7,500 research outputs found
Performance Analysis and Optimization of Cache-Enabled Small Cell Networks
This paper studies the performance of cache-enabled dense small cell networks consisting of multi- antenna sub-6 GHz and millimeter-wave base stations. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mmWave frequencies. In general, the optimal content placement is unknown when the base stations have multiple antennas. Then we propose a simple yet effective probabilistic content placement scheme to maximize the successful content delivery probability, which could balance caching both the most popular contents and achieving content diversity. Numerical results demonstrate that our proposed content placement scheme yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and millimeter-wave systems reveal an interesting tradeoff between caching capacity and base station density for the millimeter-wave system to achieve similar performance as the sub-6 GHz system
Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks
Caching and multicasting are two promising methods to support massive content
delivery in multi-tier wireless networks. In this paper, we consider a random
caching and multicasting scheme with caching distributions in the two tiers as
design parameters, to achieve efficient content dissemination in a two-tier
large-scale cache-enabled wireless multicasting network. First, we derive
tractable expressions for the successful transmission probabilities in the
general region as well as the high SNR and high user density region,
respectively, utilizing tools from stochastic geometry. Then, for the case of a
single operator for the two tiers, we formulate the optimal joint caching
design problem to maximize the successful transmission probability in the
asymptotic region, which is nonconvex in general. By using the block successive
approximate optimization technique, we develop an iterative algorithm, which is
shown to converge to a stationary point. Next, for the case of two different
operators, one for each tier, we formulate the competitive caching design game
where each tier maximizes its successful transmission probability in the
asymptotic region. We show that the game has a unique Nash equilibrium (NE) and
develop an iterative algorithm, which is shown to converge to the NE under a
mild condition. Finally, by numerical simulations, we show that the proposed
designs achieve significant gains over existing schemes.Comment: 30 pages, 6 pages, submitted to IEEE GLOBECOM 2017 and IEEE Trans.
Commo
Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-antenna Dense Small Cell Networks
This paper studies the performance of cache-enabled dense small cell networks
consisting of multi-antenna sub-6 GHz and millimeter-wave base stations.
Different from the existing works which only consider a single antenna at each
base station, the optimal content placement is unknown when the base stations
have multiple antennas. We first derive the successful content delivery
probability by accounting for the key channel features at sub-6 GHz and mmWave
frequencies. The maximization of the successful content delivery probability is
a challenging problem. To tackle it, we first propose a constrained
cross-entropy algorithm which achieves the near-optimal solution with moderate
complexity. We then develop another simple yet effective heuristic
probabilistic content placement scheme, termed two-stair algorithm, which
strikes a balance between caching the most popular contents and achieving
content diversity. Numerical results demonstrate the superior performance of
the constrained cross-entropy method and that the two-stair algorithm yields
significantly better performance than only caching the most popular contents.
The comparisons between the sub-6 GHz and mmWave systems reveal an interesting
tradeoff between caching capacity and density for the mmWave system to achieve
similar performance as the sub-6 GHz system.Comment: 14 pages; Accepted to appear in IEEE Transactions on Wireless
Communication
Edge Caching in Dense Heterogeneous Cellular Networks with Massive MIMO Aided Self-backhaul
This paper focuses on edge caching in dense heterogeneous cellular networks
(HetNets), in which small base stations (SBSs) with limited cache size store
the popular contents, and massive multiple-input multiple-output (MIMO) aided
macro base stations provide wireless self-backhaul when SBSs require the
non-cached contents. Our aim is to address the effects of cell load and hit
probability on the successful content delivery (SCD), and present the minimum
required base station density for avoiding the access overload in an arbitrary
small cell and backhaul overload in an arbitrary macrocell. The massive MIMO
backhaul achievable rate without downlink channel estimation is derived to
calculate the backhaul time, and the latency is also evaluated in such
networks. The analytical results confirm that hit probability needs to be
appropriately selected, in order to achieve SCD. The interplay between cache
size and SCD is explicitly quantified. It is theoretically demonstrated that
when non-cached contents are requested, the average delay of the non-cached
content delivery could be comparable to the cached content delivery with the
help of massive MIMO aided self-backhaul, if the average access rate of cached
content delivery is lower than that of self-backhauled content delivery.
Simulation results are presented to validate our analysis.Comment: Accepted to appear in IEEE Transactions on Wireless Communication
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