques by constructing the
conflict graph. The scheduling problem is, then, shown to be equivalent to a
maximum-weight independent set problem in the constructed graph, in which each
vertex symbolizes an association of cloud, user, BS and PZ, with a weight
representing the utility of that association. Simulation results suggest that
the proposed hybrid scheduling strategy provides appreciable gain as compared
to the scheduling-level coordinated networks, with a negligible degradation to
signal-level coordination
Joint Hybrid Backhaul and Access Links Design in Cloud-Radio Access Networks
The cloud-radio access network (CRAN) is expected to be the core network
architecture for next generation mobile radio systems. In this paper, we
consider the downlink of a CRAN formed of one central processor (the cloud) and
several base-station (BS), where each BS is connected to the cloud via either a
wireless or capacity-limited wireline backhaul link. The paper addresses the
joint design of the hybrid backhaul links (i.e., designing the wireline and
wireless backhaul connections from the cloud to the BSs) and the access links
(i.e., determining the sparse beamforming solution from the BSs to the users).
The paper formulates the hybrid backhaul and access link design problem by
minimizing the total network power consumption. The paper solves the problem
using a two-stage heuristic algorithm. At one stage, the sparse beamforming
solution is found using a weighted mixed `1=`2 norm minimization approach; the
correlation matrix of the quantization noise of the wireline backhaul links is
computed using the classical rate-distortion theory. At the second stage, the
transmit powers of the wireless backhaul links are found by solving a power
minimization problem subject to quality-of-service constraints, based on the
principle of conservation of rate by utilizing the rates found in the first
stage. Simulation results suggest that the performance of the proposed
algorithm approaches the global optimum solution, especially at high
signal-to-interference-plus-noise ratio (SINR).Comment: 6 pages, 3 figures, IWCPM 201
Hybrid Radio/Free-Space Optical Design for Next Generation Backhaul Systems
The deluge of date rate in today's networks imposes a cost burden on the
backhaul network design. Developing cost efficient backhaul solutions becomes
an exciting, yet challenging, problem. Traditional technologies for backhaul
networks include either radio-frequency backhauls (RF) or optical fibers (OF).
While RF is a cost-effective solution as compared to OF, it supports lower data
rate requirements. Another promising backhaul solution is the free-space optics
(FSO) as it offers both a high data rate and a relatively low cost. FSO,
however, is sensitive to nature conditions, e.g., rain, fog, line-of-sight.
This paper combines both RF and FSO advantages and proposes a hybrid RF/FSO
backhaul solution. It considers the problem of minimizing the cost of the
backhaul network by choosing either OF or hybrid RF/FSO backhaul links between
the base-stations (BS) so as to satisfy data rate, connectivity, and
reliability constraints. It shows that under a specified realistic assumption
about the cost of OF and hybrid RF/FSO links, the problem is equivalent to a
maximum weight clique problem, which can be solved with moderate complexity.
Simulation results show that the proposed solution shows a close-to-optimal
performance, especially for practical prices of the hybrid RF/FSO links
Resilient Backhaul Network Design Using Hybrid Radio/Free-Space Optical Technology
The radio-frequency (RF) technology is a scalable solution for the backhaul
planning. However, its performance is limited in terms of data rate and
latency. Free Space Optical (FSO) backhaul, on the other hand, offers a higher
data rate but is sensitive to weather conditions. To combine the advantages of
RF and FSO backhauls, this paper proposes a cost-efficient backhaul network
using the hybrid RF/FSO technology. To ensure a resilient backhaul, the paper
imposes a given degree of redundancy by connecting each node through
link-disjoint paths so as to cope with potential link failures. Hence, the
network planning problem considered in this paper is the one of minimizing the
total deployment cost by choosing the appropriate link type, i.e., either
hybrid RF/FSO or optical fiber (OF), between each couple of base-stations while
guaranteeing link-disjoint connections, a data rate target, and a
reliability threshold. The paper solves the problem using graph theory
techniques. It reformulates the problem as a maximum weight clique problem in
the planning graph, under a specified realistic assumption about the cost of OF
and hybrid RF/FSO links. Simulation results show the cost of the different
planning and suggest that the proposed heuristic solution has a
close-to-optimal performance for a significant gain in computation complexity
A Tutorial on Clique Problems in Communications and Signal Processing
Since its first use by Euler on the problem of the seven bridges of
K\"onigsberg, graph theory has shown excellent abilities in solving and
unveiling the properties of multiple discrete optimization problems. The study
of the structure of some integer programs reveals equivalence with graph theory
problems making a large body of the literature readily available for solving
and characterizing the complexity of these problems. This tutorial presents a
framework for utilizing a particular graph theory problem, known as the clique
problem, for solving communications and signal processing problems. In
particular, the paper aims to illustrate the structural properties of integer
programs that can be formulated as clique problems through multiple examples in
communications and signal processing. To that end, the first part of the
tutorial provides various optimal and heuristic solutions for the maximum
clique, maximum weight clique, and -clique problems. The tutorial, further,
illustrates the use of the clique formulation through numerous contemporary
examples in communications and signal processing, mainly in maximum access for
non-orthogonal multiple access networks, throughput maximization using index
and instantly decodable network coding, collision-free radio frequency
identification networks, and resource allocation in cloud-radio access
networks. Finally, the tutorial sheds light on the recent advances of such
applications, and provides technical insights on ways of dealing with mixed
discrete-continuous optimization problems
- …