Abstract:We explore joint source-channel coding (JSCC) for time-varying channels using a multiresolution framework for both source coding and transmission via novel multiresolution modulation constellations. We consider the problem of still image transmission over time-varying channels with the channel state information (CSI) available at 1) receiver only and 2) both transmitter and receiver being informed about the state of the channel, and we quantify the effect of CSI availability on the performance. Our source mode… Show more
“…Where as, with uniform mapping, errors may occur with equal probability for all coefficients. The probability of error for HR constellation under the influence of channel SNR is given as [7 & 8] (2) K is the error coefficient which is determined by the average number of signals at the minimum distance. Q(.)…”
Section: Decoding Diversity Using Mr-uepmentioning
This paper suggests a generic scheme for provisioning of QoS under largely fluctuating channel quality and flat fading conditions for multimedia communication over satellite. A resolution scalable source is matched to a hierarchical constellation in order to achieve an adaptive decoding capability to combat fluctuations in signal to noise ratio (SNR). The receiver estimates the SNR and if the SNR is found to be below a certain threshold, it reduces the rate by dropping off a higher order constellation which is riding on a baseline QPSK constellation. Thus, the first tier of the scheme guarantees service at lower resolution in poor channel conditions. The second tier of the scheme facilitates near coherent demodulation under frequency nonselective fading conditions. It makes use of pilot symbols which are embedded in the information symbols to probe the fading channel.The received pilots provide an estimate of multiplicative distortion encountered in slow & flat fading channel. This estimated amplitude and phase reference are used to adjust the level and angle of the incoming symbols to the reference constellation. This receiver based rate adaptation scheme is typically suitable for broadcast applications and addresses the issue of service quality provision for a multitude of receivers. It provides a stable reference for demodulation under fading and supports graceful degradation for deteriorating channel conditions. Exhaustive simulations are carried out to examine the validity of the concept.
General TermsJoint source and channel coding (JSCC)
“…Where as, with uniform mapping, errors may occur with equal probability for all coefficients. The probability of error for HR constellation under the influence of channel SNR is given as [7 & 8] (2) K is the error coefficient which is determined by the average number of signals at the minimum distance. Q(.)…”
Section: Decoding Diversity Using Mr-uepmentioning
This paper suggests a generic scheme for provisioning of QoS under largely fluctuating channel quality and flat fading conditions for multimedia communication over satellite. A resolution scalable source is matched to a hierarchical constellation in order to achieve an adaptive decoding capability to combat fluctuations in signal to noise ratio (SNR). The receiver estimates the SNR and if the SNR is found to be below a certain threshold, it reduces the rate by dropping off a higher order constellation which is riding on a baseline QPSK constellation. Thus, the first tier of the scheme guarantees service at lower resolution in poor channel conditions. The second tier of the scheme facilitates near coherent demodulation under frequency nonselective fading conditions. It makes use of pilot symbols which are embedded in the information symbols to probe the fading channel.The received pilots provide an estimate of multiplicative distortion encountered in slow & flat fading channel. This estimated amplitude and phase reference are used to adjust the level and angle of the incoming symbols to the reference constellation. This receiver based rate adaptation scheme is typically suitable for broadcast applications and addresses the issue of service quality provision for a multitude of receivers. It provides a stable reference for demodulation under fading and supports graceful degradation for deteriorating channel conditions. Exhaustive simulations are carried out to examine the validity of the concept.
General TermsJoint source and channel coding (JSCC)
“…The states now form a firstorder Markov sequence. Using this property and the memoryless assumption of the channel (see (1)- (3)), in line with the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm [47], the probability of a particular state given the observed sequence is given by the following forward recursive equation: (10) where the summation is over a subset of states in time step , that are connected to the state . Throughout the paper, we use the notation as a factor normalizing the sum of probabilities to one.…”
Section: ) a Basic Solutionmentioning
confidence: 99%
“…We note that in each time step, the forward recursion of (10) proceeds one step forward through the trellis while the backward term is recomputed over the entire backward window as indicated in (12) and (13). 2 Now, using the presented trellis structure and the forward equation (10), the probabilities required for the asymptotically 2 It is noteworthy that the forward-backward algorithm [47] has been used in different forms and applications such as channel decoding and the decoding in hidden Markov models. In another work [38], similar developments are related to the prediction and filtering within the context of Kalman filtering.…”
Section: ) a Basic Solutionmentioning
confidence: 99%
“…A related classical work is the work of Sundberg [8] in which he analyzed the effect of error in different bits on the reconstruction of a pulse-code modulation (PCM) coded signal. Examples of more recent applications of UEP is present in [9] and [10].…”
Abstract-Exploiting the residual redundancy in a source coder output stream during the decoding process has been proven to be a bandwidth-efficient way to combat noisy channel degradations. This redundancy can be employed to either assist the channel decoder for improved performance or design better source decoders. In this work, a family of solutions for the asymptotically optimum minimum mean-squared error (MMSE) reconstruction of a source over memoryless noisy channels is presented when the redundancy in the source encoder output stream is exploited in the form of a -order Markov model ( 1) and a delay of 0 is allowed in the decoding process. It is demonstrated that the proposed solutions provide a wealth of tradeoffs between computational complexity and the memory requirements. A simplified MMSE decoder which is optimized to minimize the computational complexity is also presented. Considering the same problem setup, several other maximum a posteriori probability (MAP) symbol and sequence decoders are presented as well. Numerical results are presented which demonstrate the efficiency of the proposed algorithms.Index Terms-Forward-backward recursion, joint sourcechannel coding, maximum a posteriori probability (MAP) detection, Markov sources, minimum mean-squared error (MMSE) estimation, residual redundancies, source decoding.
“…The source coding and channel coding are designed separately in [2]- [4], while [5]- [9] are focused on joint source-channel coding (JSCC) design [10], which is just the scheme mainly investigated in this paper because the JSCC scheme has greater performance and more improvement on the overall efficiency than the separate design.…”
Abstract-In this paper, a novel unequal error protection (UEP) scheme, which is constructed from protograph double low-density parity-check (PD-LDPC) codes, and tailored for medical images is proposed to minimize the end to end image distortion over additive white Gaussian noise (AWGN) channel. The UEP scheme is carried out by adopting different coding strategies in terms of the different significant levels and different entropies of image data streams from discrete cosine transform (DCT). A typical radiography image and other two gray-scale images are exploited in the simulation. The experimental results show that the proposed scheme can evidently increase the peak signal to noise ratio (PSNR) value of the received images and reconstruct the transmitted images with good quality even at a very low signal-to-noise ratio (SNR). In particular, the proposed scheme outperforms the other UEP schemes based on regular D-LDPC codes and turbo codes by up to 0.5 and 2.5 dB in the SNR when the PSNR of the reconstructed images reach the expected upper bound, respectively.Index Terms-Unequal error protection (UEP), Protograph Double LDPC (PD-LDPC), Radiography image.
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