J. Chakareski and P. A. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," Microsoft Research Technical Report MSR-TR-2002-81, August 2002.  Home/Search   Document Details and Download   Summary   Related Articles   Check

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J. Chakareski and P.A. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," Tech. Rep. MSR-TR-

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J. Chakareski and P.A. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," in Proc. Int'l Conf. Acoustics, Speech, and Signal Processing,Orlando,FL, May 2002, IEEE, vol. 3, pp. 2513--2516.

....using histograms of these numbers over all data units. It can be seen from Figure 3 that for BERs 10 , at most 2 parity packets are needed for decoding. On the whole, including BER = 10 , not more than 4 parity packets suffice to observe success in decoding in every instance. In [32] we also evaluate the PoDF as a function of the number of paths for the List Viterbi decoder and the number of iterations for the Turbo decoding algorithm. Those results are not included here due to space considerations. B. Error cost performances In this subsection we examine the expected ....

J. Chakareski and P. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," Microsoft Research, Redmond, WA, Tech. Rep. MSR-TR-2002-81, Aug. 2002, publicly available at ftp://ftp.research.microsoft.com/pub/tr/TR-2002-81.ps.

....paper are the introduction of an incremental redundancy scheme for application layer error control in multimedia streaming to wireless clients, and an extension of our previous rate distortion optimization framework to accommodate this new scheme. Parts of this work have already been presented in [26, 27]. We present the major ideas in our paper as follows. In Section II we define our abstractions of the encoding, packetization, and communication processes. In Section III we present in detail our In this paper, a transmission policy is an algorithm for transmitting data, following the ....

J. Chakareski and P. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," in Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, vol. 3. Orlando, FL: IEEE, May 2002, pp. 2513-- 2516.

....packet. The lower convex hull of the set of all expected error cost pairs is called the error cost function. How to compute this function, for the scenario of hybrid receiver sender driven streaming, is the focus of this paper. To our knowledge, the most closely related contemporaneous works are [1 3] where the authors have studied distortion rate optimized streaming over lossy packet networks to wireline and to wireless clients, in both sender driven and receiver driven scenarios, and [4, 5] which considers proxy caching in a costdistortion optimization framework. Another related work is [6] ....

...., if the action taken at state . Therefore, the policies for this case of transmission history are necessarily subtrees of the Markov decision tree shown in Figure 1. Tree structured transmission policies in a rate distortion optimization framework have been studied for the first time in [3, 7]. As stated earlier we are interested in the policy minimizing the expected Lagrangian #8R #8R 1 X4Q #8R 2 #BxF #BxF (1) where #BxF . Let #BxFb #BxF 1 X4Q #BxF J#BxFbhg G xFb R #BxFb #BxFbhg otherwise be the expected ....

J. Chakareski and P. A. Chou. Application layer error correction coding for rate-distortion optimized streaming to wireless clients. In Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, Orlando, FL, May 2002. IEEE.

....The solution to this resource allocation problem is obtained by minimizing a Lagrangian, taking into account the data units dependence relationships in addition to their different delivery deadlines and basic importances. To our knowledge, the most closely related contemporaneous works are [1 4] where the authors have studied distortion rate optimized streaming over lossy packet networks to wireline and to wireless clients, in both sender driven and receiver driven scenarios, and [5, 6] which considers proxy caching in a costdistortion optimization framework. Another related work is [7] ....

.... backward channel is similarly characterized by the probability of packet loss ) and delay density ( Furthermore Channel 2 is modeled as an independent time invariant packet erasure channel with random delays at the packet level and as a binary symmetric channel (BSC) at the bit level [3, 4]. Hence the forward channel is characterized with random loss, delay density and BER , 0 1(2 . 3 5476 . These induce a modified probability of packet loss, which also accounts for packets being discarded by the client platform due to corrupted IP UDP RTP header, i.e. ....

[Article contains additional citation context not shown here]

J. Chakareski and P. A. Chou. Application layer error correction coding for rate-distortion optimized streaming to wireless clients. In Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, Orlando, FL, May 2002. IEEE.

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J. Chakareski and P. A. Chou. Application layer error correction coding for ratedistortion optimized streaming to wireless clients. In Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, Orlando, FL, May 2002. IEEE.

....substantial gains. The framework put forth in [22] is flexible. Using the framework, optimized packet schedules can be computed at the sender [22] or at the receiver [23] The framework is also applicable to streaming over heterogenous networks, where the last hop to the client is wireless [24]. The authors have also presented simplified methods to compute approximately optimized policies that require low computational complexity. Furthermore, the framework, as shown in [23] appears to be robust against simplifications to the algorithm and approximations to , the information ....

J. Chakareski and P. A. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," in Proc. IEEE Int. Conf. on Acoust., Speech and Sig. Proc., Orlando, USA, May 2002.

....The solution to this resource allocation problem is obtained by minimizing a Lagrangian, taking into account the data units dependence relationships in addition to their different delivery deadlines and basic importances. To our knowledge, the most closely related contemporaneous works are [1 4] where the authors have studied distortionrate optimized streaming over lossy packet networks to wireline and to wireless clients, in both sender driven and receiverdriven scenarios, and [5] which considers proxy caching in a cost distortion optimization framework. Another related work is [6] ....

..... The backward channel is similarly characterized by the probability of packet loss B1 and delay density pB1 . Furthermore Channel 2 is modeled as an independent time invariant packet erasure channel with random delays at the packet level and as a binary symmetric channel (BSC) at the bit level [3, 4]. Hence the forward channel is characterized with random loss, delay density and BER F2 ; pF2 ; BERF2 . These induce a modified probability of packet loss, which also accounts for packets being discarded by the client platform due to corrupted IP UDP RTP header, i.e. F2 (1 ....

[Article contains additional citation context not shown here]

J. Chakareski and P. A. Chou. Application layer error correction coding for rate-distortion optimized streaming to wireless clients. In Proc. Int'l Conf. Acoustics, Speech, and Signal Processing, Orlando, FL, May 2002.

....[5] for the rst parity packet, or using the Turbo decoding algorithm [6] for subsequent parity packets. The client immediately transmits an ACK to the server upon successful decoding, or a NAK upon decoding failure. For more details on the incremental redundancy scheme, we refer the reader to [3, 4]. The server may transmit a packet for a data unit at any of a nite set of transmission opportunities t 0 ; t 1 ; t N 1 . Whether or not the server transmits a packet at any given transmission opportunity is determined by the server s transmission policy for the data unit, which takes ....

J. Chakareski and P.A. Chou, Application Layer Error Correction Coding for RateDistortion Optimized Streaming to Wireless Clients, submitted to IEEE Intern. Conf. on Acoustics, Speech, and Signal Proc. (ICASSP)

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J. Chakareski and P. A. Chou, "Application layer error correction coding for rate-distortion optimized streaming to wireless clients," Microsoft Research Technical Report MSR-TR-2002-81, August 2002.

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J. Chakareski and P. A. Chou, "Application layer error correction coding for ratedistortion optimized streaming to wireless clients," in IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings ICASSP '02, Orlando, FL, May 2002.

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