15,864 research outputs found
Content-Specific Broadcast Cellular Networks based on User Demand Prediction: A Revenue Perspective
The Long Term Evolution (LTE) broadcast is a promising solution to cope with
exponentially increasing user traffic by broadcasting common user requests over
the same frequency channels. In this paper, we propose a novel network
framework provisioning broadcast and unicast services simultaneously. For each
serving file to users, a cellular base station determines either to broadcast
or unicast the file based on user demand prediction examining the file's
content specific characteristics such as: file size, delay tolerance, price
sensitivity. In a network operator's revenue maximization perspective while not
inflicting any user payoff degradation, we jointly optimize resource
allocation, pricing, and file scheduling. In accordance with the state of the
art LTE specifications, the proposed network demonstrates up to 32% increase in
revenue for a single cell and more than a 7-fold increase for a 7 cell
coordinated LTE broadcast network, compared to the conventional unicast
cellular networks.Comment: 6 pages; This paper will appear in the Proc. of IEEE WCNC 201
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
V2X Content Distribution Based on Batched Network Coding with Distributed Scheduling
Content distribution is an application in intelligent transportation system
to assist vehicles in acquiring information such as digital maps and
entertainment materials. In this paper, we consider content distribution from a
single roadside infrastructure unit to a group of vehicles passing by it. To
combat the short connection time and the lossy channel quality, the downloaded
contents need to be further shared among vehicles after the initial
broadcasting phase. To this end, we propose a joint infrastructure-to-vehicle
(I2V) and vehicle-to-vehicle (V2V) communication scheme based on batched sparse
(BATS) coding to minimize the traffic overhead and reduce the total
transmission delay. In the I2V phase, the roadside unit (RSU) encodes the
original large-size file into a number of batches in a rateless manner, each
containing a fixed number of coded packets, and sequentially broadcasts them
during the I2V connection time. In the V2V phase, vehicles perform the network
coded cooperative sharing by re-encoding the received packets. We propose a
utility-based distributed algorithm to efficiently schedule the V2V cooperative
transmissions, hence reducing the transmission delay. A closed-form expression
for the expected rank distribution of the proposed content distribution scheme
is derived, which is used to design the optimal BATS code. The performance of
the proposed content distribution scheme is evaluated by extensive simulations
that consider multi-lane road and realistic vehicular traffic settings, and
shown to significantly outperform the existing content distribution protocols.Comment: 12 pages and 9 figure
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