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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012 497
Femtocells: Past, Present, and Future
Jeffrey G. Andrews, Holger Claussen, Mischa Dohler, Sundeep Rangan, Mark C. Reed
Abstract—Femtocells, despite their name, pose a potentially
large disruption to the carefully planned cellular networks that
now connect a majority of the planet’s citizens to the Internet
and with each other. Femtocells – which by the end of 2010
already outnumbered traditional base stations and at the time
of publication are being deployed at a rate of about five million
a year – both enhance and interfere with this network in ways
that are not yet well understood. Will femtocells be crucial for
offloading data and video from the creaking traditional network?
Or will femtocells prove more trouble than they are worth,
undermining decades of careful base station deployment with
unpredictable interference while delivering only limited gains?
Or possibly neither: are femtocells just a “flash in the pan”; an
exciting but short-lived stage of network evolution that will be
rendered obsolete by improved WiFi offloading, new backhaul
regulations and/or pricing, or other unforeseen technological
developments? This tutorial article overviews the history of
femtocells, demystifies their key aspects, and provides a preview
of the next few years, which the authors believe will see a rapid
acceleration towards small cell technology. In the course of the
article, we also position and introduce the articles that headline
this special issue.
Index Terms—Femtocells, Heterogeneous Networks, Cellular
Networks, 3GPP.
I. INTRODUCTION
THE TOPOLOGY and architecture of cellular networks
are undergoing a major paradigm shift from voice-
centric, circuit switched and centrally optimized for cov-
erage towards data-centric, packet switched and organically
deployed for capacity. The principle drivers for this shift are
intense consumer demand for mobile data that has exceeded
even the most aggressive predictions of five years ago; en-
abling features of the newer wireless standards, in particular
LTE; and relentless hardware and software integration that
has enabled the entire functionality of a base station to be
miniaturized. For example, in 2010 the amount of global
mobile data traffic nearly tripled for the third year in a row,
and exceeded the traffic on the entire global Internet in 2000
[1]. By 2015, nearly 1 billion people are expected to access the
Internet exclusively through a mobile wireless device [1]. It is
obvious that the traditional cellular network, which is already
at the point of failure in many important markets, cannot
Manuscript received 26 September 2011; revised 9 December 2011. As this
article was authored by the guest editors, David Lee handled the reviews.
J. Andrews is with the University of Texas at Austin (e-mail: jan-
drews@ece.utexas.edu).
H. Claussen is with Bell Labs, Alcatel-Lucent (e-mail: holger.claussen
@alcatel-lucent.com).
M. Dohler is with CTTC (e-mail: mischa.dohler@cttc.es).
S. Rangan is with Polytechnic Institute of New York University (e-mail:
srangan@poly.edu).
M.C. Reed is with the Australian National University (e-mail:
mark.reed@anu.edu.au).
Digital Object Identifier 10.1109/JSAC.2012.120401.
Fig. 1. Traffic demand for North America [2]
keep pace with this data explosion through the expensive
and incremental methods of the past: namely increasing the
amount of spectrum or by deploying more macro base stations.
This rapid increase in mobile data activity has raised the
stakes on developing innovative new technologies and cellular
topologies that can meet these demands in an energy efficient
manner. The importance of this is highlighted in Fig. 1 where
the projected increase in network traffic and its contributing
components for North America from 2007 to 2020 is shown
[2]. The point reinforced by this figure is that trafficisset
to grow exponentially over many years with wireless data
increasing the most rapidly.
One of most interesting trends to emerge from this cellular
(r)evolution are femtocells [3], [4]. Femtocells are small, inex-
pensive, low-power base stations that are generally consumer-
deployed and connected to their own wired backhaul connec-
tion. In these respects, they resemble WiFi access points, but
instead they utilize one or more commercial cellular standards
and licensed spectrum. To a mobile station (MS), a femtocell
appears indistinguishable from a traditional base station, as
they have all the usual overhead channels and are capable
of in-band handoffs. Originally envisioned as a means to
provide better voice coverage in the home – many subscribers
cite poor signal quality in their house when switching to a
different service provider – they are now primarily viewed
as a cost-effective means of offloading data traffic from the
macrocell network. By the start of 2011, an estimated 2.3
million femtocells were already deployed globally, and this is
expected to reach nearly 50 million by 2014 [5]. Femtocells,
along with WiFi offloading, are expected to carry over 60%
of all global data traffic by 2015 [6].
