Today's mobile video suffers from two limitations: 1) it cannot reduce bandwidth consumption by leveraging wireless broadcast to multicast popular content to interested receivers, and 2) it lacks robustness to wireless interference and errors. This paper presents SoftCast, a cross-layer design for mobile video that addresses both limitations. To do so, SoftCast changes the network stack to act like a linear transform. As a result, the transmitted video signal becomes linearly related to the pixels' luminance. Thus, when noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. This enables a video source to multicast a single stream that each receiver decodes to a video quality commensurate with its channel quality. It also increases robustness to interference and errors which now reduce the sharpness of the received pixels but do not cause the video to glitch or stall. We have implemented SoftCast and evaluated it in a testbed of software radios. Our results show that it improves the average video quality for multicast users by 5.5dB, eliminates video glitches caused by mobility, and increases robustness to packet loss by an order of magnitude.

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A cross-layer design for scalable mobile video

We discuss reliable transmission of a discrete memoryless source over a discrete memoryless broadcast channel, where each receiver has side information (of arbitrary quality) about the source unknown to the sender. When there are K=2 receivers, the optimum coding strategy using separate and stand-alone source and channel codes is to build two independent binning structures and send bin indices using degraded message sets through the channel, yielding a full characterization of achievable rates. However, as we show with an example, generalization of this technique to multiple binning schemes does not fully resolve the K>2 case. Joint source-channel coding, on the other hand, allows for a much simpler strategy (i.e., with no explicit binning) yielding a successful single-letter characterization of achievable rates for any Kges2. This characterization, which utilizes a trivial outer bound to the capacity region of general broadcast channels, is in terms of marginal source and channel distributions rather than a joint source-channel distribution. This contrasts with existing results for other multiterminal scenarios and implies that optimal schemes achieve "operational separation." On the other hand, it is shown with an example that an optimal joint source-channel coding strategy is strictly advantageous over the combination of stand-alone source and channel codes, and thus "informational separation" does not hold

Slepian-Wolf coding over broadcast channels

We consider the problem of broadcasting a single Gaussian source to two listeners over a Gaussian broadcast channel, with rho channel uses per source sample, where rho>1. A distortion pair (D1 ,D2) is said to be achievable if one can simultaneously achieve a mean-squared error (MSE) D1 at receiver 1 and D2 at receiver 2. The main result of this correspondence is an outer bound for the set of all achievable distortion pairs. That is, we find necessary conditions under which (D1,D2) is achievable. We then apply this result to the problem of point-to-point transmission over a Gaussian channel with unknown signal-to-noise ratio (SNR) and rho>1. We show that if a system must be optimal at a certain SNRmin, then, asymptotically, the system distortion cannot decay faster than O(1/SNR). As for achievability, we show that a previously reported scheme, due to Mittal and Phamdo (2002), is optimal at high SNR. We introduce two new schemes for broadcasting with bandwidth expansion, combining digital and analog transmissions. We finally show how a system with a partial feedback, returning from the bad receiver to the transmitter and to the good receiver, achieves a distortion pair that lies on the outer bound derived here

Distortion Bounds for Broadcasting With Bandwidth Expansion

This study deals with constructing and implementing new algorithm based on hiding a large amount of data (image, audio, text) file into color BMP image. We have been used adaptive image filtering and adaptive image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with their sub cases for each byte in one pixel. This concept based on both visual and statistical. According to the steps of design, we have been concluded 16 main cases with their sub cases that cover all aspects of the input data into color bitmap image. High security layers have been proposed through three layers to make it difficult to break through the encryption of the input data and confuse steganalysis too. Our results against statistical and visual attacks are discussed and make comparison with the previous Steganography algorithms like S-Tools. We show that our algorithm can embed efficiently a large amount of data that has been reached to 75% of the image size with high quality of the output.

Hiding a Large Amount of Data with High Security Using Steganography Algorithm

This paper deals with lossy joint source-channel coding for transmitting memoryless sources over AWGN channels. The scheme is based on the geometrical interpretation of communication by Kotel'nikov and Shannon where amplitudecontinuous, time-discrete source samples are mapped directly onto the channel using curves or planes. The source and channel spaces can have different dimensions and thereby achieving either compression or error control, depending on whether the source bandwidth is smaller or larger than the channel bandwidth. We present a general theory for 1:N and M:1 dimension changing mappings, and provide two examples for a Gaussian source and channel where we optimize both a 2:1 bandwidth-reducing and a 1:2 bandwidth-expanding mapping. Both examples show high spectral efficiency and provide both graceful degradation and improvement for imperfect channel state information at the transmitter.

Shannon-kotel-nikov mappings in joint source-channel coding

We consider the problem of transmitting a band-limited Gaussian source on an additive band-limited Gaussian noise channel. The well-known "threshold effect" dictates that the more powerful a code is, the more sensitive it is to the exact knowledge of the channel noise. A code is said to be robust if it is asymptotically optimal for a wide range of channel noise. Thus, robust codes have a "graceful degradation" characteristic and are free of the threshold effect. It is demonstrated that robust codes exist whenever the source and channel bandwidths are equal. In the unequal-bandwidth case, a collection of nearly robust joint source-channel codes is constructed using a hybrid digital-analog (HDA) coding technique. For designing nearly robust codes, a matched tandem code whose channel encoder's output is partially/fully matched to its input is proposed and the existence of an asymptotically optimal matched tandem code is shown. The nearly robust codes achieve the Shannon limit (theoretically optimum distortion) and have a less severe threshold effect. Finally, for the case of two different noise conditions, the distortion regions of these codes are determined.

N. Phamdo

Papers

Hybrid digital-analog (HDA) joint source-channel codes for broadcasting and robust communications