Context-Aware Radio Resource Management
in HetNets
Nikos Dimitriou, Andreas
Zalonis, Andreas Polydoros*
Institute of Accelerating Systems and
Applications
Athens, Greece
{nikodim | azalonis |
polydoros}@phys.uoa.gr
Adrian Kliks
Oliver Holland
Chair of Wireless Communications
Poznan University of Technology
Poznań, Poland
[email protected]
King’s College London
London, UK
[email protected]
Abstract—In order to address the rapid increase in data-rate
requirements in existing and upcoming wireless communication
systems, one solution is to add more base-stations to achieve
increased spectrum reuse. A Heterogeneous Network (HetNet)—
consisting of a deployment of a variety of different types of small
cells in a cellular infrastructure—is one manifestation of that
approach. In this HetNet case, Radio Resource Management
(RRM) techniques are important to balance and optimize the
radio resource allocation among users of different systems by
avoiding or controlling the generated interference. This paper
provides a concise description of the role of RRM techniques in
HetNets by analyzing the criteria and tradeoffs that are assumed,
and presents a framework for the exploitation of the available
context information within the HetNet environment, that leads to
optimized spectrum usage.
I. INTRODUCTION
In recent years there has been a rapid increase in data-rate
requirements in existing and upcoming wireless communication systems. The approach to address this has been to allocate
more bandwidth. However, the proliferation of applications
that use air interface transmission mediums limits the available
bandwidth in the radio-frequency spectrum, making it a very
scarce and costly resource. Research activities are focusing on
improving the spectral efficiency of wireless communications,
such that higher data rates can be achieved within a given
bandwidth. An alternative approach is to add more antennas
and/or transmitters in order to reduce the distance between the
transmitter and the receiver, or allow for increased reuse of
spectrum.
It is envisioned that future networks will consist of the
composition of various access and core “sub-networks” with
different characteristics and capabilities. These sub-networks
may have different topologies (e.g., star, mesh, hybrid) and
may provide different services (e.g., communication, broadcasting, web-browsing, sensing) and thus may have different
Quality of Service (QoS) and security specifications and they
may as well follow different networking concepts (e.g., address-based, content-based). Additionally, these networks will
include various terminal and intermediate network nodes with
This work has been supported by the “Network of Excellence in Wireless
Communications”, ICT-NEWCOM, http://www.newcom-project.eu, and
partially supported by the “ICT-ACROPOLIS Network of Excellence”,
www.ict-acropolis.eu, and the “Spectrum Overlay through Aggregation of
Heterogeneous Dispersed Bands” project, ICT-SOLDER, www.ict-solder.eu.
*A. Polydoros is also Distinguished Adjunct Professor at King Abdulaziz
University, Saudi Arabia.
different characteristics (mobility patterns, connectivity modes,
processing power, transmission
power, throughput,
reconfigurability options, awareness and cognition capabilities,
etc.).
The Heterogeneous Network (HetNet) concept [1] is a first
step towards that direction. A HetNet can be defined as a network comprised of traditional large macrocells and smaller
cells including microcells, picocells and femtocells. HetNets
can also involve the combination of different types/standards of
wireless systems, such as WiFi and WiMAX, for the application of traffic offloading. In such an environment, legacy network architectures and resource management protocols may
not be suitable to support ubiquitous network requirements,
which may affect the provided QoS to the end user.
RRM plays a key role in network operation, since it regulates the allocation and usage of available resources to the
various users. In Radio Access Networks (RANs), the fundamental resource that is shared among users is represented by
portions of RF spectrum, that are allocated to users or groups of
users according to specific multiple access protocols. Band
sharing by different systems is quite different from band sharing by the users of the same systems, since the former case
involves the co-existence within the same band of networks
that may have different operating protocols, traffic characteristics and service requirements. In order to achieve the coexistence of different systems within the same band and the dynamic sharing of the common resources, new advanced functionalities have to be introduced, to enable the awareness of the environment and to avoid cases in which the same resource is allocated/used in the same time by two different systems, that may
lead to excessive interference and in outage events.
The paper will provide a concise description of the role of
RRM techniques in HetNets by exploiting related context information. First, the role of context information in this environment will be discussed. Then, in section 3, the paper will
present the various issues that are involved in performing RRM
based on the abovementioned rich context information. It will
present the fundamental characteristics of RRM either within a
single system or within a heterogeneous system environment.
