432 research outputs found
Minimum Distortion Variance Concatenated Block Codes for Embedded Source Transmission
Some state-of-art multimedia source encoders produce embedded source bit
streams that upon the reliable reception of only a fraction of the total bit
stream, the decoder is able reconstruct the source up to a basic quality.
Reliable reception of later source bits gradually improve the reconstruction
quality. Examples include scalable extensions of H.264/AVC and progressive
image coders such as JPEG2000. To provide an efficient protection for embedded
source bit streams, a concatenated block coding scheme using a minimum mean
distortion criterion was considered in the past. Although, the original design
was shown to achieve better mean distortion characteristics than previous
studies, the proposed coding structure was leading to dramatic quality
fluctuations. In this paper, a modification of the original design is first
presented and then the second order statistics of the distortion is taken into
account in the optimization. More specifically, an extension scheme is proposed
using a minimum distortion variance optimization criterion. This robust system
design is tested for an image transmission scenario. Numerical results show
that the proposed extension achieves significantly lower variance than the
original design, while showing similar mean distortion performance using both
convolutional codes and low density parity check codes.Comment: 6 pages, 4 figures, In Proc. of International Conference on
Computing, Networking and Communications, ICNC 2014, Hawaii, US
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
TTCM-aided rate-adaptive distributed source coding for Rayleigh fading channels
Adaptive turbo-trellis-coded modulation (TTCM)-aided asymmetric distributed source coding (DSC) is proposed, where two correlated sources are transmitted to a destination node. The first source sequence is TTCM encoded and is further compressed before it is transmitted through a Rayleigh fading channel, whereas the second source signal is assumed to be perfectly decoded and, hence, to be flawlessly shown at the destination for exploitation as side information for improving the decoding performance of the first source. The proposed scheme is capable of reliable communications within 0.80 dB of the Slepian-Wolf/Shannon (SW/S) theoretical limit at a bit error rate (BER) of 10-5. Furthermore, its encoder is capable of accommodating time-variant short-term correlation between the two sources
Concatenated Turbo/LDPC codes for deep space communications: performance and implementation
Deep space communications require error correction codes able to reach extremely low bit-error-rates, possibly with a steep waterfall region and without error floor. Several schemes have been proposed in the literature to achieve these goals. Most of them rely on the concatenation of different codes that leads to high hardware implementation complexity and poor resource sharing. This work proposes a scheme based on the concatenation of non-custom LDPC and turbo codes that achieves excellent error correction performance. Moreover, since both LDPC and turbo codes can be decoded with the BCJR algorithm, our preliminary results show that an efficient hardware architecture with high resource reuse can be designe
Improved Nonlinear Transform Source-Channel Coding to Catalyze Semantic Communications
Recent deep learning methods have led to increased interest in solving
high-efficiency end-to-end transmission problems. These methods, we call
nonlinear transform source-channel coding (NTSCC), extract the semantic latent
features of source signal, and learn entropy model to guide the joint
source-channel coding with variable rate to transmit latent features over
wireless channels. In this paper, we propose a comprehensive framework for
improving NTSCC, thereby higher system coding gain, better model versatility,
and more flexible adaptation strategy aligned with semantic guidance are all
achieved. This new sophisticated NTSCC model is now ready to support large-size
data interaction in emerging XR, which catalyzes the application of semantic
communications. Specifically, we propose three useful improvement approaches.
First, we introduce a contextual entropy model to better capture the spatial
correlations among the semantic latent features, thereby more accurate rate
allocation and contextual joint source-channel coding are developed accordingly
to enable higher coding gain. On that basis, we further propose response
network architectures to formulate versatile NTSCC, i.e., once-trained model
supports various rates and channel states that benefits the practical
deployment. Following this, we propose an online latent feature editing method
to enable more flexible coding rate control aligned with some specific semantic
guidance. By comprehensively applying the above three improvement methods for
NTSCC, a deployment-friendly semantic coded transmission system stands out
finally. Our improved NTSCC system has been experimentally verified to achieve
considerable bandwidth saving versus the state-of-the-art engineered VTM + 5G
LDPC coded transmission system with lower processing latency
Optimized puncturing distributions for irregular non-binary LDPC codes
In this paper we design non-uniform bit-wise puncturing distributions for
irregular non-binary LDPC (NB-LDPC) codes. The puncturing distributions are
optimized by minimizing the decoding threshold of the punctured LDPC code, the
threshold being computed with a Monte-Carlo implementation of Density
Evolution. First, we show that Density Evolution computed with Monte-Carlo
simulations provides accurate (very close) and precise (small variance)
estimates of NB-LDPC code ensemble thresholds. Based on the proposed method, we
analyze several puncturing distributions for regular and semi-regular codes,
obtained either by clustering punctured bits, or spreading them over the
symbol-nodes of the Tanner graph. Finally, optimized puncturing distributions
for non-binary LDPC codes with small maximum degree are presented, which
exhibit a gap between 0.2 and 0.5 dB to the channel capacity, for punctured
rates varying from 0.5 to 0.9.Comment: 6 pages, ISITA1
A Hybrid Statistical and Prioritised Unequal Error Protection Scheme for IEEE 802.11n LDPC Codes
The combination of powerful error correcting codes such as (LDPC) codes and Quadrature Amplitude Modulation (QAM) has been widely deployed in wireless communication standards such as the IEEE 802.11n and DVB-T2. Recently, several Unequal Error Protection schemes which exploit non-uniform degree distribution of bit nodes in irregular LDPC codes have been proposed. In parallel, schemes that exploit the inherent UEP characteristics of the QAM constellation have also been developed. In this paper, a hybrid UEP scheme is proposed for LDPC codes with QAM. The scheme uses statistical distribution of source symbols to map the systematic bits of the LDPC encoded symbols to the QAM constellation. Essentially, systematic symbols having highest probabilities of occurrence are mapped onto the low power region of the QAM constellation and those with a low probability of occurrence are mapped onto the high power region. The decrease in overall transmission power allows for an increased spacing between the QAM constellation points. Additionally, the scheme uses the distribution of the bit node degree of the LDPC code-word to map the parity bits having the highest degree onto prioritised QAM constellation points. Simulations with the IEEE 802.11n LDPC codes revealed that the proposed scheme can provide gains of up to 0.91 dB in Eb/No compared with other UEP schemes for a range of Bit Error Rate (BER) values
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