In this paper, we propose a scheme for the optimal allocation of power, sourcecoding rate, and channelcoding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual se...
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ISBN:
(纸本)9780819484192
In this paper, we propose a scheme for the optimal allocation of power, sourcecoding rate, and channelcoding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower sourcecoding rate, so they will be able to allocate a greater portion of the total available bit rate to channelcoding. Stronger channelcoding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channelcoding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, sourcecoding rate and channelcoding rate for the nodes of the visual sensor network.
Shannon's capacity and rate-distortion function, combined with the separation principle, provide tight bounds for the minimum possible distortion in joint source-channel coding. These bounds, however, are usually ...
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ISBN:
(纸本)9781457705953
Shannon's capacity and rate-distortion function, combined with the separation principle, provide tight bounds for the minimum possible distortion in joint source-channel coding. These bounds, however, are usually achievable only in the limit of large block length. In their 1973 paper, Ziv and Zakai provide a family of alternative capacity and rate-distortion functions, based on functionals satisfying the data-processing inequality, which potentially give tighter bounds for systems with a small block length, e.g., for scalar modulation. We examine a recently proposed approximation for the Ziv-Zakai bounds based on the Renyi-divergence functional. For the specific case of a uniform source, we derive explicit bounds on the Ziv-Zakai-Renyi rate-distortion function, which prove this approximation in the limit of small distortion. Our results can be extended, using the same technique, to more general sources.
We propose a new code design for compress-and-forward relaying over bandlimited relay-to-destination channels. The main contribution of this paper is a code design based on joint (source-channel) coding and modulation...
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ISBN:
(纸本)9781612842547
We propose a new code design for compress-and-forward relaying over bandlimited relay-to-destination channels. The main contribution of this paper is a code design based on joint (source-channel) coding and modulation that uses the correlation between the observations at the relay and the destination as protection against channel errors. This allows for relay nodes with reduced complexity, shifting most of the processing requirements to the destination node. Moreover, by using scalar quantizers with an entropy constraint our system provides remarkable performance in channel conditions where neither amplify-and-forward nor compress-and-forward efficiently exploit the presence of a relay node. Simulation results confirm the benefits of our proposed system.
We consider discrete-time all-analog-processing joint source-channel coding, using non-linear spiral-like curves. We assume a Rayleigh channel, where the receiver may employ or not multiple antennas. Maximum Likelihoo...
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ISBN:
(纸本)9781457705397
We consider discrete-time all-analog-processing joint source-channel coding, using non-linear spiral-like curves. We assume a Rayleigh channel, where the receiver may employ or not multiple antennas. Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detection are considered. Our results show that MMSE performs much better than ML in high CSNR in single-antenna wireless systems, while diversity combining is able to significantly reduce such performance gap, therefore making the low complexity ML decoding very attractive in the case of multiple receive antennas.
We propose a new coding technique for sequential transmission of a stream of Gauss-Markov sources over erasure channels under a zero decoding delay constraint. Our proposed scheme is a combination (hybrid) of predicti...
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We propose a new coding technique for sequential transmission of a stream of Gauss-Markov sources over erasure channels under a zero decoding delay constraint. Our proposed scheme is a combination (hybrid) of predictive coding with truncated memory, and quantization-and-binning. We study the optimality of our proposed scheme using an information theoretic model. In our setup, the encoder observes a stream of source vectors that are spatially independent and identically distributed (i.i.d.) and temporally sampled from a first-order stationary Gauss-Markov process. The channel introduces an erasure burst of a certain maximum length B, starting at an arbitrary time, not known to the transmitter. The reconstruction of each source vector at the destination must be with zero delay and satisfy a quadratic distortion constraint with an average distortion of D. The decoder is not required to reconstruct those source vectors that belong to the period spanning the erasure burst and a recovery window of length W following it. We study the minimum compression rate R(B, W, D) in this setup. As our main result, we establish upper and lower hounds on the compression rate. The upper bound (achievability) is based on our hybrid scheme. It achieves significant gains over baseline schemes such as (leaky) predictive coding, memoryless binning, a separation-based scheme, and a group of pictures based scheme. The lower hound is established by observing connection to a network sourcecoding problem. The bounds simplify in the high resolution regime, where we provide explicit expressions whenever possible, and identify conditions when the proposed scheme is close to optimal. We finally discuss the interplay between the parameters of our burst erasure channel and the statistical channel models and explain how the hounds in the former model can be used to derive insights into the simulation results involving the latter. In particular, our proposed scheme outperforms the baseline schemes over
In this letter, we consider two problems of sending a bivariate Gaussian source through a two-user Gaussian non-orthogonal multiple-access channel. We provide a new distortion outer bound for the considered joint sour...