Finally, in section 4 some specific examples of context-aware
RRM schemes will be presented demonstrating the abovementioned approach and highlighting the benefits in those specific
cases.
II. CONTEXT INFORMATION
Based on [2] context information can be defined as the information possessed by an entity that can be used to describe
and characterize the current situation of this entity (element of
the network). Depending on the entity type (e.g., mobile or
fixed node/antenna) the useful and available context information changes significantly. For instance some information
accessible in cellular networks cannot be obtained in WiFi
systems. Furthermore, the quality of the context information
may vary. Inaccurate or outdated collected information may
result in wrong characterization of the current network situation.
In the HetNet environment, context information may be
collected by direct local sensing/measurements performed by
the terminals and the network access points or it may be based
on information exchanged between these network elements
that may also be gathered in specific databases for joint use.
This context information may include the following:
• Measurements of the received signal strength, or the
SINR for specific frequency slots, possibly augmented
by information regarding the direction of the emitting
signal source.
• The capabilities of the systems covering the area, such as
maximum offered throughput, minimum QoS and supported services.
• The bandwidth availability and access rules (e.g., primary/secondary access, licensed/unlicensed bands, contention based/contention-less access etc.)
• The actual radio access network types co-existing within
the geographical area and the supported air interfaces and
transmission modes (e.g., GPRS, 3G, 4G, etc.)
• A list of the operators offering the aforementioned radio
access networks, along with information regarding their
cost and offers for the services they provide.
• The current traffic load per cell for each of the coexisting operators within the area.
In order to efficiently store, update and exploit all this information the use of specific databases has been considered,
that can be accessed by the network elements and used by the
RRM algorithms. The Radio Environment Map (REM) has
been envisaged as an integrated information structure that
consists of various types of information or metrics such as
geolocation data, available services, spectral usage regulations, locations and activities of radio nodes, user and service
policies and past experience [3]. The REM is supposed to
include all the necessary information regarding the (location
dependent) radio characteristics of a geographical area. A
REM may have a wide scope covering a whole city or prefecture area (global REM), or it may only be confined within a
radius of few meters around a receiving terminal node (local
REM). It can be stated that these two different kinds of REMs
may provide different views; the local REM may include information that is related to real-time measurements that may
have a quick update rate, characterizing the short-term dynamics of the observed radio environment (that may be dominated
by fast fading effects in both frequency and time domains). It
is also conceivable that the local REM may have a finer spatial
granularity than the global REM. On the other extreme, the
global REM is expected to integrate the views of the local
REMs within the area of interest, averaging the reported
measurements over time and space, in order to provide a
broader long-term view of the area radio environment. The
global REM may also incorporate elements of networkspecific context information (e.g., operator services & capabilities) that are directly provided by the operators themselves by
information servers that collect and integrate this context information (e.g., an IEEE 802.21 Media Independent Information Server).
III. RRM IN HETNETS
RRM encompasses all the functionalities that control of the
communication link parameters of the users sharing the same
transmission medium (cable or wireless). These parameters are
related to the QoS requirements of each link (e.g., BER, PER,
SINR target etc.), the transmission/reception capabilities of
each mobile/base transceiver (e.g., maximum transmitted
power, receiver noise figure, transmit/receive antenna gains
etc.), the transmission medium characteristics (e.g., slow/fast
fading parameters, power loss exponent etc.) and the multiple
access scheme specific mechanisms (e.g., time/frequency slot
duration, scheduling schemes etc.). The abovementioned parameters dictate the percentage of the available capacity that
each user link requires and they reflect the actual contribution
of each connection to the system load.
The following procedures can be considered to be parts of
RRM: Call Admission Control, Packet Scheduling, Congestion Control, Mobility Management, Power Control, Rate
Adaptation, Frequency Planning, Interference Management
etc. In all cases the objective is to manage the available radio
resources efficiently, taking into account conditions and constraints related to different OSI layers, such as transmitted
power and received signal strength on the physical layer,
frame/packet scheduling and time slots organization (MAC
layer), QoS and QoE requirements (upper layers) etc. The
definition of a resource varies according to its reference viewpoint. From the mobile node/user’s point of view, the resources correspond to the QoS requirements. Voice, video or
data services have specific throughput and bit error rate requirements, which can be translated into specific received
signal strength and signal to noise-plus-interference requirements. These individual user requirements are reflected on the
transmitted power requirements for each frequency/time slot
used by the base station or the access point. These in turn are
translated into specific spectrum usage requirements for the
respective coverage area by the operator.