To make sense of this new network paradigm, we sur-
vey the history of small cell technology (Section II) and
provide a broad technical, prototcol and business taxonomy
0733-8716/12/$25.00 c
2012 IEEE
498 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012
for femtocells (Section III). Then, we overview plausible
engineering and mathematical models for femtocell-overlaid
cellular systems (Section IV). Adding this much unplanned in-
band infrastructure to the network raises many questions and
introduces many interesting technical, business, and regulatory
challenges. We conclude by discussing all three sets of chal-
lenges (see Section V), focusing on the technical challenges,
which span multiple fields: modeling and analysis, commu-
nication and information theory, network protocol design,
distributed optimization, and implementation. In the course
of the article, we provide a broad and detailed review of the
literature, highlighting the contributions that accompany this
overview article in this first IEEE special issue on femtocells.
II. A BRIEF HISTORY OF FEMTOCELLS
A. Early Origins
The idea of small cells has been around for nearly 3 decades
[7]. Initially, “small cells” was a term used to describe the cell
size in a metropolitan area, where a macrocell (on the order
of kilometers in diameter) would be cell split into a number
of smaller cells with reduced transmit power, known today as
metropolitan macrocells or microcells, and having a radius of
perhaps several hundred meters.
Simultaneously, cellular repeaters or “boosters” were being
investigated [8], [9] as an alternative to small base stations.
These re-radiating devices were intended to help improve the
signal quality in poor coverage regions, while reducing costs
by not requiring a wireline backhaul. However, their reuse
of the licensed spectrum for backhaul limited the achievable
throughput, and hence these repeaters were neither helpful to
the system capacity nor simple to deploy.
In the 1990s, a precursor to cellular picocells began to
appear [10] with cell sizes ranging from tens to about one
hundred meters. These “traditional” small cells were used
for capacity and coverage infill, i.e. where macro penetration
was insufficient to provide a reliable connection or where
the macrocell was overloaded. These types of small cells
were essentially a smaller version of the macro base station,
and required comparable planning, management and network
interfaces. More similar to the current femtocell concept was
a little known industry project in the early 1990s led by
Southwest Bell and Panasonic to develop an indoor femtocell-
like solution that re-used the same spectrum as the macrocells
[11] and used wired backhaul (T1 or PSTN). However, there
was a lack at this time of ubiquitous IP backhaul, and the
level of integration had not yet achieved the critical point
where a base station could be truly miniaturized. Like the other
small cell technologies just mentioned, they were technically
a step forward but economically unsuccessful, because the
cost of deploying and operating a large number of small cells
outweighed the advantage they provided.
B. The Birth of Modern Femtocells
New thinking on the deployment and configuration of cellu-
lar systems began to address the operational and cost aspects
of small cell deployment [12], [13]. These ideas have been
applied successfully to residential femtocells where cost issues
are amplified. A femtocell is fundamentally different from the
traditional small cells in their need to be more autonomous
and self-adaptive. Additionally, the backhaul interface back to
the cellular network – which is IP-based and likely supports
a lower rate and higher latency than the standard X2 inter-
face connecting macro and picocells – mandates the use of
femtocell gateways and other new network infrastructure to
appropriately route and serve the traffic to and from what will
soon be millions of new base stations.
Perhaps more important than the need to provide cellular
coverage infill for residential use, the mobile data explosion
discussed in the Section I has mandated the need for a new
cellular architecture with at least an order of magnitude more
capacity [14]. The most viable way to meet this demand is
to reduce the cell size and thereby the spatial frequency re-
use [15], unless the plentiful (and inexpensive) frequencies in
the tens of GHz can be harnessed for mobile broadband, which
is extremely challenging [16]. In parallel to the escalating data
demands, several technological and societal trends have made
low-cost femtocells viable. These include the wide availability
and low cost of wired broadband internet connections; the
development of 4G cellular standards that are OFDMA and
IP-based and provide a better platform for femtocell overlays
than 3G CDMA (near-far problem) networks that are circuit
switched (the femtocell backhaul is inherently IP); and relent-
less hardware and software integration has made it foreseeable
to have a fully functional low power base station in the $100
price point range.
