19,373 research outputs found
Toward one Symbol Network Coding Vectors
In this paper, we propose a novel design for network coding vectors that limits the overhead information. Network coding vectors contain information regarding the operations the packets have undergone in the network nodes. They are used at the decoder side to invert coding operations and recover the data. We propose to reduce the size of this side information with the use of Vandermonde-like generator matrices at the sources. These matrices permit to describe the coding operations performed on packets with only one symbol. We analytically investigate the limitations arising from such design constraints. Interestingly, we find that the feasible generation size is upper bounded by log_2 q in Galois field mathbb{F}_q of size q as this is the maximum packet diversity allowed by the employed generator matrices. In addition, we show that network coding nodes should only perform addition operations in order to maintain the properties of the coding vectors. We finally discuss the benefits and limitations of the proposed coding vectors in practical systems
Coding with Constraints: Minimum Distance Bounds and Systematic Constructions
We examine an error-correcting coding framework in which each coded symbol is
constrained to be a function of a fixed subset of the message symbols. With an
eye toward distributed storage applications, we seek to design systematic codes
with good minimum distance that can be decoded efficiently. On this note, we
provide theoretical bounds on the minimum distance of such a code based on the
coded symbol constraints. We refine these bounds in the case where we demand a
systematic linear code. Finally, we provide conditions under which each of
these bounds can be achieved by choosing our code to be a subcode of a
Reed-Solomon code, allowing for efficient decoding. This problem has been
considered in multisource multicast network error correction. The problem setup
is also reminiscent of locally repairable codes.Comment: Submitted to ISIT 201
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Mobile Audiovisual Terminal: System Design and Subjective Testing in DECT and UMTS networks
It is anticipated that there will shortly be a requirement
for multimedia terminals that operate via mobile
communications systems. This paper presents a functional specification
for such a terminal operating at 32 kb/s in a digital
European cordless telecommunications (DECT) and universal
mobile telecommunications system (UMTS) radio network. A terminal
has been built, based on a PC with digital signal processor
(DSP) boards for audio and video coding and decoding. Speech
coding is by a phonetically driven code-excited linear prediction
(CELP) speech coder and video coding by a block-oriented hybrid
discrete cosine transform (DCT) coder. Separate channel coding
is provided for the audio and video data. The paper describes the
techniques used for audio and video coding, channel coding, and
synchronization. Methods of subjective testing in a DECT network
and in a UMTS network are also described. These consisted of
subjective tests of first impressions of the mobile audio–visual
terminal (MAVT) quality, interactive tests, and the completion
of an exit questionnaire. The test results showed that the quality
of the audio was sufficiently good for comprehension and the
video was sufficiently good for following and repeating simple
mechanical tasks. However, the quality of the MAVT was not
good enough for general use where high-quality audio and video
was needed, especially when transmission was in a noisy radio
environment
On Coding for Reliable Communication over Packet Networks
We present a capacity-achieving coding scheme for unicast or multicast over
lossy packet networks. In the scheme, intermediate nodes perform additional
coding yet do not decode nor even wait for a block of packets before sending
out coded packets. Rather, whenever they have a transmission opportunity, they
send out coded packets formed from random linear combinations of previously
received packets. All coding and decoding operations have polynomial
complexity.
We show that the scheme is capacity-achieving as long as packets received on
a link arrive according to a process that has an average rate. Thus, packet
losses on a link may exhibit correlation in time or with losses on other links.
In the special case of Poisson traffic with i.i.d. losses, we give error
exponents that quantify the rate of decay of the probability of error with
coding delay. Our analysis of the scheme shows that it is not only
capacity-achieving, but that the propagation of packets carrying "innovative"
information follows the propagation of jobs through a queueing network, and
therefore fluid flow models yield good approximations. We consider networks
with both lossy point-to-point and broadcast links, allowing us to model both
wireline and wireless packet networks.Comment: 33 pages, 6 figures; revised appendi
Network monitoring in multicast networks using network coding
In this paper we show how information contained in robust network codes can be used for passive inference of possible locations of link failures or losses in a network. For distributed randomized network coding, we bound the probability of being able to distinguish among a given set of failure events, and give some experimental results for one and two link failures in randomly generated networks. We also bound the required field size and complexity for designing a robust network code that distinguishes among a given set of failure events
Multilevel Topological Interference Management
The robust principles of treating interference as noise (TIN) when it is
sufficiently weak, and avoiding it when it is not, form the background for this
work. Combining TIN with the topological interference management (TIM)
framework that identifies optimal interference avoidance schemes, a baseline
TIM-TIN approach is proposed which decomposes a network into TIN and TIM
components, allocates the signal power levels to each user in the TIN
component, allocates signal vector space dimensions to each user in the TIM
component, and guarantees that the product of the two is an achievable number
of signal dimensions available to each user in the original network.Comment: To be presented at 2013 IEEE Information Theory Worksho
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