This paper studies a multi-terminalsourcecoding problem, where two terminals possess two (correlated) Gaussian sources to be compressed and delivered to the destination through an intermediate relay. Unlike the CEO ...
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ISBN:
(纸本)9781457705953
This paper studies a multi-terminalsourcecoding problem, where two terminals possess two (correlated) Gaussian sources to be compressed and delivered to the destination through an intermediate relay. Unlike the CEO and conventional two-terminalsourcecoding problems as well as point-to-point relay sourcecoding problem, lattices are found to play an important role in achieving "good" rates for this problem setting. Two achievable strategies - compute-and-forward and compress-and-forward are used to develop achievable rates for this problem setting. For the symmetric case, the inner and outer bounds developed are shown to be within 1/2 bits of each other.
In this paper, we consider a cache aided network in which each user is assumed to have individual caches, while upon users' requests, an update message is sent through a common link to all users. First, we formula...
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In this paper, we consider a cache aided network in which each user is assumed to have individual caches, while upon users' requests, an update message is sent through a common link to all users. First, we formulate a general information theoretic setting that represents the database as a discrete memoryless source, and the users' requests as side information that is available everywhere except at the cache encoder. The decoders' objective is to recover a function of the source and the side information. By viewing cache aided networks in terms of a general distributed sourcecoding problem and through information theoretic arguments, we present inner and outer bounds on the fundamental tradeoff of cache memory size and update rate. Then, we specialize our general inner and outer bounds to a specific model of content delivery networks: file selection networks, in which the database is a collection of independent equal-size files and each user requests one of the files independently. For file selection networks, we provide an outer bound and two inner bounds (for centralized and decentralized caching strategies). For the case when the user request information is uniformly distributed, we characterize the rate versus cache size tradeoff to within a multiplicative gap of 4. By further extending our arguments to the framework of Maddah-Ali and Niesen, we also establish a new outer bound and two new inner bounds in which it is shown to recover the centralized and decentralized strategies, previously established by Maddah-Ali and Niesen. Finally, in terms of rate versus cache size tradeoff, we improve the previous multiplicative gap of 72 to 4.7 for the average case with unitbrm requests.
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