Small cells have recently become a hot topic for research
as evidenced by a significant increase in publications in this
area, and small cell technology has advanced a great deal from
the simple cell splitting ideas presented in [7]. For example,
the number of publications including femtocell or femtocells
in the topic registered in the IEEE data base have increased
from 3 in 2007 to 10 (2008), 51 (2009), 116 (2010), and
continues to accelerate. In addition, the European Union has
started funding research on femtocells, for example the ICT-4-
248523 BeFEMTO project, which focuses on the analysis and
development of LTE/LTE-A compliant femtocell technologies
[17]. Today, advanced auto-configuration and self-optimization
capability has enabled small cells to be deployed by the
end-user in a plug-and-play manner, and they are able to
automatically integrate themselves into existing macrocellular
networks. This was a key step to enable large scale deploy-
ments of small cells.
As a result we have now seen successful commercial
femtocell deployments. In the US, Sprint Nextel started their
nationwide femtocell offering in 2008, with Verizon and
AT&T following suit in 2009 and 2010, respectively. In
Europe, Vodafone started their first femto deployment in 2009
in the UK, and subsequently other countries. In Asia, Softbank
mobile, China Unicom, and NTT DoCoMo launched their
femtocell services in 2009. According to the Femto Forum,
operator deployments grew by 60% in the second quarter
of 2011 to 31, including eight of the top 10 global mobile
operator groups.
C. Modern Femtocell Research
There is a growing body of research on femtocells, of
which we briefly summarize some notable early results here.
ANDREWS et al.: FEMTOCELLS: PAST, PRESENT, AND FUTURE 499
Early simulation results for femtocells were presented by H.
Claussen and co-authors at Bell Labs (UK) [18]–[20], which
were extended to self-optimization strategies and multiple
antennas shortly afterward [21], [22]. On the academic side,
early work included new mathematical models and analysis by
Chandrasekhar and Andrews, specifically looking at the uplink
interference problem in CDMA-based networks with closed
access [23], [24]. This model and approach was adapted to the
downlink and with multiple antennas in [25]. Other early work
from UCLA suggested adaptive access control to mitigate the
cross-tier interference problem [26], which was given further
attention in [27], [28].
Das and Ramaswamy in [29], [30], investigated the re-
verse link (RL) capacity of femtocells, modeling inter-cell
interference as a Gaussian random variable. As discussed in
Section IV, such a model is probably not accurate for cellular
systems with femtocells. In [31] the authors investigated user-
assisted approaches to interference optimization, while in [32]
the authors presented interference management techniques for
both downlink and uplink of femtocells operating based on
high speed packet access (HSPA); this work was extended in
[33], which developed new analytical techniques to improve
the optimization for WCDMA femtocell systems.
Several papers have also considered interference coordina-
tion in OFDMA based networks, including co-channel inter-
ference [34], interference management [35], and interference
avoidance strategies [36]. Mobility management and access
control for femtocells was discussed in [37]–[39] where access
control can be viewed as an effective form of interference
avoidance.
Built on these past contributions, technologies have emerged
over time, the governing standards of which are discussed
subsequently.
III. FEMTOCELL STANDARDIZATION
From a technology point of view, a femtocell is not only
characterized by short communication range and high through-
put, but also by its ability to seamlessly interact with the
traditional cellular network at all layers of the network stack,
performing tasks like handoffs (HOs), interference manage-
ment, billing, and authentication. This necessitates substantial
support by the appropriate standards bodies.
The governing body with arguably most impact onto stan-
dardization bodies is the Femto Forum. It is a not-for-profit
membership organization founded in 2007 to enable and
promote femtocells and femto technology worldwide. Today,
it counts on more than 70 providers of femtocell technology,
including mobile operators, telecommunication hardware and
software vendors, content providers and start-ups. It has had a
major impact in various standardization bodies, such as ETSI
and 3GPP. It caters, among others, for developing a policy
framework that encourages and drives the standardization of
key aspects of femtocell technologies worldwide. It is active
in two main areas: 1) standardization, regulation & interoper-
ability; and 2) marketing & promotion of femtocell solutions
across the industry and to journalists, analysts, regulators,
special interest groups and standards bodies. We now overview
how femtocells fitinto3GCDMA-basednetworks,andthen
4G OFDMA-based networks (LTE).
