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Turbo codes are so named because of their iterative soft-decision decoding process, which enables the combination of relatively simple RSC codes to achieve near-optimum performance. Turbo decoding involves iterative exchange between the constituent decoders of progressively better estimates of the message bits, in a decoding procedure that is helped by the statistical independence of the two code sequences generated by each input bit. The turbo decoder is shown in Figure 7.2. In the decoding procedure, each decoder takes into account the information provided by the samples of the channel, which correspond to the systematic (message) and parity bits,

estimate ^n,i will have a minimum mean-squared error equal to if it were in the broadt ci cast domain of node 1. This is the minimum mean-squared error for all nodes in the network that is achievable by the synchronization mechanism. This is why the only optimal estimator needed was the estimator outlined earlier in this section for nodes in the broadcast domain of node 1. Now because the estimate made by node i in R3 is the same as if it would have made in the broadcast domain of node 1, the pulse transmission time for node i again satis es the requirements of Theorem 2.1. Hence, again Theorem 2.1 can be applied. This cycle will then repeat until all nodes are synchronized, and then the cycle will continue to keep the nodes synchronized. It is important to note that with this dense network, the network is optimally synchronized at each step of the synchronization process since every node has access to the transition times of node 1. 2.5 2.5.1 TIME SYNCHRONIZATION SIMULATION Simulator Implementation

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Similar to bandwidth usage, the usage of disk space on the overlay node is also scheduled according to resource provision and session management 4 End-User Subscription At last, after content is transported close to the end users, an end user joins the application layer multicast session by grafting itself to a nearby overlay node on the distribution tree If the end user runs the same application layer multicast software, subscription would be straightforward and be part of the tree organization However, that s not the case for many Internet applications, eg, web browsing or playing QuickTime video, which have established the end-user access convention For these scenarios, another set of algorithms are needed to hook the end user to a nearby overlay node on the distribution tree.

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For example, in Overcast [61], the application layer multicast system allows unmodi ed HTTP clients to join an application layer multicast group by naming the multicast group as a URL The host portion of the URL denotes the multicast source while the path portion identi es a multicast group To subscribe, the end user simply points its browser to this URL The source then uses the HTTP Location: directive to redirect the browser to a nearby overlay node that s part of the distribution tree How to identify the nearby overlay node and route the end user there is the topic of global content routing So we won t elaborate further here..

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equivalent with loudness rating. The method recommended to determine loudness rating eliminates the need for subjective determinations of loudness loss in terms of corrected reference equivalent. The concept of overall loudness loss (OLR) is very similar to the ORE concept used with reference equivalent. Table 3.1 gives opinion results for various values of OLR in dB. These values are based upon representative laboratory conversation test results for telephone connections in which other characteristics such as circuit noise have little contribution to impairment.

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