175 research outputs found
Rate Aware Instantly Decodable Network Codes
This paper addresses the problem of reducing the delivery time of data
messages to cellular users using instantly decodable network coding (IDNC) with
physical-layer rate awareness. While most of the existing literature on IDNC
does not consider any physical layer complications and abstract the model as
equally slotted time for all users, this paper proposes a cross-layer scheme
that incorporates the different channel rates of the various users in the
decision process of both the transmitted message combinations and the rates
with which they are transmitted. The consideration of asymmetric rates for
receivers reflects more practical application scenarios and introduces a new
trade-off between the choice of coding combinations for various receivers and
the broadcasting rate for achieving shorter completion time. The completion
time minimization problem in such scenario is first shown to be intractable.
The problem is, thus, approximated by reducing, at each transmission, the
increase of an anticipated version of the completion time. The paper solves the
problem by formulating it as a maximum weight clique problem over a newly
designed rate aware IDNC (RA-IDNC) graph. The highest weight clique in the
created graph being potentially not unique, the paper further suggests a
multi-layer version of the proposed solution to improve the obtained results
from the employed completion time approximation. Simulation results indicate
that the cross-layer design largely outperforms the uncoded transmissions
strategies and the classical IDNC scheme
Throughput Maximization in Cloud Radio Access Networks using Network Coding
This paper is interested in maximizing the total throughput of cloud radio
access networks (CRANs) in which multiple radio remote heads (RRHs) are
connected to a central computing unit known as the cloud. The transmit frame of
each RRH consists of multiple radio resources blocks (RRBs), and the cloud is
responsible for synchronizing these RRBS and scheduling them to users. Unlike
previous works that consider allocating each RRB to only a single user at each
time instance, this paper proposes to mix the flows of multiple users in each
RRB using instantly decodable network coding (IDNC). The proposed scheme is
thus designed to jointly schedule the users to different RRBs, choose the
encoded file sent in each of them, and the rate at which each of them is
transmitted. Hence, the paper maximizes the throughput which is defined as the
number of correctly received bits. To jointly fulfill this objective, we design
a graph in which each vertex represents a possible user-RRB association,
encoded file, and transmission rate. By appropriately choosing the weights of
vertices, the scheduling problem is shown to be equivalent to a maximum weight
clique problem over the newly introduced graph. Simulation results illustrate
the significant gains of the proposed scheme compared to classical coding and
uncoded solutions.Comment: 7 pages, 7 figure
Delivery Time Reduction for Order-Constrained Applications using Binary Network Codes
Consider a radio access network wherein a base-station is required to deliver
a set of order-constrained messages to a set of users over independent erasure
channels. This paper studies the delivery time reduction problem using
instantly decodable network coding (IDNC). Motivated by time-critical and
order-constrained applications, the delivery time is defined, at each
transmission, as the number of undelivered messages. The delivery time
minimization problem being computationally intractable, most of the existing
literature on IDNC propose sub-optimal online solutions. This paper suggests a
novel method for solving the problem by introducing the delivery delay as a
measure of distance to optimality. An expression characterizing the delivery
time using the delivery delay is derived, allowing the approximation of the
delivery time minimization problem by an optimization problem involving the
delivery delay. The problem is, then, formulated as a maximum weight clique
selection problem over the IDNC graph wherein the weight of each vertex
reflects its corresponding user and message's delay. Simulation results suggest
that the proposed solution achieves lower delivery and completion times as
compared to the best-known heuristics for delivery time reduction
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
Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications
From its introduction to its quindecennial, network coding has built a strong reputation for enhancing packet recovery and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the system by proposing elaborate schemes able to reach the network capacity. With the shift toward distributed computing on mobile devices, performance and complexity become both critical factors that affect the efficiency of a coding strategy. Instantly decodable network coding presents itself as a new paradigm in network coding that trades off these two aspects. This paper review instantly decodable network coding schemes by identifying, categorizing, and evaluating various algorithms proposed in the literature. The first part of the manuscript investigates the conventional centralized systems, in which all decisions are carried out by a central unit, e.g., a base-station. In particular, two successful approaches known as the strict and generalized instantly decodable network are compared in terms of reliability, performance, complexity, and packet selection methodology. The second part considers the use of instantly decodable codes in a device-to-device communication network, in which devices speed up the recovery of the missing packets by exchanging network coded packets. Although the performance improvements are directly proportional to the computational complexity increases, numerous successful schemes from both the performance and complexity viewpoints are identified
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