1,226 research outputs found
A robust machine learning method for cell-load approximation in wireless networks
We propose a learning algorithm for cell-load approximation in wireless
networks. The proposed algorithm is robust in the sense that it is designed to
cope with the uncertainty arising from a small number of training samples. This
scenario is highly relevant in wireless networks where training has to be
performed on short time scales because of a fast time-varying communication
environment. The first part of this work studies the set of feasible rates and
shows that this set is compact. We then prove that the mapping relating a
feasible rate vector to the unique fixed point of the non-linear cell-load
mapping is monotone and uniformly continuous. Utilizing these properties, we
apply an approximation framework that achieves the best worst-case performance.
Furthermore, the approximation preserves the monotonicity and continuity
properties. Simulations show that the proposed method exhibits better
robustness and accuracy for small training sets in comparison with standard
approximation techniques for multivariate data.Comment: Shorter version accepted at ICASSP 201
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Traffic-Driven Spectrum Allocation in Heterogeneous Networks
Next generation cellular networks will be heterogeneous with dense deployment
of small cells in order to deliver high data rate per unit area. Traffic
variations are more pronounced in a small cell, which in turn lead to more
dynamic interference to other cells. It is crucial to adapt radio resource
management to traffic conditions in such a heterogeneous network (HetNet). This
paper studies the optimization of spectrum allocation in HetNets on a
relatively slow timescale based on average traffic and channel conditions
(typically over seconds or minutes). Specifically, in a cluster with base
transceiver stations (BTSs), the optimal partition of the spectrum into
segments is determined, corresponding to all possible spectrum reuse patterns
in the downlink. Each BTS's traffic is modeled using a queue with Poisson
arrivals, the service rate of which is a linear function of the combined
bandwidth of all assigned spectrum segments. With the system average packet
sojourn time as the objective, a convex optimization problem is first
formulated, where it is shown that the optimal allocation divides the spectrum
into at most segments. A second, refined model is then proposed to address
queue interactions due to interference, where the corresponding optimal
allocation problem admits an efficient suboptimal solution. Both allocation
schemes attain the entire throughput region of a given network. Simulation
results show the two schemes perform similarly in the heavy-traffic regime, in
which case they significantly outperform both the orthogonal allocation and the
full-frequency-reuse allocation. The refined allocation shows the best
performance under all traffic conditions.Comment: 13 pages, 11 figures, accepted for publication by JSAC-HC
Traffic Driven Resource Allocation in Heterogenous Wireless Networks
Most work on wireless network resource allocation use physical layer
performance such as sum rate and outage probability as the figure of merit.
These metrics may not reflect the true user QoS in future heterogenous networks
(HetNets) with many small cells, due to large traffic variations in overlapping
cells with complicated interference conditions. This paper studies the spectrum
allocation problem in HetNets using the average packet sojourn time as the
performance metric. To be specific, in a HetNet with base terminal stations
(BTS's), we determine the optimal partition of the spectrum into possible
spectrum sharing combinations. We use an interactive queueing model to
characterize the flow level performance, where the service rates are decided by
the spectrum partition. The spectrum allocation problem is formulated using a
conservative approximation, which makes the optimization problem convex. We
prove that in the optimal solution the spectrum is divided into at most
pieces. A numerical algorithm is provided to solve the spectrum allocation
problem on a slow timescale with aggregate traffic and service information.
Simulation results show that the proposed solution achieves significant gains
compared to both orthogonal and full spectrum reuse allocations with moderate
to heavy traffic.Comment: 6 pages, 5 figures IEEE GLOBECOM 2014 (accepted for publication
The role of asymptotic functions in network optimization and feasibility studies
Solutions to network optimization problems have greatly benefited from
developments in nonlinear analysis, and, in particular, from developments in
convex optimization. A key concept that has made convex and nonconvex analysis
an important tool in science and engineering is the notion of asymptotic
function, which is often hidden in many influential studies on nonlinear
analysis and related fields. Therefore, we can also expect that asymptotic
functions are deeply connected to many results in the wireless domain, even
though they are rarely mentioned in the wireless literature. In this study, we
show connections of this type. By doing so, we explain many properties of
centralized and distributed solutions to wireless resource allocation problems
within a unified framework, and we also generalize and unify existing
approaches to feasibility analysis of network designs. In particular, we show
sufficient and necessary conditions for mappings widely used in wireless
communication problems (more precisely, the class of standard interference
mappings) to have a fixed point. Furthermore, we derive fundamental bounds on
the utility and the energy efficiency that can be achieved by solving a large
family of max-min utility optimization problems in wireless networks.Comment: GlobalSIP 2017 (to appear
A survey of self organisation in future cellular networks
This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks
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