Joint source and channel coding using a non-linear receiver

Liu, F.-H.; Ho, P.; Cuperman, V.

doi:10.1109/icc.1993.397535

Cited by 62 publications

(34 citation statements)

References 11 publications

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“…The combination of power control and joint source and channel coding for wireless video has taken on an increasing importance [3,14,15]. In order to launch independently layered bitstreams to the individual antennas, a scalable video codec was adopted to generate multi-layer video bitstreams [26] where power allocation was implemented to optimize error performance according to the importance of the source layer, using unequal error protection (UEP).…”

Section: Previous Workmentioning

confidence: 99%

Scalable video delivery over MIMO OFDM wireless systems using joint power allocation and antenna selection

Zhao¹,

You²,

Gui³

2010

Bell Labs Tech. J.

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This paper proposes a scalable video delivery transmission framework over multiple input multiple output (MIMO) wireless systems promises to provide next-generation wireless services such as voice, high-speed data, Internet access, and audio and video streaming on an all-IP network. However, wireless video is highly sensitive to delay and bit error rate (BER)/packet loss in a bandwidth-constrained and variant environment. Furthermore, many existing mobile networks cannot provide a guaranteed quality of service because temporally high bit error rates are unavoidable during

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Section: Previous Workmentioning

confidence: 99%

Scalable video delivery over MIMO OFDM wireless systems using joint power allocation and antenna selection

Zhao¹,

You²,

Gui³

2010

Bell Labs Tech. J.

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“…We then calculate the set of stage decoding probabilities , using (5). The average distortion can now be evaluated from and as (10) Note that the term accounts for the fact that, with probability , none of the stage indices are decoded.…”

Section: ) Ifmentioning

confidence: 99%

“…In these cases, instead of completely rejecting unreliable indices, we decode them while taking into account their degree of reliability. The advantages of weighted decoding for the case of a full search VQ were described in, e.g., [10], [15], and [3]. Consider the following scheme where we decode all the stage indices irrespective of the level of channel noise.…”

Section: Weighted Decoding Of Stage Indicesmentioning

confidence: 99%

Unequally protected multistage vector quantization for time-varying CDMA channels

Gadkari

Rose²

2001

IEEE Trans. Commun.

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Abstract-We present a source-channel coding system for operation over code-division multiple-access channels with time-varying conditions. The proposed system consists of a multistage vector quantizer (MSVQ) in conjunction with unequal protection against channel errors. The receiver estimates the channel conditions and decodes as many stages of the quantizer as can be reliably decoded. The approach to system design and optimization is first derived and evaluated for a system that employs hard decoding of stage indices. The approach is then extended to the more general case of weighted decoding. Simulation results are given for transmission of Gauss-Markov sources over broadcast and slow fading channels. Consistent and substantial improvement is achieved over the standard MSVQ with equal error protection, and the gains, in terms of source signal-to-noise ratio, are in the range of 3-5 dB.

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“…2) Other approaches, where the decoder is adapted to the current level of channel noise, are described in literature. The fact that an optimal estimate of the source vector can be obtained by direct computation as described in (9) was observed in [12], [21], [25], and [26]. A decoding strategy based on linear mapping of block codes is described in [26], while [18] investigates the use of multiresolution codebooks.…”

Section: ) Switched Encodermentioning

confidence: 99%

“…While TEA for robust vector quantization is a direct generalization of the early weighted PCM, it is also related to the more recent work on optimal design of multidimensional constellations for joint source-channel coding [21], [28]. These papers consider the joint design of a VQ and a multidimensional constellation, under an average power constraint.…”

mentioning

confidence: 99%

Vector quantization with transmission energy allocation for time-varying channels

Gadkari

Rose²

1999

IEEE Trans. Commun.

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Abstract-This work is concerned with the problem of designing robust, vector quantizer (VQ)-based communication systems for operation over time-varying Gaussian channels. Transmission energy allocation to VQ codeword bits, according to their error sensitivities, is a powerful tool for improving robustness to channel noise. The power of this technique can be further enhanced by appropriately combining it with index assignment methods. We pose the corresponding joint optimization problem and suggest a simple iterative algorithm for finding a locally optimal solution. The susceptibility of the solution to poor local minima is significantly reduced by an enhanced version of the algorithm which invokes the method of noisy channel relaxation whereby the VQ system is optimized while gradually decreasing the assumed level of channel noise. In a series of experiments, the resulting combined technique is shown to outperform standard pseudo-Gray coding by up to 3.5 dB and to exhibit graceful degradation at mismatched channel conditions. Finally, we extend these ideas to the case where both the transmitter and the receiver have information on the current state of a time-varying channel. The proposed method is based on switched encoding and adaptive decoding. Experimental results show that the proposed system achieves close to optimal performance.

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Joint source and channel coding using a non-linear receiver

Cited by 62 publications

References 11 publications

Scalable video delivery over MIMO OFDM wireless systems using joint power allocation and antenna selection

Scalable video delivery over MIMO OFDM wireless systems using joint power allocation and antenna selection

Unequally protected multistage vector quantization for time-varying CDMA channels

Vector quantization with transmission energy allocation for time-varying channels

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