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On the Optimal Load-Memory Tradeoff of Coded Caching for Location-Based Content

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 Added by Kai Wan
 Publication date 2021
and research's language is English




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Caching at the wireless edge nodes is a promising way to boost the spatial and spectral efficiency, for the sake of alleviating networks from content-related traffic. Coded caching originally introduced by Maddah-Ali and Niesen significantly speeds up communication efficiency by transmitting multicast messages simultaneously useful to multiple users. Most prior works on coded caching are based on the assumption that each user may request all content in the library. However, in many applications the users are interested only in a limited set of content items that depends on their location. For example, visitors in a museum may stream audio and video related to the artworks in the room they are visiting, or assisted self-driving vehicles may access super-high definition maps of the area through which they are travelling. Motivated by these considerations, this paper formulates the coded caching problem for location-based content with edge cache nodes. The considered problem includes a content server with access to N location-based files, K edge cache nodes located at different regions, and K users each of which is in the serving region of one cache node and can retrieve the cached content of this cache node with negligible cost. Depending on the location, each user only requests a file from a location-dependent subset of the library. The objective is to minimize the worst-case load transmitted from the content server among all possible demands. We propose a highly non-trivial converse bound under uncoded cache placement, which shows that a simple achievable scheme is optimal. In addition, this achievable scheme is generally order optimal within 3. Finally, we extend the coded caching problem for location-based content to the multiaccess coded caching topology, where each user is connected to L nearest cache nodes. When $L geq 2$ we characterize the exact optimality on the worst-case load.



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Coded Caching is an efficient technique to reduce peak hour network traffic. One limitation of known coded caching schemes is that the demands of all users are revealed to their peers in the delivery phase. Schemes that assure privacy for user demands are studied in recent past. Assuming that the users are equipped with caches of small memory sizes, the achievable rate under demand privacy constraints is investigated in this work. We present an MDS code based demand private coded caching scheme with $K$ users and $N$ files that achieves a memory rate pair $left(frac{1}{K(N-1)+1},Nleft(1-frac{1}{K(N-1)+1}right)right)$. The presented memory-rate pair meets the lower bound under demand-privacy requirements, proposed by Yan textit{et al.} in the recent work cite{c13}. By memory sharing this characterizes the exact rate-memory trade-off for the demand private coded caching scheme for cache memory $Min left[0,frac{1}{K(N-1)+1}right]$.
72 - Yong Deng , Min Dong 2021
For a caching system with multiple users, we aim to characterize the memory-rate tradeoff for caching with uncoded cache placement, under nonuniform file popularity. Focusing on the modified coded caching scheme (MCCS) recently proposed by Yu, etal., we formulate the cache placement optimization problem for the MCCS to minimize the average delivery rate under nonuniform file popularity, restricting to a class of popularity-first placements. We then present two information-theoretic lower bounds on the average rate for caching with uncoded placement, one for general cache placements and the other restricted to the popularity-first placements. By comparing the average rate of the optimized MCCS with the lower bounds, we prove that the optimized MCCS attains the general lower bound for the two-user case, providing the exact memory-rate tradeoff. Furthermore, it attains the popularity-first-based lower bound for the case of general K users with distinct file requests. In these two cases, our results also reveal that the popularity-first placement is optimal for the MCCS, and zero-padding used in coded delivery incurs no loss of optimality. For the case of K users with redundant file requests, our analysis shows that there may exist a gap between the optimized MCCS and the lower bounds due to zero-padding. We next fully characterize the optimal popularity-first cache placement for the MCCS, which is shown to possess a simple file-grouping structure and can be computed via an efficient algorithm using closed-form expressions. Finally, we extend our study to accommodate both nonuniform file popularity and sizes, where we show that the optimized MCCS attains the lower bound for the two-user case, providing the exact memory-rate tradeoff. Numerical results show that, for general settings, the gap between the optimized MCCS and the lower bound only exists in limited cases and is very small.
We study downlink beamforming in a single-cell network with a multi-antenna base station serving cache-enabled users. Assuming a library of files with a common rate, we formulate the minimum transmit power with proactive caching and coded delivery as a non-convex optimization problem. While this multiple multicast problem can be efficiently solved by successive convex approximation (SCA), the complexity of the problem grows exponentially with the number of subfiles delivered to each user in each time slot, which itself grows exponentially with the number of users. We introduce a low-complexity alternative through time-sharing that limits the number of subfiles received by a user in each time slot. We then consider the joint design of beamforming and content delivery with sparsity constraints to limit the number of subfiles received by a user in each time slot. Numerical simulations show that the low-complexity scheme has only a small performance gap to that obtained by solving the joint problem with sparsity constraints, and outperforms state-of-the-art results at all signal-to-noise ratio (SNR) and rate values with a sufficient number of transmit antennas. A lower bound on the achievable degrees-of-freedom (DoF) of the low-complexity scheme is derived to characterize its performance in the high SNR regime.
Coded caching is an efficient way to reduce network traffic congestion during peak hours by storing some content at the users local cache memory without knowledge of later demands. The goal of coded caching design is to minimize the transmission rate and the subpacketization. In practice the demand for each user is sensitive since one can get the other users preferences when it gets the other users demands. The first coded caching scheme with private demands was proposed by Wan et al. However the transmission rate and the subpacketization of their scheme increase with the file number stored in the library. In this paper we consider the following secure coded caching: prevent the wiretappers from obtaining any information about the files in the server and protect the demands from all the users in the delivery phase. We firstly introduce a combinatorial structure called secure placement delivery array (SPDA in short) to realize a coded caching scheme for our security setting. Then we obtain three classes of secure schemes by constructing SPDAs, where one of them is optimal. It is worth noting that the transmission rates and the subpacketizations of our schemes are independent to the file number. Furthermore, comparing with the previously known schemes with the same security setting, our schemes have significantly advantages on the subpacketizations and for some parameters have the advantage on the transmission rates.
Classical coded caching setting avails each user to have one dedicated cache. This is generalized to a more general shared cache scheme and the exact expression for the worst case rate was derived in [E. Parrinello, A. Unsal, P. Elia, Fundamental Limits of Caching in Heterogeneous Networks with Uncoded Prefetching, available on arXiv:1811.06247 [cs.IT], Nov. 2018]. For this case, an optimal linear error correcting delivery scheme is proposed and an expression for the peak rate is established for the same. Furthermore, a new delivery scheme is proposed, which gives an improved rate for the case when the demands are not distinct.
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