1) UMTS/cdma2000 Femtocells: UMTS’ three main em-
bodiments (put forward by 3GPP) and cdma2000 (put for-
ward by 3GPP2) have similar architectures and are based on
CDMA. Being IMT-2000 compliant, they theoretically offer
order of magnitude higher data rates than the GSM family,
although depending on the load, the user experience may
not be much different. CDMA networks are interference-
limited and their performance has a fragile dependence on
power control. Without accurate centralized power control,
the “near-far effect” causes nearby users to overwhelm the
received power of farther users, since they use the same
band. With femtocells, such centralized power control is nearly
impossible to accomplish because the received power levels
cannot be simultaneously equalized at numerous points in
space. For example, an uplink macrocell mobile user may
transmit at a power level that effectively disables many nearby
femtocells in that band. Therefore, adding even a small number
of CDMA femtocells can have a profound impact, as seen
theoretically in [24]. Two straightforward solutions to this
problem exist, however. The first is to go to an open access
control paradigm (discussed below in Sect. IV-B), where each
mobile simply communicates with the strongest available base
station: thus, strong interferers are simply handed off and
subsequently lower their power. When this is not possible,
and the femtocells are closed access, the mobile can switch
to another 3G band (most operators have at least two paired
5 MHz channels per market) or revert to GSM.
2) LTE/LTE-A Femtocells: 3GPP is now focused on Long
Term Evolution (i.e. LTE, formally 3GPP Release 8 on-
wards) and LTE-Adanved technologies (LTE-A, Release 10
onwards), while 3GPP2 activities are now essentially discon-
tinued. WiMAX marches on, including femtocell standard-
ization activities [40], but its impact in developed markets
figures to be small. The physical and MAC layer impact of
femtocells on LTE and WiMAX are quite similar, due to their
comparable physical and MAC layer designs, which are based
on orthogonal frequency division multiple access (OFDMA).
Since LTE is likely to be the dominant cellular data platform
for the foreseeable future, the smooth integration of femtocells
into LTE is particularly important, and is the subject of a paper
in the special issue [41].
A key difference in OFDMA (both LTE and WiMAX) is
the large quantity of dynamically allocated time and frequency
slots [42]. This considerable increase in the flexibility of
resource allocation is both a blessing and a curse. Because
femtocells can be allocated orthogonal resources to nearby
pico and macrocells, the possibility for fine-tuned interference
management exists, whereas it did not in GSM or CDMA.
That is, in theory, a complex network-wide optimization could
be done whereby femtocells claim just as much resources as
they “need”, with the macrocells then avoiding using those
time and frequency slots. And therein lies the curse: potentially
a large amount of coordination is necessary. A popular com-
promise is fractional frequency reuse [43], whereby frequency
(or time) resources can be semi-statically allocated to interior,
edge, or small cell users, with power control on top to
lower the throughput disparities experienced in each of these
scenarios. Alternatively, a semi-static partition could simply be
made between femtocells and macrocells. The results in [44]
500 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012
indicate that even with dense femtocell deployments, most
resources should go to the macrocell, since each femtocell
only needs a small number of resource blocks to provide
comparably high throughput to their user(s).
IV. UPLINK AND DOWNLINK FEMTOCELL MODELS
Accurate wireless channel and network models are fun-
damental to the development of standards and to evaluating
possible solutions to the difficulties posed in wireless systems.
In this section we first briefly overview traditional cellular
models, before moving onto modeling such systems with
femtocells, i.e. two-tiered cellular networks. We conclude
by discussing the most general (and practically important)
case of multi-tiered cellular systems consisting of macrocells,
femtocells, picocells and possibly further radiating elements
(like relays, distributed antennas, or future infrastructure).
