27 research outputs found
Batched Sparse Codes
Network coding can significantly improve the transmission rate of
communication networks with packet loss compared with routing. However, using
network coding usually incurs high computational and storage costs in the
network devices and terminals. For example, some network coding schemes require
the computational and/or storage capacities of an intermediate network node to
increase linearly with the number of packets for transmission, making such
schemes difficult to be implemented in a router-like device that has only
constant computational and storage capacities. In this paper, we introduce
BATched Sparse code (BATS code), which enables a digital fountain approach to
resolve the above issue. BATS code is a coding scheme that consists of an outer
code and an inner code. The outer code is a matrix generation of a fountain
code. It works with the inner code that comprises random linear coding at the
intermediate network nodes. BATS codes preserve such desirable properties of
fountain codes as ratelessness and low encoding/decoding complexity. The
computational and storage capacities of the intermediate network nodes required
for applying BATS codes are independent of the number of packets for
transmission. Almost capacity-achieving BATS code schemes are devised for
unicast networks, two-way relay networks, tree networks, a class of three-layer
networks, and the butterfly network. For general networks, under different
optimization criteria, guaranteed decoding rates for the receiving nodes can be
obtained.Comment: 51 pages, 12 figures, submitted to IEEE Transactions on Information
Theor
Expander Chunked Codes
Chunked codes are efficient random linear network coding (RLNC) schemes with
low computational cost, where the input packets are encoded into small chunks
(i.e., subsets of the coded packets). During the network transmission, RLNC is
performed within each chunk. In this paper, we first introduce a simple
transfer matrix model to characterize the transmission of chunks, and derive
some basic properties of the model to facilitate the performance analysis. We
then focus on the design of overlapped chunked codes, a class of chunked codes
whose chunks are non-disjoint subsets of input packets, which are of special
interest since they can be encoded with negligible computational cost and in a
causal fashion. We propose expander chunked (EC) codes, the first class of
overlapped chunked codes that have an analyzable performance,where the
construction of the chunks makes use of regular graphs. Numerical and
simulation results show that in some practical settings, EC codes can achieve
rates within 91 to 97 percent of the optimum and outperform the
state-of-the-art overlapped chunked codes significantly.Comment: 26 pages, 3 figures, submitted for journal publicatio
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
Upper Bound Scalability on Achievable Rates of Batched Codes for Line Networks
The capacity of line networks with buffer size constraints is an open, but
practically important problem. In this paper, the upper bound on the achievable
rate of a class of codes, called batched codes, is studied for line networks.
Batched codes enable a range of buffer size constraints, and are general enough
to include special coding schemes studied in the literature for line networks.
Existing works have characterized the achievable rates of batched codes for
several classes of parameter sets, but leave the cut-set bound as the best
existing general upper bound. In this paper, we provide upper bounds on the
achievable rates of batched codes as functions of line network length for these
parameter sets. Our upper bounds are tight in order of the network length
compared with the existing achievability results.Comment: 6 pages, 1 tabl
Inactivation Decoding of LT and Raptor Codes: Analysis and Code Design
In this paper we analyze LT and Raptor codes under inactivation decoding. A
first order analysis is introduced, which provides the expected number of
inactivations for an LT code, as a function of the output distribution, the
number of input symbols and the decoding overhead. The analysis is then
extended to the calculation of the distribution of the number of inactivations.
In both cases, random inactivation is assumed. The developed analytical tools
are then exploited to design LT and Raptor codes, enabling a tight control on
the decoding complexity vs. failure probability trade-off. The accuracy of the
approach is confirmed by numerical simulations.Comment: Accepted for publication in IEEE Transactions on Communication