1,706 research outputs found
A New Look at Physical Layer Security, Caching, and Wireless Energy Harvesting for Heterogeneous Ultra-dense Networks
Heterogeneous ultra-dense networks enable ultra-high data rates and ultra-low
latency through the use of dense sub-6 GHz and millimeter wave (mmWave) small
cells with different antenna configurations. Existing work has widely studied
spectral and energy efficiency in such networks and shown that high spectral
and energy efficiency can be achieved. This article investigates the benefits
of heterogeneous ultra-dense network architecture from the perspectives of
three promising technologies, i.e., physical layer security, caching, and
wireless energy harvesting, and provides enthusiastic outlook towards
application of these technologies in heterogeneous ultra-dense networks. Based
on the rationale of each technology, opportunities and challenges are
identified to advance the research in this emerging network.Comment: Accepted to appear in IEEE Communications Magazin
Cost-Effective Cache Deployment in Mobile Heterogeneous Networks
This paper investigates one of the fundamental issues in cache-enabled
heterogeneous networks (HetNets): how many cache instances should be deployed
at different base stations, in order to provide guaranteed service in a
cost-effective manner. Specifically, we consider two-tier HetNets with
hierarchical caching, where the most popular files are cached at small cell
base stations (SBSs) while the less popular ones are cached at macro base
stations (MBSs). For a given network cache deployment budget, the cache sizes
for MBSs and SBSs are optimized to maximize network capacity while satisfying
the file transmission rate requirements. As cache sizes of MBSs and SBSs affect
the traffic load distribution, inter-tier traffic steering is also employed for
load balancing. Based on stochastic geometry analysis, the optimal cache sizes
for MBSs and SBSs are obtained, which are threshold-based with respect to cache
budget in the networks constrained by SBS backhauls. Simulation results are
provided to evaluate the proposed schemes and demonstrate the applications in
cost-effective network deployment
Joint Optimization Framework for Operational Cost Minimization in Green Coverage-Constrained Wireless Networks
In this work, we investigate the joint optimization of base station (BS)
location, its density, and transmit power allocation to minimize the overall
network operational cost required to meet an underlying coverage constraint at
each user equipment (UE), which is randomly deployed following the binomial
point process (BPP). As this joint optimization problem is nonconvex and
combinatorial in nature, we propose a non-trivial solution methodology that
effectively decouples it into three individual optimization problems. Firstly,
by using the distance distribution of the farthest UE from the BS, we present
novel insights on optimal BS location in an optimal sectoring type for a given
number of BSs. After that we provide a tight approximation for the optimal
transmit power allocation to each BS. Lastly, using the latter two results, the
optimal number of BSs that minimize the operational cost is obtained. Also, we
have investigated both circular and square field deployments. Numerical results
validate the analysis and provide practical insights on optimal BS deployment.
We observe that the proposed joint optimization framework, that solves the
coverage probability versus operational cost tradeoff, can yield a significant
reduction of about in the operational cost as compared to the benchmark
fixed allocation scheme.Comment: 30 pages, 15 figures, submitted to IEEE Transactions on Green
Communications and Networkin
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