A. Macrocellular Modeling
1) Link Level Modeling: Cellular models start with the
modeling of a single link, or wireless channel. Such channels
depend on a large number of factors including the propagation
environment, range, carrier frequency, antenna placement, and
antenna type. Typically all of these factors are abstracted
into either theoretical – e.g. path loss, shadowing, fading –
and more accurate but less elegant empirical models, such as
those used by 3GPP [45]. Since femtocells typically differ
significantly from standard cellular systems in all the above
categories except carrier frequency, it can be assumed that their
channel behavior will be more similar to WiFi channels than
cellular channels. Nevertheless, such “indoor” channels are for
the most part well understood at a variety of frequencies [46],
with current general models such as the Winner II channel
models including indoor as a special case.
2) System-Level Modeling: The more challenging and
unique aspects of cellular systems emerge when multiple
simultaneous users are considered. Although sophisticated
theoretical results and techniques have been developed for
downlink (aka “broadcast”) channels and uplink (“multiple
access”) channels [47], [48], these models and the associated
“optimal” techniques have the significant shortcoming that
they generally do not consider the role of (non-Gaussian)
interference or highly disparate (30-50 dB) gains between the
various users.
Developing analytically tractable models for cellular sys-
tems is very difficult. This fact is clearly demonstrated by
the persistence of the extremely simple “Wyner model”, that
adopts a deterministic (or fixed average) SINR for users in
a cell, regardless of whether they are interior or edge users
[49]. Such an approach, unsurprisingly, is not particularly
accurate in most cases [50]. Given the paucity of analytically
tractable models, industry and most academics have stuck
to the well-accepted hexagonal grid model for evaluating
candidate system design features. The grid model is easy
enough to simulate and is thought to closely approximate
well-planned cellular deployments, which has allowed it to
withstand the test of time.
An alternate but currently less popular philosophy is to
model the base stations as randomly located. Perhaps counter-
intuitively, making the base stations randomly located leads to
an analytically tractable model (assuming the placements are
iid) and ultimately fairly simple precise expressions can be
developed for the SINR distribution (and its daughter metrics
like outage and throughput) [51]. One can see in Fig. 2 that
subjectively at least, a real-world macrocell deployment lies
roughly between a fully deterministic grid a fully random (i.e.
iid) placement. We will see below that one further advantage
of this model is that it more naturally integrates femtocells
and other heterogeneous elements.
B. Femtocell Access Control
One important classification for femtocells that strongly
affects the model is the type access control. For a Closed
Subscriber Group (CSG), only pre-registered mobile users can
use a certain femtocell. This would typically be a tiny fraction
of the mobile population. At the other extreme, in an Open
Subscriber Group (OSG), any mobile can use any femtocell,
or at least one that is “open”. Naturally, hybrid approaches are
possible: for example a femtocell might allow up to Nnon-
registered mobile users to access it, but afterwards not admit
new users. This would limit the load on the femtocell and its
backhaul connection.
Generally speaking, open access is a superior approach from
a network capacity point of view, and from the mobile users
point of view. A particular femtocell owner might expect to
see degraded QoS by opening it up to all mobiles in the
network, but in fact this generally does not happen, and in the
CDMA uplink in particular the femtocell performance is much
better even for the home user with open access, since strong
interferers are handed off, mitigating the near-far problem
[27]. In any case, the type of access control is one of the
key features in any cellular model that includes femtocells.
C. Femtocell Network Modeling
The addition of femtocells obviously requires an evolution
of the traditional cellular model. There appear to be four high-
level approaches to modeling femtocells in cellular networks,
although the details can vary quite a bit from paper to paper.
And of course some papers may use and even compare several
of the below models [52].
The first approach is to keep the familiar grid model for
macro base stations (including the special case of a single
macro BS), and to drop femtocells “on top” of it, either
randomly [41], [53]–[56] or in a deterministic fashion [57]–
[59]. One BS (usually the closest and/or strongest) would
connect to the mobile user, with all other macrocell and
femtocell BSs (downlink) or mobile users (uplink) acting
as interference. In closed access, it may not be possible
to connect to the preferred base station, in which case the
interference from even a single interferer can be stronger than
the desired signal, which is an important distinction from a
traditional cellular network.