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In this letter, we consider two problems of sending a bivariate Gaussian source through a two-user Gaussian non-orthogonal multiple-access channel. We provide a new distortion outer bound for the considered joint source-channel coding problems, which significantly reduces the gap between inner and outer bounds of the distortion for correlation coefficients below a threshold. Furthermore, numerical results show, that under some conditions, our proposed outer bound matches with the inner bound obtained via the separate source-channelcoding scheme, which proves the optimality of this scheme.
In recent years, IP (Internet Protocol)-based video surveillance has widely been useful for post-event analysis and assisting the work of privacy protection and public safety. To support high-quality IP video surveill...
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In recent years, IP (Internet Protocol)-based video surveillance has widely been useful for post-event analysis and assisting the work of privacy protection and public safety. To support high-quality IP video surveillance, error-resilience techniques are important for surveillance system design, because video has more stringent requirements than general video transmission for packet loss, latency, and jitter. The optimal FEC (forward error correction) code rate decision is a crucial procedure to determine the optimal source and channelcoding rates to minimize the overall picture distortion when transporting video packets over packet loss channels. The conventional FEC code rate decision schemes using an analytical source-coding distortion model and a channel-induced distortion model are usually complex and typically employ the process of model parameter training, which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate jointsource-channel distortion model to estimate the channel-loss threshold set for optimal FEC code rate decision. Since the proposed model is expressed as a simple closed form and has a small number of scene-dependent model parameters, a video sender of the surveillance system using the model can be easily implemented. For training the scene-dependent model parameters in real time, we propose a practical test-run procedure. This method accelerates the test-run while maintaining its accuracy for training the scene-dependent model parameters. Using the proposed simple model and practical test-run method, the video sender can find the optimal code rate for on-the-fly joint source-channel coding whenever there is a change in the packet-loss condition in the channel. Simulations show that the proposed method can accurately estimate the channel loss threshold set, resulting in an optimal FEC code rate with low computational complexity.
A communication system based on the joint source-channel coding principle is proposed where a fixed-rate source encoder using neither a codebook nor an entropy encoder is exploited to avoid the error propagation effec...
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ISBN:
(纸本)9781467318808
A communication system based on the joint source-channel coding principle is proposed where a fixed-rate source encoder using neither a codebook nor an entropy encoder is exploited to avoid the error propagation effect and thus gain in system robustness. An explicit expression of the mean square error (MSE) distortion of the system for a uniform source is derived. Based on the MSE distortion, the optimal design of the communication system under the total transmission rate constraint is formulated as a mixed integer nonlinear optimization problem. We provide an algorithm to achieve the optimal solution via a convex optimization solver. The numerical result shows that the overall performance of the proposed system is close to the performance of the entropy coding scalar quantizer (ECSQ) system established by A. Gyorgy and T. Linder [1] for almost all rate regions.
Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previ...
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Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previously known asymptotic achievability and converse results, the energy-distortion exponent, defined as the rate of decay of the square-error distortion as the available energy-to-noise ratio increases without bound, is completely characterized for both the point-to-point and broadcast channel cases. Turning then to the scenario of zero-delay transmission, where outage events with arbitrarily small probability are allowed, it is shown that the same energy-distortion exponent as in the infinite-delay case can be achieved in all the studied scenarios.
Virtual reality (VR) and augmented reality (AR) applications with interactions are usually delay-sensitive. Fast delivery of three-dimensional (3-D) models in VR/AR over wireless networks has been a crucial task due t...
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ISBN:
(纸本)9781538635315
Virtual reality (VR) and augmented reality (AR) applications with interactions are usually delay-sensitive. Fast delivery of three-dimensional (3-D) models in VR/AR over wireless networks has been a crucial task due to limited bandwidth and packet error. In this paper we propose an application layer content-aware joint source-channel coding scheme based on forward error correction (FEC). A 3D model is progressively encoded to a base mesh and several refinement layers consisting of connectivity and geometric data. A new design of LT code with a special coding graph has been proposed to provide unequal error protection (UEP) to these two kinds of data. Then a statistical measure is used to optimize the rate allocation for each refinement layer, which is scalable to both network bandwidth and packet loss rate (PLR). Experimental results show that the proposed streaming scheme can achieve the objectives of low transmission delay and small distortion under serious loss.
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