10,919 research outputs found
Ultra Dense Small Cell Networks: Turning Density into Energy Efficiency
In this paper, a novel approach for joint power control and user scheduling
is proposed for optimizing energy efficiency (EE), in terms of bits per unit
energy, in ultra dense small cell networks (UDNs). Due to severe coupling in
interference, this problem is formulated as a dynamic stochastic game (DSG)
between small cell base stations (SBSs). This game enables to capture the
dynamics of both the queues and channel states of the system. To solve this
game, assuming a large homogeneous UDN deployment, the problem is cast as a
mean-field game (MFG) in which the MFG equilibrium is analyzed with the aid of
low-complexity tractable partial differential equations. Exploiting the
stochastic nature of the problem, user scheduling is formulated as a stochastic
optimization problem and solved using the drift plus penalty (DPP) approach in
the framework of Lyapunov optimization. Remarkably, it is shown that by weaving
notions from Lyapunov optimization and mean-field theory, the proposed solution
yields an equilibrium control policy per SBS which maximizes the network
utility while ensuring users' quality-of-service. Simulation results show that
the proposed approach achieves up to 70.7% gains in EE and 99.5% reductions in
the network's outage probabilities compared to a baseline model which focuses
on improving EE while attempting to satisfy the users' instantaneous
quality-of-service requirements.Comment: 15 pages, 21 figures (sub-figures are counted separately), IEEE
Journal on Selected Areas in Communications - Series on Green Communications
and Networking (Issue 2
Spatial Coordination Strategies in Future Ultra-Dense Wireless Networks
Ultra network densification is considered a major trend in the evolution of
cellular networks, due to its ability to bring the network closer to the user
side and reuse resources to the maximum extent. In this paper we explore
spatial resources coordination as a key empowering technology for next
generation (5G) ultra-dense networks. We propose an optimization framework for
flexibly associating system users with a densely deployed network of access
nodes, opting for the exploitation of densification and the control of overhead
signaling. Combined with spatial precoding processing strategies, we design
network resources management strategies reflecting various features, namely
local vs global channel state information knowledge exploitation, centralized
vs distributed implementation, and non-cooperative vs joint multi-node data
processing. We apply these strategies to future UDN setups, and explore the
impact of critical network parameters, that is, the densification levels of
users and access nodes as well as the power budget constraints, to users
performance. We demonstrate that spatial resources coordination is a key factor
for capitalizing on the gains of ultra dense network deployments.Comment: An extended version of a paper submitted to ISWCS'14, Special Session
on Empowering Technologies of 5G Wireless Communication
Ultra-Dense Networks: Is There a Limit to Spatial Spectrum Reuse?
The aggressive spatial spectrum reuse (SSR) by network densification using
smaller cells has successfully driven the wireless communication industry
onward in the past decades. In our future journey toward ultra-dense networks
(UDNs), a fundamental question needs to be answered. Is there a limit to SSR?
In other words, when we deploy thousands or millions of small cell base
stations (BSs) per square kilometer, is activating all BSs on the same
time/frequency resource the best strategy? In this paper, we present
theoretical analyses to answer such question. In particular, we find that both
the signal and interference powers become bounded in practical UDNs with a
non-zero BS-to-UE antenna height difference and a finite UE density, which
leads to a constant capacity scaling law. As a result, there exists an optimal
SSR density that can maximize the network capacity. Hence, the limit to SSR
should be considered in the operation of future UDNs.Comment: conference submission in Oct. 201
Leveraging intelligence from network CDR data for interference aware energy consumption minimization
Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo
- …