77 research outputs found
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
Generalized Instantly Decodable Network Coding for Relay-Assisted Networks
In this paper, we investigate the problem of minimizing the frame completion
delay for Instantly Decodable Network Coding (IDNC) in relay-assisted wireless
multicast networks. We first propose a packet recovery algorithm in the single
relay topology which employs generalized IDNC instead of strict IDNC previously
proposed in the literature for the same relay-assisted topology. This use of
generalized IDNC is supported by showing that it is a super-set of the strict
IDNC scheme, and thus can generate coding combinations that are at least as
efficient as strict IDNC in reducing the average completion delay. We then
extend our study to the multiple relay topology and propose a joint generalized
IDNC and relay selection algorithm. This proposed algorithm benefits from the
reception diversity of the multiple relays to further reduce the average
completion delay in the network. Simulation results show that our proposed
solutions achieve much better performance compared to previous solutions in the
literature.Comment: 5 pages, IEEE PIMRC 201
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
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
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