16 research outputs found
Caching and Coded Multicasting: Multiple Groupcast Index Coding
The capacity of caching networks has received considerable attention in the
past few years. A particularly studied setting is the case of a single server
(e.g., a base station) and multiple users, each of which caches segments of
files in a finite library. Each user requests one (whole) file in the library
and the server sends a common coded multicast message to satisfy all users at
once. The problem consists of finding the smallest possible codeword length to
satisfy such requests. In this paper we consider the generalization to the case
where each user places requests. The obvious naive scheme consists
of applying times the order-optimal scheme for a single request, obtaining
a linear in scaling of the multicast codeword length. We propose a new
achievable scheme based on multiple groupcast index coding that achieves a
significant gain over the naive scheme. Furthermore, through an information
theoretic converse we find that the proposed scheme is approximately optimal
within a constant factor of (at most) .Comment: 5 pages, 1 figure, to appear in GlobalSIP14, Dec. 201
Caching Gain in Wireless Networks with Fading: A Multi-User Diversity Perspective
We consider the effect of caching in wireless networks where fading is the
dominant channel effect. First, we propose a one-hop transmission strategy for
cache-enabled wireless networks, which is based on exploiting multi-user
diversity gain. Then, we derive a closed-form result for throughput scaling of
the proposed scheme in large networks, which reveals the inherent trade-off
between cache memory size and network throughput. Our results show that
substantial throughput improvements are achievable in networks with sources
equipped with large cache size. We also verify our analytical result through
simulations.Comment: 6 pages, 4 figures, conferenc
On the Average Performance of Caching and Coded Multicasting with Random Demands
For a network with one sender, receivers (users) and possible
messages (files), caching side information at the users allows to satisfy
arbitrary simultaneous demands by sending a common (multicast) coded message.
In the worst-case demand setting, explicit deterministic and random caching
strategies and explicit linear coding schemes have been shown to be order
optimal. In this work, we consider the same scenario where the user demands are
random i.i.d., according to a Zipf popularity distribution. In this case, we
pose the problem in terms of the minimum average number of equivalent message
transmissions. We present a novel decentralized random caching placement and a
coded delivery scheme which are shown to achieve order-optimal performance. As
a matter of fact, this is the first order-optimal result for the caching and
coded multicasting problem in the case of random demands.Comment: 5 pages, 3 figure, to appear in ISWCS 201
Fundamental Limits of Coded Caching: Improved Delivery Rate-Cache Capacity Trade-off
A centralized coded caching system, consisting of a server delivering N
popular files, each of size F bits, to K users through an error-free shared
link, is considered. It is assumed that each user is equipped with a local
cache memory with capacity MF bits, and contents can be proactively cached into
these caches over a low traffic period; however, without the knowledge of the
user demands. During the peak traffic period each user requests a single file
from the server. The goal is to minimize the number of bits delivered by the
server over the shared link, known as the delivery rate, over all user demand
combinations. A novel coded caching scheme for the cache capacity of M= (N-1)/K
is proposed. It is shown that the proposed scheme achieves a smaller delivery
rate than the existing coded caching schemes in the literature when K > N >= 3.
Furthermore, we argue that the delivery rate of the proposed scheme is within a
constant multiplicative factor of 2 of the optimal delivery rate for cache
capacities 1/K N >= 3.Comment: To appear in IEEE Transactions on Communication
Coded Caching for a Large Number Of Users
Information theoretic analysis of a coded caching system is considered, in
which a server with a database of N equal-size files, each F bits long, serves
K users. Each user is assumed to have a local cache that can store M files,
i.e., capacity of MF bits. Proactive caching to user terminals is considered,
in which the caches are filled by the server in advance during the placement
phase, without knowing the user requests. Each user requests a single file, and
all the requests are satisfied simultaneously through a shared error-free link
during the delivery phase.
First, centralized coded caching is studied assuming both the number and the
identity of the active users in the delivery phase are known by the server
during the placement phase. A novel group-based centralized coded caching (GBC)
scheme is proposed for a cache capacity of M = N/K. It is shown that this
scheme achieves a smaller delivery rate than all the known schemes in the
literature. The improvement is then extended to a wider range of cache
capacities through memory-sharing between the proposed scheme and other known
schemes in the literature. Next, the proposed centralized coded caching idea is
exploited in the decentralized setting, in which the identities of the users
that participate in the delivery phase are assumed to be unknown during the
placement phase. It is shown that the proposed decentralized caching scheme
also achieves a delivery rate smaller than the state-of-the-art. Numerical
simulations are also presented to corroborate our theoretical results