The abovementioned context information offer opportunities for more efficient allocation of the available radio resources among the users within a composite wireless network.
The challenge that lies ahead is related to the actual exploitation of the context data (e.g., related to PHY measurements,
power profiles, topological data, RAN lists, directional spectrum sensing data, measured interference etc.) for the development of RRM algorithms (either extending some of those
previously analyzed or proposing new schemes). These
schemes may be dealing with both intra-layer and cross-layer
parameters’ selection, and will account for a balance between
power and bandwidth efficiency. The metrics for assessing
those schemes have to be related to both the performance
enhancements that they will provide (in terms of user and
system throughput efficiency and capacity utilization) and the
actual complexity that they will require (in terms of signalling
overhead, storage needs etc). In any case RRM decisions are
based on network- and user-specific information, which assists
in identifying the suitable (according to specific criteria)
amount of resources that should be allocated to each user.
A.
Legacy intra-System scenarios
In legacy cellular systems such as GSM, GPRS/EDGE,
CDMA, HSDPA, HSUPA the resource allocation and planning among the different cells and among the users of the
same cells is such that the communication links within any
area are orthogonal (either by different frequency carriers,
different timeslots of the same frequency carrier, or different
spreading codes). In the 3GPP LTE and IEEE 802.16 standards, that consider subcarriers allocated on a TDMA or FDMA
basis, the aim is full frequency reuse between the cells by also
controlling and minimizing the effects of the co-channel interference. In this case the resource management is based on
some parameters that are fed back from the user to the basestation. Usually these parameters are related to measurements
of the received signal strength or the SINR on specific frequencies that may assist in determining the propagation channel losses and variations between the base station and the
mobile. Apart from assessing the link quality between the
base-station and the mobile, it is important to assess the interference that may be generated by other co-channel links (e.g.,
neighboring cell connections reusing the same frequency) and
to also estimate the expected consequences to the other users
after allocating a specific resource to the user of interest (e.g.,
generated interference to the other active co-channel links).
Full frequency re-use enables the full exploitation of the available spectrum throughout the wireless network and – if combined with proper interference mitigation/avoidance schemes –
it may lead to the optimum spectral and usage efficiency of
resources.
The main characteristics and limitations of the traditional
RRM approaches are summarized below:
• The cellular infrastructure is considered as fixed and the
amount of resources allocated in each cell does not
change in short term.
• The user feeds back only channel and signal quality metrics and not any location information.
• The user does not sense explicitly other systems that may
exist in other frequency bands.
• The baseline configuration of the cellular systems does
not involve the cooperation between base stations for optimized resource usage.
• There is no provision for opportunistic resource access or
for primary/secondary prioritization of users in resource
allocation
B.
Inter-System, joint RRM scenarios
As discussed above, the evolution of networks has led to
the formation of an environment in which different access and
core networks coexist (HetNets). Currently, each user is bound
to use one or a subset of these networks, since most often the
user is a subscriber to a specific operator and is allowed to
roam among the access networks that are owned by this specific operator or are covered by service level agreements with
other operators. Additionally, the user may connect to other
low range access networks in unlicenced bands (such as
WiFi). Thus, the opportunity to offload part of the traffic to
WiFi network has become an attractive option for cellular
operators. The so-called Integrated Femto-WiFi (IFW) networks have been recently proposed for installation in residential buildings, in enterprise premises as well as in metro stations [4]. Other opportunities for cellular traffic offloading
include the use of available TV Wight Space (TVWS) spectrum. In those scenarios, where two or more systems can have
access to the same band, or the user can be assigned resources
from various Radio Access Networks (RANs), the role of
context-aware RRM becomes very important.
