Fundamental Limits of Cache-Aided Wireless BC: Interplay of Coded-Caching and CSIT Feedback

Zhang, Jingjing; Elia, Petros

doi:10.1109/tit.2017.2674668

Cited by 96 publications

(11 citation statements)

References 45 publications

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“…Several coded caching schemes have been proposed since then [11]- [16]. The caching problem has also been extended in various directions, including decentralized caching [17], online caching [18], caching with nonuniform demands [19]- [22], hierarchical caching [23]- [25], device-to-device caching [26], cache-aided interference channels [27]- [30], caching on file selection networks [31]- [33], caching on broadcast channels [34]- [37], and caching for channels with delayed feedback with channel state information [38], [39]. The same idea is also useful in the context of distributed computing, in order to take advantage of extra computation to reduce the communication load [40]- [44].…”

Section: Introductionmentioning

confidence: 99%

The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

Maddah-Ali

Avestimehr

2018

IEEE Trans. Inform. Theory

303

278

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Abstract-We consider a basic cache network, in which a single server is connected to multiple users via a shared bottleneck link. The server has a database of files (content). Each user has an isolated memory that can be used to cache content in a prefetching phase. In a following delivery phase, each user requests a file from the database, and the server needs to deliver users' demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of the rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the bottleneck link for a given cache size available at each user. In particular, we propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without any coordination.

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Section: Introductionmentioning

confidence: 99%

The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

Maddah-Ali

Avestimehr

2018

IEEE Trans. Inform. Theory

303

278

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“…In particular, the peak rate vs. memory tradeoff was formulated and characterized within a factor of 12 in a basic cache network with a shared bottleneck link [2]. This result has been extended to many scenarios, including decentralized caching [3], online caching [4], caching with nonuniform demands [5]- [7], device-to-device caching [8], caching on file selection networks [9], caching on broadcast channels [10], caching for channels with delayed feedback with channel state information [11], and hierarchical cache networks [12], [13], among others. Essentially, many of these extensions share similar ideas in terms of the achievability and the converse bounds.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the rate-memory tradeoff in cache networks within a factor of 2

Maddah-Ali

Avestimehr

2017

2017 IEEE International Symposium on Information Theory (ISIT)

163

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We consider a basic caching system, where a single server with a database of N files (e.g. movies) is connected to a set of K users through a shared bottleneck link. Each user has a local cache memory with a size of M files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the bottleneck link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), where the best proved characterization in the current literature gives a factor of 4 and 4.7 respectively. Moreover, in the practically important case where the number of files (N ) is large, we exactly characterize the tradeoff for systems with no more than 5 users, and characterize the tradeoff within a factor of 2 otherwise. We establish these results by developing novel information theoretic outer-bounds for the caching problem, which improves the state of the art and gives tight characterization in various cases. I. INTRODUCTIONCaching is a common strategy to mitigate heavy peak-time communication load in a distributed network, via duplicating parts of the content in memories distributed across the network during off-peak times. In other words, caching allows us to trade distributed memory in the network for communication load reduction. Characterizing this fundamental rate-memory tradeoff is of great practical interest, and has been a research subject for several decades. For single-cache networks, the ratememory tradeoff has been characterized for various scenarios in 80th [1]. However, those techniques were found insufficient to tackle the multiple-cache cases. There has been a surge of recent results in information theory that aim at formalizing and characterizing such rate-memory tradeoff in cache networks [2]- [13]. In particular, the peak rate vs. memory tradeoff was formulated and characterized within a factor of 12 in a basic cache network with a shared bottleneck link [2]. This result has been extended to many scenarios, including decentralized caching [3] Essentially, many of these extensions share similar ideas in terms of the achievability and the converse bounds. Therefore, if we can improve the results for the basic bottleneck caching network, the ideas can be used to improve the results in other cases as well.In the literature, various approaches have been proposed for improving the bounds on rate-memory tradeoff for the bottleneck network. Several caching schemes have been proposed in [14]-[21], and converse bounds have also been introduced in [9], [22]-[26]. For the case, where the prefetching is uncoded, the exact rate-memory tradeoff for both peak and average rate (under uniform file popularity) and for both centra...

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“…Coded caching that jointly considers various heterogeneous aspects was studied in [ 17 ]. Other works on coded caching include, e.g., cache-aided noiseless multi-server network [ 18 ], cache-aided wireless/noisy broadcast networks [ 19 , 20 , 21 , 22 ], cache-aided relay networks [ 23 , 24 , 25 ], cache-aided interference management [ 26 , 27 ], coded caching with random demands [ 28 ], caching in combination networks [ 29 ], coded caching under secrecy constraints [ 30 ], coded caching with reduced subpacketization [ 31 , 32 ], the coded caching problem where each user requests multiple files [ 33 ], and a cache-aided broadcast network for correlated content [ 34 ], etc.…”

Section: Introductionmentioning

confidence: 99%

Coded Caching for Broadcast Networks with User Cooperation

Huang

Chen

You

et al. 2022

Entropy

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Caching technique is a promising approach to reduce the heavy traffic load and improve user latency experience for the Internet of Things (IoT). In this paper, by exploiting edge cache resources and communication opportunities in device-to-device (D2D) networks and broadcast networks, two novel coded caching schemes are proposed that greatly reduce transmission latency for the centralized and decentralized caching settings, respectively. In addition to the multicast gain, both schemes obtain an additional cooperation gain offered by user cooperation and an additional parallel gain offered by the parallel transmission among the server and users. With a newly established lower bound on the transmission delay, we prove that the centralized coded caching scheme is order-optimal, i.e., achieving a constant multiplicative gap within the minimum transmission delay. The decentralized coded caching scheme is also order-optimal if each user’s cache size is larger than a threshold which approaches zero as the total number of users tends to infinity. Moreover, theoretical analysis shows that to reduce the transmission delay, the number of users sending signals simultaneously should be appropriately chosen according to the user’s cache size, and always letting more users send information in parallel could cause high transmission delay.

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Fundamental Limits of Cache-Aided Wireless BC: Interplay of Coded-Caching and CSIT Feedback

Cited by 96 publications

References 45 publications

The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

Characterizing the rate-memory tradeoff in cache networks within a factor of 2

Coded Caching for Broadcast Networks with User Cooperation

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