94 research outputs found
Centralized and Cooperative Transmission of Secure Multiple Unicasts using Network Coding
We introduce a method for securely delivering a set of messages to a group of
clients over a broadcast erasure channel where each client is interested in a
distinct message. Each client is able to obtain its own message but not the
others'. In the proposed method the messages are combined together using a
special variant of random linear network coding. Each client is provided with a
private set of decoding coefficients to decode its own message. Our method
provides security for the transmission sessions against computational
brute-force attacks and also weakly security in information theoretic sense. As
the broadcast channel is assumed to be erroneous, the missing coded packets
should be recovered in some way. We consider two different scenarios. In the
first scenario the missing packets are retransmitted by the base station
(centralized). In the second scenario the clients cooperate with each other by
exchanging packets (decentralized). In both scenarios, network coding
techniques are exploited to increase the total throughput. For the case of
centralized retransmissions we provide an analytical approximation for the
throughput performance of instantly decodable network coded (IDNC)
retransmissions as well as numerical experiments. For the decentralized
scenario, we propose a new IDNC based retransmission method where its
performance is evaluated via simulations and analytical approximation.
Application of this method is not limited to our special problem and can be
generalized to a new class of problems introduced in this paper as the
cooperative index coding problem
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
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 for Real-Time Scalable Video Broadcast over Wireless Networks
In this paper, we study a real-time scalable video broadcast over wireless
networks in instantly decodable network coded (IDNC) systems. Such real-time
scalable video has a hard deadline and imposes a decoding order on the video
layers.We first derive the upper bound on the probability that the individual
completion times of all receivers meet the deadline. Using this probability, we
design two prioritized IDNC algorithms, namely the expanding window IDNC
(EW-IDNC) algorithm and the non-overlapping window IDNC (NOW-IDNC) algorithm.
These algorithms provide a high level of protection to the most important video
layer before considering additional video layers in coding decisions. Moreover,
in these algorithms, we select an appropriate packet combination over a given
number of video layers so that these video layers are decoded by the maximum
number of receivers before the deadline. We formulate this packet selection
problem as a two-stage maximal clique selection problem over an IDNC graph.
Simulation results over a real scalable video stream show that our proposed
EW-IDNC and NOW-IDNC algorithms improve the received video quality compared to
the existing IDNC algorithms
Coding Opportunity Densification Strategies for Instantly Decodable Network Coding
In this paper, we aim to identify the strategies that can maximize and
monotonically increase the density of the coding opportunities in instantly
decodable network coding (IDNC).Using the well-known graph representation of
IDNC, first derive an expression for the exact evolution of the edge set size
after the transmission of any arbitrary coded packet. From the derived
expressions, we show that sending commonly wanted packets for all the receivers
can maximize the number of coding opportunities. Since guaranteeing such
property in IDNC is usually impossible, this strategy does not guarantee the
achievement of our target. Consequently, we further investigate the problem by
deriving the expectation of the edge set size evolution after ignoring the
identities of the packets requested by the different receivers and considering
only their numbers. We then employ this expected expression to show that
serving the maximum number of receivers having the largest numbers of missing
packets and erasure probabilities tends to both maximize and monotonically
increase the expected density of coding opportunities. Simulation results
justify our theoretical findings. Finally, we validate the importance of our
work through two case studies showing that our identified strategy outperforms
the step-by-step service maximization solution in optimizing both the IDNC
completion delay and receiver goodput
Coalition Formation Game for Cooperative Content Delivery in Network Coding Assisted D2D Communications
Device-to-device (D2D) communications have shown a huge potential in cellular offloading and become a potential technology in 5G and beyond. In D2D networks, the requested contents by user devices (UDs) can be delivered via D2D links, thus offloading the content providers (CPs). In this work, we address the problem of minimizing the delay of delivering content in a decentralized and partially D2D connected network using network coding (NC) and cooperation among the UDs. The proposed optimization framework considers UDs’ acquired and missing contents, their limited coverage zones, NC, and content’s erasure probability. As such, the completion time for delivering all missing contents to all UDs is minimized. The problem is modeled as a coalition game with cooperative-players wherein the payoff function is derived so that increasing individual payoff results in the desired cooperative behavior. Given the intractability of the formulation, the coalition game is relaxed to a coalition formation game (CFG). A distributed coalition formation algorithm relying on merge-and-split rules is developed for solving the relaxed problem at each transmission. The effectiveness of the proposed solution is validated through computer simulation against existing schemes
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