Two or more RANs may share the same spectrum band either by dynamically dividing among themselves different parts
of it, or by opportunistically accessing unused channels over
the whole common band. In these cases, there are some specific pre-defined priorities and policies that are followed. For
example, the users of a specific network may be considered as
‘primary’ users (having the right for exclusive channel usage)
and the rest of the users from other networks may be characterized as ‘secondary’, having the obligation to release the
resources that a ‘primary’ user may require. Between users of
different networks the signals accessing the same frequency
channel may be overlaid (allowing only concurrent transmissions), underlaid (allowing simultaneous transmissions) or
interweaved (allowing exclusive transmission to primary users). The terminals may be able to sense all or part of the accessible network elements (access points and terminals). Terminal context awareness may be extended to the identification
of nearby available radio access networks. They may also have
the capability to exchange control information and data (related to ‘peer to peer’ communication capabilities that can be
used in an ad-hoc manner).
In heterogeneous access networks, belonging to the same
or different operators, the following hierarchical view may be
considered. From the operator’s point of view, the level of
resource usage is directly connected to the actual turnover that
is achieved by utilizing the operator’s owned or leased spectrum within the operator’s RANs. The operator may formulate
policies aiming at the optimization of the spectrum usage and
the consequent maximization of the profits coming from individual customer contracts, package deals, offers etc. The operator may also perform long-term coverage measurements to
verify the penetration and the quality of the services that it
provides to its customers. These measurements may be used
for the reconfiguration of the operator’s RANs to match the
network coverage characteristics to the customer requirements
and services demands. These coverage characteristics drive the
specifications of the RAN infrastructure (e.g., transmitted
power of base stations) and the links’ maximum achievable
throughput. The RANs themselves may perform more frequent
measurements to monitor the wireless access load (linked to
the number of users per cell and the actual services distributed
per cell) and based on the actual measured load levels they
may invoke different radio resource management algorithms
to satisfy the traffic demands and to balance the tradeoff between performance and fairness among the users sharing the
same resources in each cell. Finally, the lower level of the
described hierarchy corresponds to the users. The user terminals have varying capabilities in terms of the applications that
they can run/download, the services that they can provide and
the Quality of Service that they may require. Additionally, the
users may have different preferences regarding the usage of
different available networks, depending on their offered se
services and other factors such as cost. In terms of measurements,
the terminals may be capable of performing short term mon
monitoring of the received signal level, the SINR, the battery level
the terminal coordinates and the user’s speed which may all be
used for efficient resource allocation.
Package Deals
Spectrum usage policies
Coverage Studies
Network
Operators
Managing Entities
RAN specifications
Figure 3 depicts the areas of feasible power allocation for
users controlled by the APss B and C when a user controlled by
AP A is located in a specific point. These areas correspond to
three different tests. In each test the users were assumed to
have
ave the same SINR requirement, which was set equal to 4, 8
and 12 dB. It is evident that as the required SINR increases,
the corresponding required transmitted power for each user
increases and so does the generated co
co-channel interference
between the neighboring
hboring cells. As a consequence, the areas of
feasible power allocation in the B and C cells tend to shrink
and the required SINR increases. The same effect would be
observed if the user of cell A moved closer to the cell border,
towards cells B and C.
Network Load Measurements
RRM Algorithms
Radio Access
Networks
Terminal capabilities
Required QoS
Information Collection &
Processing
Policy formulation,
Dissemination & enforcement
RRM algorithms execution
User Preferences
Signal Measurements
User Location / Mobility
users
Battery level
hetFigure 1: Hierarchical view of the joint RRM among he
erogeneous networks.
Figure 2: Co-channel single-tier
single
allocation scenario
Therefore, within a HetNet we may envisage a multilevel
hierarchy of network entities (Figure 1) that may retrieve,
possess and store different kinds of information and measur
measurements, they may initiate, disseminate or execute various ne
network policies and they may also employ different radio rresource management algorithms. For such a complex network
of networks to operate efficiently, it is necessary to introduce
managing entities that will
ill monitor the different operator ne
networks and will regulate their operation, allowing for distribu
distributed decision making.
IV. EXAMPLES OF CONTEXT-AWARE RRM IN HETNETS
SCENARIOS
Herein, three specific examples of context
context-aware resource
allocation strategies proposed
oposed in the literature,
literature in three different scenarios encountered in the HetNet concept
concept, are presented. In each, the context information used is identified and
categorized based on the hierarchical framework of the various
network entities.
