43 research outputs found
Inter-session Network Coding for Transmitting Multiple Layered Streams over Single-hop Wireless Networks
This paper studies the problem of transmitting multiple independent layered
video streams over single-hop wireless networks using network coding (NC). We
combine feedback-free random linear NC (RLNC) with unequal error protection
(UEP) and our goal is to investigate the benefits of coding across streams,
i.e. inter session NC. To this end, we present a transmission scheme that in
addition to mixing packets of different layers of each stream (intra-session
NC), mixes packets of different streams as well. Then, we propose the
analytical formulation of the layer decoding probabilities for each user and
utilize it to define a theoretical performance metric. Assessing this
performance metric under various scenarios, it is observed that inter-session
NC improves the trade-off among the performances of users. Furthermore, the
analytical results show that the throughput gain of inter-session NC over
intra-session NC increases with the number of independent streams and also by
increasing packet error rate, but degrades as network becomes more
heterogeneous.Comment: Accepted to be presented at 2014 IEEE Information Theory Workshop
(ITW), 5 pages, 4 figure
Random Linear Network Coding for Wireless Layered Video Broadcast: General Design Methods for Adaptive Feedback-free Transmission
This paper studies the problem of broadcasting layered video streams over
heterogeneous single-hop wireless networks using feedback-free random linear
network coding (RLNC). We combine RLNC with unequal error protection (UEP) and
our main purpose is twofold. First, to systematically investigate the benefits
of UEP+RLNC layered approach in servicing users with different reception
capabilities. Second, to study the effect of not using feedback, by comparing
feedback-free schemes with idealistic full-feedback schemes. To these ends, we
study `expected percentage of decoded frames' as a key content-independent
performance metric and propose a general framework for calculation of this
metric, which can highlight the effect of key system, video and channel
parameters. We study the effect of number of layers and propose a scheme that
selects the optimum number of layers adaptively to achieve the highest
performance. Assessing the proposed schemes with real H.264 test streams, the
trade-offs among the users' performances are discussed and the gain of adaptive
selection of number of layers to improve the trade-offs is shown. Furthermore,
it is observed that the performance gap between the proposed feedback-free
scheme and the idealistic scheme is very small and the adaptive selection of
number of video layers further closes the gap.Comment: 15 pages, 12 figures, 3 tables, Under 2nd round of review, IEEE
Transactions on Communication
On Throughput and Decoding Delay Performance of Instantly Decodable Network Coding
In this paper, a comprehensive study of packet-based instantly decodable
network coding (IDNC) for single-hop wireless broadcast is presented. The
optimal IDNC solution in terms of throughput is proposed and its packet
decoding delay performance is investigated. Lower and upper bounds on the
achievable throughput and decoding delay performance of IDNC are derived and
assessed through extensive simulations. Furthermore, the impact of receivers'
feedback frequency on the performance of IDNC is studied and optimal IDNC
solutions are proposed for scenarios where receivers' feedback is only
available after and IDNC round, composed of several coded transmissions.
However, since finding these IDNC optimal solutions is computational complex,
we further propose simple yet efficient heuristic IDNC algorithms. The impact
of system settings and parameters such as channel erasure probability, feedback
frequency, and the number of receivers is also investigated and simple
guidelines for practical implementations of IDNC are proposed.Comment: This is a 14-page paper submitted to IEEE/ACM Transaction on
Networking. arXiv admin note: text overlap with arXiv:1208.238
From Instantly Decodable to Random Linear Network Coding
Our primary goal in this paper is to traverse the performance gap between two
linear network coding schemes: random linear network coding (RLNC) and
instantly decodable network coding (IDNC) in terms of throughput and decoding
delay. We first redefine the concept of packet generation and use it to
partition a block of partially-received data packets in a novel way, based on
the coding sets in an IDNC solution. By varying the generation size, we obtain
a general coding framework which consists of a series of coding schemes, with
RLNC and IDNC identified as two extreme cases. We then prove that the
throughput and decoding delay performance of all coding schemes in this coding
framework are bounded between the performance of RLNC and IDNC and hence
throughput-delay tradeoff becomes possible. We also propose implementations of
this coding framework to further improve its throughput and decoding delay
performance, to manage feedback frequency and coding complexity, or to achieve
in-block performance adaption. Extensive simulations are then provided to
verify the performance of the proposed coding schemes and their
implementations.Comment: 30 pages with double space, 14 color figure
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
Broadcast Rate Requires Nonlinear Coding in a Unicast Index Coding Instance of Size 36
Insufficiency of linear coding for the network coding problem was first
proved by providing an instance which is solvable only by nonlinear network
coding (Dougherty et al., 2005).Based on the work of Effros, et al., 2015, this
specific network coding instance can be modeled as a groupcast index coding
(GIC)instance with 74 messages and 80 users (where a message can be requested
by multiple users). This proves the insufficiency of linear coding for the GIC
problem. Using the systematic approach proposed by Maleki et al., 2014, the
aforementioned GIC instance can be cast into a unicast index coding (UIC)
instance with more than 200 users, each wanting a unique message. This confirms
the necessity of nonlinear coding for the UIC problem, but only for achieving
the entire capacity region. Nevertheless, the question of whether nonlinear
coding is required to achieve the symmetric capacity (broadcast rate) of the
UIC problem remained open. In this paper, we settle this question and prove the
insufficiency of linear coding, by directly building a UIC instance with only
36users for which there exists a nonlinear index code outperforming the optimal
linear code in terms of the broadcast rate