854 research outputs found
Mobility Increases the Data Offloading Ratio in D2D Caching Networks
Caching at mobile devices, accompanied by device-to-device (D2D)
communications, is one promising technique to accommodate the exponentially
increasing mobile data traffic. While most previous works ignored user
mobility, there are some recent works taking it into account. However, the
duration of user contact times has been ignored, making it difficult to
explicitly characterize the effect of mobility. In this paper, we adopt the
alternating renewal process to model the duration of both the contact and
inter-contact times, and investigate how the caching performance is affected by
mobility. The data offloading ratio, i.e., the proportion of requested data
that can be delivered via D2D links, is taken as the performance metric. We
first approximate the distribution of the communication time for a given user
by beta distribution through moment matching. With this approximation, an
accurate expression of the data offloading ratio is derived. For the
homogeneous case where the average contact and inter-contact times of different
user pairs are identical, we prove that the data offloading ratio increases
with the user moving speed, assuming that the transmission rate remains the
same. Simulation results are provided to show the accuracy of the approximate
result, and also validate the effect of user mobility.Comment: 6 pages, 5 figures, accepted to IEEE Int. Conf. Commun. (ICC), Paris,
France, May 201
Caching with Unknown Popularity Profiles in Small Cell Networks
A heterogenous network is considered where the base stations (BSs), small
base stations (SBSs) and users are distributed according to independent Poisson
point processes (PPPs). We let the SBS nodes to posses high storage capacity
and are assumed to form a distributed caching network. Popular data files are
stored in the local cache of SBS, so that users can download the desired files
from one of the SBS in the vicinity subject to availability. The
offloading-loss is captured via a cost function that depends on a random
caching strategy proposed in this paper. The cost function depends on the
popularity profile, which is, in general, unknown. In this work, the popularity
profile is estimated at the BS using the available instantaneous demands from
the users in a time interval . This is then used to find an estimate
of the cost function from which the optimal random caching strategy is devised.
The main results of this work are the following: First it is shown that the
waiting time to achieve an difference between the achieved
and optimal costs is finite, provided the user density is greater than a
predefined threshold. In this case, is shown to scale as , where
is the support of the popularity profile. Secondly, a transfer
learning-based approach is proposed to obtain an estimate of the popularity
profile used to compute the empirical cost function. A condition is derived
under which the proposed transfer learning-based approach performs better than
the random caching strategy.Comment: 6 pages, Proceedings of IEEE Global Communications Conference, 201
Edge-Caching Wireless Networks: Performance Analysis and Optimization
Edge-caching has received much attention as an efficient technique to reduce
delivery latency and network congestion during peak-traffic times by bringing
data closer to end users. Existing works usually design caching algorithms
separately from physical layer design. In this paper, we analyse edge-caching
wireless networks by taking into account the caching capability when designing
the signal transmission. Particularly, we investigate multi-layer caching where
both base station (BS) and users are capable of storing content data in their
local cache and analyse the performance of edge-caching wireless networks under
two notable uncoded and coded caching strategies. Firstly, we propose a coded
caching strategy that is applied to arbitrary values of cache size. The
required backhaul and access rates are derived as a function of the BS and user
cache size. Secondly, closed-form expressions for the system energy efficiency
(EE) corresponding to the two caching methods are derived. Based on the derived
formulas, the system EE is maximized via precoding vectors design and
optimization while satisfying a predefined user request rate. Thirdly, two
optimization problems are proposed to minimize the content delivery time for
the two caching strategies. Finally, numerical results are presented to verify
the effectiveness of the two caching methods.Comment: to appear in IEEE Trans. Wireless Commu
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