A.
Co-channel single-tier allocation
This scenario may be viewed both as intra system (one o
operator) or inter-system
system (multiple operators with common aaccess to the Managing entity). Thee goal is to examine the possibility of re-using
using the same frequency channels for different
users and the corresponding consequences of the generated co
cochannel interference. In [5] it was demonstrated for the case of
three co-channel APs (Figure 2)) in the same area, that the use
of context information can be exploited in order to determine
the options of feasible power allocation for each user by a
central managing entity according to the terminal QoS rrequirements and location details.
Figure 3:: Identification of areas of co-channel
co
use in cells B
and C for SINR thresholds equal to 4,8,12 dB.
In this case the context elements used are related to the location and the QoS requirements of all users,
users which are combined with the use of propagation models for all the possible
user links. The context information exploited in this scenario
is summarized in the following table. All this information can
be stored in a REM and accessed
acce
and used by a managing
entity which is located in the core network
network.
TABLE I.
CO-CHANNEL SINGLE-TIER SCENARIO
Operators
Context
information
used
Spectrum
bands, QoS
provision, APs
locations
RANs
QoS, SINR
requirements,
UE locations,
area propagation models
Users
UE locations
victim macro-user is 31% while by using the above-mentioned
context information the outage drops to 22%.
Macrocell User Outage
B.
Co-channel two-tier allocation
One of the most challenging interference scenarios in twotwo
tier networks is the interference caused by a small cell (e.g.
femtocell) to a nearby macrocell user in the case of shared
spectrum and closed access small cell (Figure
Figure 4).
4
45%
full context knowledge
40%
baseline
35%
30%
25%
20%
15%
10%
5%
0%
0,2
0,3
0,4
0,5
0,6
0,7
Distance from macro BS (km)
0,8
0,9
Figure 5: Macro-user
user Outage in various distances from the
macrocell
Figure 4: Co-channel two-tier allocation scenario
In [6] a power control mechanism was proposed that eexploit environmental and other available context knowledge. In
this example, the femto-AP
AP has access to a REM (which may
reside in the AP or in the core network) and use the collected
information autonomously, without a centralized control.
Thus, in this case the managing entity lies within the AP. The
control mechanism is based on an approach proposed in [7].
The femtocell detects a neighboring victim macro-user and
reduces its transmission power aiming to maintain
maintai a predefined SINR target for the macro-user.. In case the target cannot
be achieved, the femtocell transmits at a predefined minimum
power level.
It is clear in the above approach that the context inforinfo
mation needed exceeds the information collected from the
Channel State Information (CSI) in the femto-AP. The enhanced context information includes the macrocell and
femtocell locations, the victim macro-user
user detection and location, and the channel gains between
etween these network elements
elements.
TABLE II.
CO-CHANNEL TWO-TIER SCENARIO
Operators
Context
information
used
Spectrum
bands, QoS
provision,
Macro BS
location
RANs
Femto-AP
location, Macro
acro
UE detection,,
area propagation models,
building characchara
teristics
C.
Channel allocation in inter-system scenario (two-tier
cellular with WiFi offloading)
In [8] the scenario of an Integrated Femto
Femto-WiFi Network
in a cellular environment
nment was investigated (Figure 6).
6 The
paper tackles the problem of resource-efficient
resource
traffic management through the application
ication of the WiFi offloading conco
cept in cellular networks. As it is illustrated in the figure, both
small cells, i.e. WiFi spot or LTE femtocell, are connected to
the core network via stable DSL backhaul. Thus from the
operator viewpoint, access to both entities will be ensured
through IP network. On the other hand, as femtocells utilize
operator’s frequency bands, the WiFi Access Points operates
in one of the ISM frequency regions. As a consequence the
later are susceptible to high interference coming from
fr
other
WiFi links in the vicinity, and operator has rather limited conco
trol of that phenomena. Nevertheless, the possibility of traffic
offloading seems to be beneficial for network operator, since
the amount of multimedia data transferred via the cellular
cellula
networks grown particularly fast. Shifting portion of the traffic
to the public WiFi networks will result in rarer cellular network congestion or will allow for controlled switching
switching-off of
unused base-stations
stations reducing the overall power consumption.