A second simpler but less complete model is to focus
on a single femtocell (and its associated user) dropped in
the cellular network [27], [60], [61]. In the downlink, the
interference to the femtocell user is assumed to be only from
the various macrocells, which in a fairly sparse femtocell
deployment, is probably accurate. In the uplink as well, the
ANDREWS et al.: FEMTOCELLS: PAST, PRESENT, AND FUTURE 501
(a) (b) (c)
Fig. 2. Example of different macrocell only models. Traditional grid networks remain the most popular, but 4G systems have smaller and more irregular
cell sizes, and perhaps are just as well modeled by a totally random BS placement.
strong interference is bound to come from nearby mobiles
transmitting at high power up to the macro base station, so the
model may be reasonable. The main limitation of this model is
that the performance of downlink macrocell users – who may
experience strong femtocell interference depending on their
position – cannot be accurately characterized.
The third model, which appears to be the most recent, is
to allow both the macrocells and femtocells to be randomly
placed. This is the approach of three papers in this special
issue [62]–[64], and to the best of our knowledge, these
are the first full-length works to propose such an approach
(earlier versions being [65], [66]. Both of these papers are
for the downlink only and an extension to the uplink would
be desirable. An appealing aspect of this approach is that the
randomness actually allows significantly improved tractability
and the SINR distribution can be found explicitly. This may
allow the fundamental impact of different PHY and MAC
designs to be evaluated theoretically in the future.
A fourth model is simply to keep all the channel gains
(including interfering channels) and possibly even the various
per-user capacities general, without specifying the precise
spatial model for the various base stations, e.g. [67], [68]. This
can be used in many higher-level formulations, e.g. for game
theory [60], power control, and resource allocation, although
ultimately some distribution of these channel gains must be
assumed in order to do any simulation, and the gains are
to a first order determined by the locations of the various
transmitting sources. So ultimately, this fourth model typically
will conform to one of the above three models.
V. OVERVIEW OF KEY CHALLENGES
Building on the models developed in last section, as well as
the preceding discussions on standards and historical trends,
in this section we turn our attention to some of the new
challenges that arise in femtocell deployments. To motivate
future research and an appreciation for the disruptive potential
of femtocells, we now overview the broader challenges of fem-
tocells, focusing on both technical and economic/regulatory
issues.
A. Technical Challenges
1) Interference Coordination: Perhaps the most significant
and widely-discussed challenge for femtocell deployments is
the possibility of stronger, less predictable, and more varied
interference, as shown in Fig 3. This occurs predominantly
when femtocells are deployed in the same spectrum as the
legacy (outdoor) wireless network, but can also occur even
when femtocells are in a different but adjacent frequency band
due to out-of-band radiation, particularly in dense deploy-
ments. As discussed in the previous section, the introduction
of femtocells fundamentally alters the cellular topology by
creating an underlay of small cells, with largely random
placements and possible restrictions on access to certain BSs.
Precise characterizations of the interference conditions in such
heterogeneous and multi-tier networks have been the subject
of extensive study [69], [70]. One of the important and perhaps
surprising results shown in [62] is that in principle, with open-
access and strongest cell selection, heterogeneous, multi-tier
deployments do not worsen the overall interference conditions
or even change the SINR statistics. This “invariance prop-
erty” has also been observed in real-world systems by Nokia
Siemens [71] and Qualcomm [72], and provides optimism that
femtocell deployments need not compromise the integrity of
the existing macrocell network.
However, in practice, at least two aspects of femtocell
networks can increase the interference significantly. First,
under closed access, unregistered mobiles cannot connect to
a femtocell even if they are close by. As noted in Section
IV-B, this can cause significant degradation to the femtocell
(in the uplink) or the cell-edge macrocell user in the downlink,
which is near to a femtocell [73]. Second, the signaling
for coordinating cross-tier interference may be logistically
difficult in both open and closed access. Over-the-air control
signaling for interference coordination can be difficult due
502 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012
Apartments
Femto
Femto
User 1
User 3
User 2
Outdoor (Macro)
Base Station
Connected Path
Interfering Paths
Fig. 3. Cross-Tier Intererence for the Downlink and Uplink
to the large disparities in power. Also, backhaul-based sig-
naling with femtocells is often not supported or comes with
much higher delays since femtocells are typically not directly
connected to the operator’s core network – an issue also for
mobility and soft handover as discussed below.
