39,247 research outputs found
Instantly Decodable Network Coding: From Point to Multi-Point to Device-to-Device Communications
The network coding paradigm enhances transmission efficiency by
combining information
flows and has drawn significant attention in information theory,
networking, communications
and data storage. Instantly decodable network coding (IDNC), a
subclass of network coding,
has demonstrated its ability to improve the quality of service of
time critical applications
thanks to its attractive properties, namely the throughput
enhancement, delay reduction,
simple XOR-based encoding and decoding, and small coefficient
overhead. Nonetheless, for
point to multi-point (PMP) networks, IDNC cannot guarantee the
decoding of a specific new
packet at individual devices in each transmission. Furthermore,
for device-to-device (D2D)
networks, the transmitting devices may possess only a subset of
packets, which can be used
to form coded packets. These challenges require the optimization
of IDNC algorithms to be
suitable for different application requirements and network
configurations.
In this thesis, we first study a scalable live video broadcast
over a wireless PMP network,
where the devices receive video packets from a base station. Such
layered live video has a
hard deadline and imposes a decoding order on the video layers.
We design two prioritized
IDNC algorithms that provide a high level of priority to the most
important video layer
before considering additional video layers in coding decisions.
These prioritized algorithms
are shown to increase the number of decoded video layers at the
devices compared to the
existing network coding schemes.
We then study video distribution over a partially connected D2D
network, where a group
of devices cooperate with each other to recover their missing
video content. We introduce
a cooperation aware IDNC graph that defines all feasible coding
and transmission conflictfree
decisions. Using this graph, we propose an IDNC solution that
avoids coding and
transmission conflicts, and meets the hard deadline for high
importance video packets. It is
demonstrated that the proposed solution delivers an improved
video quality to the devices
compared to the video and cooperation oblivious coding schemes.
We also consider a heterogeneous network wherein devices use two
wireless interfaces to
receive packets from the base station and another device
concurrently. For such network,
we are interested in applications with reliable in-order packet
delivery requirements. We
represent all feasible coding opportunities and conflict-free
transmissions using a dual interface
IDNC graph. We select a maximal independent set over the graph by
considering dual
interfaces of individual devices, in-order delivery requirements
of packets and lossy channel
conditions. This graph based solution is shown to reduce the
in-order delivery delay
compared to the existing network coding schemes.
Finally, we consider a D2D network with a group of devices
experiencing heterogeneous
channel capacities. For such cooperative scenarios, we address
the problem of minimizing
the completion time required for recovering all missing packets
at the devices using IDNC
and physical layer rate adaptation. Our proposed IDNC algorithm
balances between the
adopted transmission rate and the number of targeted devices that
can successfully receive
the transmitted packet. We show that the proposed rate aware IDNC
algorithm reduces the
completion time compared to the rate oblivious coding scheme
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
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