2006
DOI: 10.1155/2007/49172
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Combined Source-Channel Coding of Images under Power and Bandwidth Constraints

Abstract: This paper proposes a framework for combined source-channel coding for a power and bandwidth constrained noisy channel. The framework is applied to progressive image transmission using constant envelope M-ary phase shift key (M-PSK) signaling over an additive white Gaussian noise channel. First, the framework is developed for uncoded M-PSK signaling (with M = 2 k ). Then, it is extended to include coded M-PSK modulation using trellis coded modulation (TCM). An adaptive TCM system is also presented. Simulation … Show more

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Cited by 6 publications
(2 citation statements)
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References 27 publications
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“…Since layered video data are sensitive to transmission failures, it is acceptable for servers to eliminate the retransmission and lower the overhead of the unnecessary receptions using FEC. To develop more flexible FEC, most of related works focused on: 1) finding an optimal bit allocation between video coding and channel coding, such as [57] and [58]; 2) designing a new encoder for target source rates under a given channel condition, such as [59]; 3) proposing novel channel coding to achieve the required robustness, such as low-density parity check (LDPC) [60], Turbo [61], Reed-Solomon (RS) [62], and Fountain [63] codes; 4) creating a joint optimization framework that covers all available error control components along with error concealment and transmission control to improve entire system performance, like [64].…”
Section: A Application-layer Coding and Adaptionmentioning
confidence: 99%
“…Since layered video data are sensitive to transmission failures, it is acceptable for servers to eliminate the retransmission and lower the overhead of the unnecessary receptions using FEC. To develop more flexible FEC, most of related works focused on: 1) finding an optimal bit allocation between video coding and channel coding, such as [57] and [58]; 2) designing a new encoder for target source rates under a given channel condition, such as [59]; 3) proposing novel channel coding to achieve the required robustness, such as low-density parity check (LDPC) [60], Turbo [61], Reed-Solomon (RS) [62], and Fountain [63] codes; 4) creating a joint optimization framework that covers all available error control components along with error concealment and transmission control to improve entire system performance, like [64].…”
Section: A Application-layer Coding and Adaptionmentioning
confidence: 99%
“…Protection against channel impairments can be achieved by using codes that provide forward error correction (FEC): Reed-Solomon [4], low density parity check (LDPC) [5], Turbo [6] and fountain [7] [8], as well as joint source-and-channel coding (JSCC) [5] [6] [7]. Other approaches that exploit source scalability to provide UEP use hybrid automatic repeat request or cross-layer optimization [9] [10] [11].…”
Section: Introductionmentioning
confidence: 99%