2 research outputs found
Partially Block Markov Superposition Transmission of Gaussian Source with Nested Lattice Codes
This paper studies the transmission of Gaussian sources through additive
white Gaussian noise (AWGN) channels in bandwidth expansion regime, i.e., the
channel bandwidth is greater than the source bandwidth. To mitigate the error
propagation phenomenon of conventional digital transmission schemes, we propose
in this paper a new capacity-approaching joint source channel coding (JSCC)
scheme based on partially block Markov superposition transmission (BMST) of
nested lattice codes. In the proposed scheme, first, the Gaussian source
sequence is discretized by a lattice-based quantizer, resulting in a sequence
of lattice points. Second, these lattice points are encoded by a short
systematic group code. Third, the coded sequence is partitioned into blocks of
equal length and then transmitted in the BMST manner. Main characteristics of
the proposed JSCC scheme include: 1) Entropy coding is not used explicitly. 2)
Only parity-check sequence is superimposed, hence, termed partially BMST
(PBMST). This is different from the original BMST. To show the superior
performance of the proposed scheme, we present extensive simulation results
which show that the proposed scheme performs within 1.0 dB of the Shannon
limits. Hence, the proposed scheme provides an attractive candidate for
transmission of Gaussian sources.Comment: 22 pages, 9 figures, Submitted to IEEE Transaction on Communication
Block Markov Superposition Transmission of RUN Codes
In this paper, we propose a simple procedure to construct (decodable) good
codes with any given alphabet (of moderate size) for any given (rational) code
rate to achieve any given target error performance (of interest) over additive
white Gaussian noise (AWGN) channels. We start with constructing codes over
groups for any given code rates. This can be done in an extremely simple way if
we ignore the error performance requirement for the time being. Actually, this
can be satisfied by repetition (R) codes and uncoded (UN) transmission along
with time-sharing technique. The resulting codes are simply referred to as RUN
codes for convenience. The encoding/decoding algorithms for RUN codes are
almost trivial. In addition, the performance can be easily analyzed. It is not
difficult to imagine that a RUN code usually performs far away from the
corresponding Shannon limit. Fortunately, the performance can be improved as
required by spatially coupling the RUN codes via block Markov superposition
transmission (BMST), resulting in the BMST-RUN codes. Simulation results show
that the BMST-RUN codes perform well (within one dB away from Shannon limits)
for a wide range of code rates and outperform the BMST with bit-interleaved
coded modulation (BMST-BICM) scheme.Comment: submitted to IEEE Transactions on Communication