Recognizing these challenges, standards bodies have initi-
ated several study efforts on femtocell interference manage-
ment including those by the Femto Forum [74] and 3GPP
[75], [76]. In addition, advanced methods for intercell interfer-
ence coordination (ICIC) specifically for femtocell networks
has been a major motivation for the 3GPP LTE-Advanced
standardization effort [71], [77]. For 3G CDMA femtos,
the dominant method for interference coordination has been
power control strategies [78]–[80] and/or reserving a “femto-
free” band where macrocell users can go to escape cross-tier
interference when it arises. 4G LTE femtocells offer more
tools for interference coordination including backhaul-based
coordination, dynamic orthogonalization, subband scheduling,
and adaptive fractional frequency reuse. How to best exploit
these techniques is an active area of research [28], [81]–[84]
and is the subject of two papers in this special issue [41], [85].
Going forward, more advanced techniques for interference
control including interference cancelation, and cooperative
communication between multiple base stations are also being
researched [43], [57], [86]. A combining scheme from signals
across multiple femtocell base stations is also discussed in this
issue [67].
2) Cell Association and Biasing: A key challenge in a
heterogenous network with a wide variety of cell sizes is to
assign users to appropriate base stations. The most obvious
way, which does in fact maximize the SINR of each user [87],
is to simply assign each user to the strongest base station
signal it receives. This results in coverage areas much like
those observed in Fig. 4. However, simulations and field trials
have shown that such an approach does not increase the overall
throughput as much as hoped, because many of the small cells
will typically have few active users.
This motivates biasing, whereby users are actively pushed
onto small cells. Despite a potentially significant SINR hit
for that mobile station, this has the potential for a win-win
because the mobile gains access to much larger fraction of
the small cell time and frequency slots. Furthermore, the
macrocell reclaims the time and frequency slots that user
would have occupied. Biasing is particularly attractive in
Fig. 4. Unbiased Cell Association in a 3-tier Heterogenous Network
Fig. 5. Biased Cell Association in a 3-tier Heterogenous Network. Picos
and femtos have a 10 dB bias.
OFDMA networks since the biased user can be assigned
orthogonal resources to the macrocell, so the interference is
tolerable.
An immediate practical challenge introduced by biasing
include the use of overhead channels, which are typically
common to all BSs in time and frequency and so a biased
user would not be able to even hear its channel assignment,
for example. This can been solved by introducing time-slotting
for the control channels [88] or interference cancellation [41].
From a research perspective, a multi-tier network including
femtocells provides an exciting opportunity to revisit cell
association and load balancing rules developed for macro-
ANDREWS et al.: FEMTOCELLS: PAST, PRESENT, AND FUTURE 503
only networks. In particular, it is currently unclear how much
biasing is “optimal”: it clearly depends heavily on (i) the
throughput/QoS metric of interest, (ii) how users and the
various base stations are distributed in space, (iii) traffic
patterns in space-time, and (iv) the amount of adaptivity and
side information the mobiles and small cell base stations are
able to exploit.
3) Mobility and Soft Handover: Since the coverage area
of an individual femtocell is small, it is essential to support
seamless handovers to and from femtocells to provide con-
tinuous connectivity within any wide-area network. Handover
scenarios include femto-to-macro (outbound mobility), macro-
to-femto (inbound mobility) and possibly femto-to-femto; the
latter occurring in enterprise deployments or dense femtocell
coverage in larger public areas.
In principle, femtocells act as other base stations and
can therefore utilize existing mobility procedures. However,
femtocell mobility presents a number of unique challenges
that require special consideration. Standards bodies such as
3GPP have devoted considerable attention to these mobility
issues. See, for example, the specifications [76], [89]. Proce-
dures are also being developed for vertical handovers between
femtocells and non-cellular access technologies such as WiFi,
for example, under the Generic Access Network framework
[90], [91].
