721 research outputs found
Distortion Exponent in MIMO Channels with Feedback
The transmission of a Gaussian source over a block-fading multiple antenna
channel in the presence of a feedback link is considered. The feedback link is
assumed to be an error and delay free link of capacity 1 bit per channel use.
Under the short-term power constraint, the optimal exponential behavior of the
end-to-end average distortion is characterized for all source-channel bandwidth
ratios. It is shown that the optimal transmission strategy is successive
refinement source coding followed by progressive transmission over the channel,
in which the channel block is allocated dynamically among the layers based on
the channel state using the feedback link as an instantaneous automatic repeat
request (ARQ) signal.Comment: Presented at the IEEE Information Theory Workshop (ITW), Taormina,
Italy, Oct. 200
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
Distortion Exponent in MIMO Fading Channels with Time-Varying Source Side Information
Transmission of a Gaussian source over a time-varying multiple-input
multiple-output (MIMO) channel is studied under strict delay constraints.
Availability of a correlated side information at the receiver is assumed, whose
quality, i.e., correlation with the source signal, also varies over time. A
block-fading model is considered for the states of the time-varying channel and
the time-varying side information; and perfect state information at the
receiver is assumed, while the transmitter knows only the statistics. The high
SNR performance, characterized by the \textit{distortion exponent}, is studied
for this joint source-channel coding problem. An upper bound is derived and
compared with lowers based on list decoding, hybrid digital-analog
transmission, as well as multi-layer schemes which transmit successive
refinements of the source, relying on progressive and superposed transmission
with list decoding. The optimal distortion exponent is characterized for the
single-input multiple-output (SIMO) and multiple-input single-output (MISO)
scenarios by showing that the distortion exponent achieved by multi-layer
superpositon encoding with joint decoding meets the proposed upper bound. In
the MIMO scenario, the optimal distortion exponent is characterized in the low
bandwidth ratio regime, and it is shown that the multi-layer superposition
encoding performs very close to the upper bound in the high bandwidth expansion
regime.Comment: Submitted to IEEE Transactions on Information Theor
Cooperative Downlink Multicell Preprocessing Relying on Reduced-Rate Back-Haul Data Exchange
Different-complexity multicell preprocessing (MCP) schemes employing distributed signal-to-interference leakageplus-noise ratio (SILNR) precoding techniques are proposed, which require reduced back-haul data exchange in comparison with the conventional MCP structure. Our results demonstrate that the proposed structures are capable of increasing the throughput achievable in the cell-edge area while offering different geographic rate profile distributions, as well as meeting different delay requirements
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Cross-layer optimization of unequal protected layered video over hierarchical modulation
Abstract-unequal protection mechanisms have been proposed at several layers in order to improve the reliability of multimedia contents, especially for video data. The paper aims at implementing a multi-layer unequal protection scheme, which is based on a Physical-Transport-Application cross-layer design. Hierarchical modulation, in the physical layer, has been demonstrated to increase the overall user capacity of a wireless communications. On the other hand, unequal erasure protection codes at the transport layer turned out to be an efficient method to protect video data generated by the application layer by exploiting their intrinsic properties. In this paper, the two techniques are jointly optimized in order to enable recovering lost data in case the protection is performed separately. We show that the cross-layer design proposed herein outperforms the performance of hierarchical modulation and unequal erasure codes taken independently
Video QoS/QoE over IEEE802.11n/ac: A Contemporary Survey
The demand for video applications over wireless networks has tremendously increased, and IEEE 802.11 standards have provided higher support for video transmission. However, providing Quality of Service (QoS) and Quality of Experience (QoE) for video over WLAN is still a challenge due to the error sensitivity of compressed video and dynamic channels. This thesis presents a contemporary survey study on video QoS/QoE over WLAN issues and solutions. The objective of the study is to provide an overview of the issues by conducting a background study on the video codecs and their features and characteristics, followed by studying QoS and QoE support in IEEE 802.11 standards. Since IEEE 802.11n is the current standard that is mostly deployed worldwide and IEEE 802.11ac is the upcoming standard, this survey study aims to investigate the most recent video QoS/QoE solutions based on these two standards. The solutions are divided into two broad categories, academic solutions, and vendor solutions. Academic solutions are mostly based on three main layers, namely Application, Media Access Control (MAC) and Physical (PHY) which are further divided into two major categories, single-layer solutions, and cross-layer solutions. Single-layer solutions are those which focus on a single layer to enhance the video transmission performance over WLAN. Cross-layer solutions involve two or more layers to provide a single QoS solution for video over WLAN. This thesis has also presented and technically analyzed QoS solutions by three popular vendors. This thesis concludes that single-layer solutions are not directly related to video QoS/QoE, and cross-layer solutions are performing better than single-layer solutions, but they are much more complicated and not easy to be implemented. Most vendors rely on their network infrastructure to provide QoS for multimedia applications. They have their techniques and mechanisms, but the concept of providing QoS/QoE for video is almost the same because they are using the same standards and rely on Wi-Fi Multimedia (WMM) to provide QoS
Joint Source-Channel Codes for MIMO Block Fading Channels
We consider transmission of a continuous amplitude source over an L-block
Rayleigh fading MIMO channel when the channel state
information is only available at the receiver. Since the channel is not
ergodic, Shannon's source-channel separation theorem becomes obsolete and the
optimal performance requires a joint source -channel approach. Our goal is to
minimize the expected end-to-end distortion, particularly in the high SNR
regime. The figure of merit is the distortion exponent, defined as the
exponential decay rate of the expected distortion with increasing SNR. We
provide an upper bound and lower bounds for the distortion exponent with
respect to the bandwidth ratio among the channel and source bandwidths. For the
lower bounds, we analyze three different strategies based on layered source
coding concatenated with progressive, superposition or hybrid digital/analog
transmission. In each case, by adjusting the system parameters we optimize the
distortion exponent as a function of the bandwidth ratio. We prove that the
distortion exponent upper bound can be achieved when the channel has only one
degree of freedom, that is L=1, and . When we have more
degrees of freedom, our achievable distortion exponents meet the upper bound
for only certain ranges of the bandwidth ratio. We demonstrate that our
results, which were derived for a complex Gaussian source, can be extended to
more general source distributions as well.Comment: 36 pages, 11 figure
Optimized Scalable Image and Video Transmission for MIMO Wireless Channels
In this chapter, we focus on proposing new strategies to efficiently transfer a compressed image/video content through wireless links using a multiple antenna technology. The proposed solutions can be considered as application layer physical layer (APP-PHY) cross layer design methods as they involve optimizing both application and physical layers. After a wide state-of-the-art study, we present two main solutions. The first focuses on using a new precoding algorithm that takes into account the image/video content structure when assigning transmission powers. We showed that its results are better than the existing conventional precoders. Second, a link adaptation process is integrated to efficiently assign coding parameters as a function of the channel state. Simulations over a realistic channel environment show that the link adaptation activates a dynamic process that results in a good image/video reconstruction quality even if the channel is varying. Finally, we incorporated soft decoding algorithms at the receiver side, and we showed that they could induce further improvements. In fact, almost 5 dB peak signal-to-noise ratio (PSNR) improvements are demonstrated in the case of transmission over a Rayleigh channel
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