188 research outputs found
Enabling Quality-Driven Scalable Video Transmission over Multi-User NOMA System
Recently, non-orthogonal multiple access (NOMA) has been proposed to achieve
higher spectral efficiency over conventional orthogonal multiple access.
Although it has the potential to meet increasing demands of video services, it
is still challenging to provide high performance video streaming. In this
research, we investigate, for the first time, a multi-user NOMA system design
for video transmission. Various NOMA systems have been proposed for data
transmission in terms of throughput or reliability. However, the perceived
quality, or the quality-of-experience of users, is more critical for video
transmission. Based on this observation, we design a quality-driven scalable
video transmission framework with cross-layer support for multi-user NOMA. To
enable low complexity multi-user NOMA operations, a novel user grouping
strategy is proposed. The key features in the proposed framework include the
integration of the quality model for encoded video with the physical layer
model for NOMA transmission, and the formulation of multi-user NOMA-based video
transmission as a quality-driven power allocation problem. As the problem is
non-concave, a global optimal algorithm based on the hidden monotonic property
and a suboptimal algorithm with polynomial time complexity are developed.
Simulation results show that the proposed multi-user NOMA system outperforms
existing schemes in various video delivery scenarios.Comment: 9 pages, 6 figures. This paper has already been accepted by IEEE
INFOCOM 201
Cross-layer Optimization for Video Delivery over Wireless Networks
As video streaming is becoming the most popular application of Internet mo-
bile, the design and the optimization of video communications over wireless
networks is attracting increasingly attention from both academia and indus-
try. The main challenges are to enhance the quality of service support, and to
dynamically adapt the transmitted video streams to the network condition.
The cross-layer methods, i.e., the exchange of information among different
layers of the system, is one of the key concepts to be exploited to achieve this
goals. In this thesis we propose novel cross-layer optimization frameworks
for scalable video coding (SVC) delivery and for HTTP adaptive streaming
(HAS) application over the downlink and the uplink of Long Term Evolution
(LTE) wireless networks. They jointly address optimized content-aware rate
adaptation and radio resource allocation (RRA) with the aim of maximiz-
ing the sum of the achievable rates while minimizing the quality difference
among multiple videos. For multi-user SVC delivery over downlink wireless
systems, where IP/TV is the most representative application, we decompose
the optimization problem and we propose the novel iterative local approxi-
mation algorithm to derive the optimal solution, by also presenting optimal
algorithms to solve the resulting two sub-problems. For multiple SVC de-
livery over uplink wireless systems, where healt-care services are the most
attractive and challenging application, we propose joint video adaptation
and aggregation directly performed at the application layer of the transmit-
ting equipment, which exploits the guaranteed bit-rate (GBR) provided by
the low-complexity sub-optimal RRA solutions proposed. Finally, we pro-
pose a quality-fair adaptive streaming solution to deliver fair video quality
to HAS clients in a LTE cell by adaptively selecting the prescribed (GBR)
of each user according to the video content in addition to the channel condi-
tion. Extensive numerical evaluations show the significant enhancements of
the proposed strategies with respect to other state-of-the-art frameworks
An intelligent fuzzy logic-based content and channel aware downlink scheduler for scalable video over OFDMA wireless systems
The recent advancements of wireless technology and applications make downlink scheduling and resource allocations an important research topic. In this paper, we consider the problem of downlink scheduling for multi-user scalable video streaming over OFDMA channels. The video streams are precoded using a scalable video coding (SVC) scheme. We propose a fuzzy logic-based scheduling algorithm, which prioritises the transmission to different users by considering video content, and channel conditions. Furthermore, a novel analytical model and a new performance metric have been developed for the performance analysis of the proposed scheduling algorithm. The obtained results show that the proposed algorithm outperforms the content-blind/channel aware scheduling algorithms with a gain of as much as 19% in terms of the number of supported users. The proposed algorithm allows for a fairer allocation of resources among users across the entire sector coverage, allowing for the enhancement of video quality at edges of the cell while minimising the degradation of users closer to the base station
Control of Multiple Remote Servers for Quality-Fair Delivery of Multimedia Contents
This paper proposes a control scheme for the quality-fair delivery of several
encoded video streams to mobile users sharing a common wireless resource. Video
quality fairness, as well as similar delivery delays are targeted among
streams. The proposed controller is implemented within some aggregator located
near the bottleneck of the network. The transmission rate among streams is
adapted based on the quality of the already encoded and buffered packets in the
aggregator. Encoding rate targets are evaluated by the aggregator and fed back
to each remote video server (fully centralized solution), or directly evaluated
by each server in a distributed way (partially distributed solution). Each
encoding rate target is adjusted for each stream independently based on the
corresponding buffer level or buffering delay in the aggregator. Communication
delays between the servers and the aggregator are taken into account. The
transmission and encoding rate control problems are studied with a
control-theoretic perspective. The system is described with a multi-input
multi-output model. Proportional Integral (PI) controllers are used to adjust
the video quality and control the aggregator buffer levels. The system
equilibrium and stability properties are studied. This provides guidelines for
choosing the parameters of the PI controllers. Experimental results show the
convergence of the proposed control system and demonstrate the improvement in
video quality fairness compared to a classical transmission rate fair streaming
solution and to a utility max-min fair approach
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