Users
Macro UE
location
It was shown in [6] that the use of enhanced context info
information significantly reduce the macro-user
user outage percentage,
with respect to the case where no such info was available
(baseline algorithm of [7]). In Figure 6 the average macro-user
macro
outage is presented for various macro-to--femto-cell distances
based on the OFDMA Interference Scenario Evaluation Methodology for LTE femtocells for the suburban case [7]. The
macro-user SINR target was set to 3 dB. The benefit of using
context-aware power control can be clearly observed. For
example with a co-channel femtocell deployed at a distance of
500 m from the macrocell,, the average outage of a nearby
Figure 6: Two-tier/WiFi
tier/WiFi offloading allocation scenario
In [8] it was shown that even significant amount of traffic
can be under some circumstances offloaded from the regular
to WiFi networks, thus providing relevant gains to the operaoper
tor. However, the benefits from such an approach will be
higher when rich context information
nformation will be exchanged beb
tween the particular entities of that heterogeneous network.
First, the WiFi offloading scenario is
is, in some sense, an exten-
sion of the case presented in previous subsection, i.e. cochannel two-tier channel allocation. It is due to the fact that
the mobile terminal could be served either by femto-AP or by
the macrocell base station. Thus, most of the entries presented
in the second table TABLE II. should be applied here as well.
However here other possibilities appear, the managing entity
can allow the user to: (i) connect to femto access point and
offload e.g. mobile data thorough the WiFi AP, (ii) connect to
the femto-AP and then switch to unlicensed networks due to
the user’s mobility and lack of the signal coverage in its new
location, (iii) connect to the WiFi network in a case when the
regular system is not accessible.
In all cases some specific context data should be known,
such as precise location of the WiFi access points, its IP address and number of users operating in the assigned channels,
the number of interfering access points, number of users per
each WiFi channel, daily traffic statistics on each channel etc.
These are summarized in Table III.
The benefits of the possessing of rich context information,
listed in Table III, has been illustrated in Fig. 7 as a traffic
distribution among macro base stations, femto or WiFi access
points. In that scenario the dual-strip model of the three-floor
building has been applied. It was assumed that there are 50
inside users and 20 outside uses which can be served by either
one of two available macro base station, femto access point or
WiFi hot spot. The goal was to check how much traffic could
be offloaded from macrocells to smaller cells resulting in
lower utilization of macro base station allowing for application
of e.g. intelligent switching-off mechanism of lowly occupied
base stations. As it can be seen that under some predefined
assumptions (e.g. interference limits in WiFi networks, number of access points etc.) around 80% of the traffic can be
shifted from macro base stations to femto access points. In
consequence the unused macro base stations could be switched
off leading to some energy and financial benefits.
TABLE III.
WIFI OFFLOADING SCHEME
(LIST OF CONTEXT DATA BESIDE ELEMENTS SHOWN IN TABLE II)
Operators
Context
information
used
Distribution of the served traffic
[2]
[3]
0.6
[4]
[5]
0.2
15
10
FAP
5
WiFiAP
Number of FAPs
[6]
0
[7]
Figure 7: Exemplary traffic distribution among macro
base station, femto and WiFi access points
Users
WiFi UE
location, number of connected user, reliability and stability
of the connection, movement
speed and
direction, types
of the supported
technologies
REFERENCES
0.8
0
MacroBS
RANs
WiFi-AP location, frequency
band and technology, WiFi
channel availability and
average occupation, WiFi
coverage area,
possibility of
(vertical) handover,
propagation
models and
building characteristics, daily
traffic characteristic, current
number of
connected users
V. CONCLUSIONS
The paper presents the main principles and issues involved
in RRM for HetNets scenarios. RRM techniques are important
to balance and optimize the radio resource usage among users
of different systems sharing the same frequency band, by regulating the generation of co-channel interference. The focus in
this paper has been on the concepts of context awareness, and
proposed a framework for the RRM algorithms to exploit that
information. The proposed framework has been demonstrated
and discussed in specific examples in three different HetNet
scenarios.
[1]
0.4
Operator WiFi
access point
location (if
applicable),
supported
technology
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