6,207 research outputs found
Autonomous Algorithms for Centralized and Distributed Interference Coordination: A Virtual Layer Based Approach
Interference mitigation techniques are essential for improving the
performance of interference limited wireless networks. In this paper, we
introduce novel interference mitigation schemes for wireless cellular networks
with space division multiple access (SDMA). The schemes are based on a virtual
layer that captures and simplifies the complicated interference situation in
the network and that is used for power control. We show how optimization in
this virtual layer generates gradually adapting power control settings that
lead to autonomous interference minimization. Thereby, the granularity of
control ranges from controlling frequency sub-band power via controlling the
power on a per-beam basis, to a granularity of only enforcing average power
constraints per beam. In conjunction with suitable short-term scheduling, our
algorithms gradually steer the network towards a higher utility. We use
extensive system-level simulations to compare three distributed algorithms and
evaluate their applicability for different user mobility assumptions. In
particular, it turns out that larger gains can be achieved by imposing average
power constraints and allowing opportunistic scheduling instantaneously, rather
than controlling the power in a strict way. Furthermore, we introduce a
centralized algorithm, which directly solves the underlying optimization and
shows fast convergence, as a performance benchmark for the distributed
solutions. Moreover, we investigate the deviation from global optimality by
comparing to a branch-and-bound-based solution.Comment: revised versio
5G Ultra-dense networks with non-uniform Distributed Users
User distribution in ultra-dense networks (UDNs) plays a crucial role in
affecting the performance of UDNs due to the essential coupling between the
traffic and the service provided by the networks. Existing studies are mostly
based on the assumption that users are uniformly distributed in space. The
non-uniform user distribution has not been widely considered despite that it is
much closer to the real scenario. In this paper, Radiation and Absorbing model
(R&A model) is first adopted to analyze the impact of the non-uniformly
distributed users on the performance of 5G UDNs. Based on the R&A model and
queueing network theory, the stationary user density in each hot area is
investigated. Furthermore, the coverage probability, network throughput and
energy efficiency are derived based on the proposed theoretical model. Compared
with the uniformly distributed assumption, it is shown that non-uniform user
distribution has a significant impact on the performance of UDNs.Comment: 14 pages, 10 figure
Enabling Disaster Resilient 4G Mobile Communication Networks
The 4G Long Term Evolution (LTE) is the cellular technology expected to
outperform the previous generations and to some extent revolutionize the
experience of the users by taking advantage of the most advanced radio access
techniques (i.e. OFDMA, SC-FDMA, MIMO). However, the strong dependencies
between user equipments (UEs), base stations (eNBs) and the Evolved Packet Core
(EPC) limit the flexibility, manageability and resiliency in such networks. In
case the communication links between UEs-eNB or eNB-EPC are disrupted, UEs are
in fact unable to communicate. In this article, we reshape the 4G mobile
network to move towards more virtual and distributed architectures for
improving disaster resilience, drastically reducing the dependency between UEs,
eNBs and EPC. The contribution of this work is twofold. We firstly present the
Flexible Management Entity (FME), a distributed entity which leverages on
virtualized EPC functionalities in 4G cellular systems. Second, we introduce a
simple and novel device-todevice (D2D) communication scheme allowing the UEs in
physical proximity to communicate directly without resorting to the
coordination with an eNB.Comment: Submitted to IEEE Communications Magazin
Uplink capacity of a variable density cellular system with multicell processing
In this work we investigate the information theoretic capacity of the uplink of a cellular system. Assuming centralised processing for all base stations, we consider a power-law path loss model along with variable cell size (variable density of Base Stations) and we formulate an average path-loss approximation. Considering a realistic Rician flat fading environment, the analytical result for the per-cell capacity is derived for a large number of users distributed over each cell. We extend this general approach to model the uplink of sectorized cellular system. To this end, we assume that the user terminals are served by perfectly directional receiver antennas, dividing the cell coverage area into perfectly non-interfering sectors. We show how the capacity is increased (due to degrees of freedom gain) in comparison to the single receiving antenna system and we investigate the asymptotic behaviour when the number of sectors grows large. We further extend the analysis to find the capacity when the multiple antennas used for each Base Station are omnidirectional and uncorrelated (power gain on top of degrees of freedom gain). We validate the numerical solutions with Monte Carlo simulations for random fading realizations and we interpret the results for the real-world systems
Echo State Learning for Wireless Virtual Reality Resource Allocation in UAV-enabled LTE-U Networks
In this paper, the problem of resource management is studied for a network of
wireless virtual reality (VR) users communicating using an unmanned aerial
vehicle (UAV)-enabled LTE-U network. In the studied model, the UAVs act as VR
control centers that collect tracking information from the VR users over the
wireless uplink and, then, send the constructed VR images to the VR users over
an LTE-U downlink. Therefore, resource allocation in such a UAV-enabled LTE-U
network must jointly consider the uplink and downlink links over both licensed
and unlicensed bands. In such a VR setting, the UAVs can dynamically adjust the
image quality and format of each VR image to change the data size of each VR
image, then meet the delay requirement. Therefore, resource allocation must
also take into account the image quality and format. This VR-centric resource
allocation problem is formulated as a noncooperative game that enables a joint
allocation of licensed and unlicensed spectrum bands, as well as a dynamic
adaptation of VR image quality and format. To solve this game, a learning
algorithm based on the machine learning tools of echo state networks (ESNs)
with leaky integrator neurons is proposed. Unlike conventional ESN based
learning algorithms that are suitable for discrete-time systems, the proposed
algorithm can dynamically adjust the update speed of the ESN's state and,
hence, it can enable the UAVs to learn the continuous dynamics of their
associated VR users. Simulation results show that the proposed algorithm
achieves up to 14% and 27.1% gains in terms of total VR QoE for all users
compared to Q-learning using LTE-U and Q-learning using LTE
Achieving Ultra-Low Latency in 5G Millimeter Wave Cellular Networks
The IMT 2020 requirements of 20 Gbps peak data rate and 1 millisecond latency
present significant engineering challenges for the design of 5G cellular
systems. Use of the millimeter wave (mmWave) bands above 10 GHz --- where vast
quantities of spectrum are available --- is a promising 5G candidate that may
be able to rise to the occasion.
However, while the mmWave bands can support massive peak data rates,
delivering these data rates on end-to-end service while maintaining reliability
and ultra-low latency performance will require rethinking all layers of the
protocol stack. This papers surveys some of the challenges and possible
solutions for delivering end-to-end, reliable, ultra-low latency services in
mmWave cellular systems in terms of the Medium Access Control (MAC) layer,
congestion control and core network architecture
How user throughput depends on the traffic demand in large cellular networks
Little's law allows to express the mean user throughput in any region of the
network as the ratio of the mean traffic demand to the steady-state mean number
of users in this region. Corresponding statistics are usually collected in
operational networks for each cell. Using ergodic arguments and Palm theoretic
formalism, we show that the global mean user throughput in the network is equal
to the ratio of these two means in the steady state of the "typical cell".
Here, both means account for double averaging: over time and network geometry,
and can be related to the per-surface traffic demand, base-station density and
the spatial distribution of the SINR. This latter accounts for network
irregularities, shadowing and idling cells via cell-load equations. We validate
our approach comparing analytical and simulation results for Poisson network
model to real-network cell-measurements
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