Perhaps the most difficult aspect of femtocell mobility is
that femtocells are not typically directly connected into the
core network where mobility procedures are usually coor-
dinated. The lack of a low delay connection to the core
network can result in significant handover signaling delays.
Moreover, for similar architectural reasons, CDMA femtocells
suffer from a further limitation that they are typically unable
to share a Radio Network Controller (RNC) with a macrocell
or other femtocell for coordinating soft handovers. Several
works have begun considering architectural changes in the
core network and femtocell gateway functions to address these
mobility issues [92], [93], although the subject remains an
active area of research.
Femto and picocells also result in much more dense deploy-
ments, which complicates base station discovery – a key initial
step in any handover. Considerable research, particularly in the
standard bodies, have considered improved methods for cell
identification and discovery signaling [94], [95].
An additional complicating factor for femtocell mobility is
the support for features such as Selected IP TrafficOffload
(SIPTO) [96]. In typical macrocellular deployments, data is
routed through a fixed gateway that provides a mobility anchor
and constant IP point of attachment to the public Internet.
However, with SIPTO, IP traffic may be routed directly to the
femtocell, offloading traffic from the operator’s core network.
In such cases, however, each connection to a femtocell results
in a different network point of attachment, possibly with
a different IP addresses. Mobility must then be managed
elsewhere [17].
4) Self-Organizing Networks: Femtocell networks are
unique in that they are largely installed by customers or private
enterprises often in an ad hoc manner without traditional RF
planning, site selection, deployment and maintenance by the
operator. Moreover, as the number of femtocells is expected
to be orders of magnitude greater than macrocells, manual
network deployment and maintenance is simply not scalable
in a cost-effective manner for large femtocell deployments.
Femtocells must therefore support an essentially plug-and-
play operation, with automatic configuration and network
adaptation. Due to these features, femtocells are sometimes
referred to as a self-organizing network (SON).
The 3GPP standards body has placed considerable attention
on SON features [97]–[100] defining procedures for automatic
registration and authentication of femtocells, management and
provisioning, neighbor discovery, synchronization, cell ID
selection and network optimization.
One aspect of SON that has attracted considerable research
attention is automatic channel selection, power adjustment
and frequency assignment for autonomous interference coor-
dination and coverage optimization. Such problems are often
formulated as a mathematical optimization problems for which
a number of algorithms have been considered [101], [102].
This special issue, in particular, contains two articles on
adaptive interference coordination – one on power control
[64] and a second on adaptive carrier selection [59]. Also, al-
though femtocells are often deployed in an unplanned manner,
femtocell placement may be optimized for interference and
coverage, particularly in enterprise settings. An optimization
method for such deployments is considered in a third paper
in this special issue [58].
The adaptive and autonomous nature of interference man-
agement in SONs also bears some similarities to the cognitive
radio concept, where spectrum is allocated in a distributed
manner by devices operating with a significant degree of
autonomy. Indeed, research has begun considering so-called
cognitive femtocells that can dynamically sense spectrum us-
age by the macrocell and adapt their transmissions to optimize
the overall usage of the spectrum [103], [104]. Two articles in
this special issue [61] and [52] explore this cognitive femto-
cell concept; the latter considering an application for video
delivery. However, purely cognitive approaches are known
from poor convergence speeds and precision; to this end, the
emerging concept of docitive networking [105] seems to be a
viable answer, with many issues still remaining unsolved.
A quite different SON feature is the autonomous shutting
down and waking up of base stations for power savings,
addressed in this special issue in [56]. Currently several
initiatives are focusing on reducing the energy consumption of
networks. The most promenent one is “GreenTouch”, a con-
sortium founded by leading industry, academia, government
and non profit research institutions around the world with the
mission to deliver the architecture, specifications and roadmap
to demonstrate the key components needed to increase network
energy efficiency by a factor of 1000 from current levels by
2015. Small cells can play a prominent role in achieving this
goal [106]–[109].
B. Economic and Regulatory Issues
Although the uptake of femtocells has not been as large
as predicted by the most optimistic early market studies
(e.g. [110]), the initial femtocell sales have nevertheless been
impressive, as outlined in Section I. Even with this expected
504 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012
success, femtocells will represent only a very small fraction of
the overall cellular market. Whether femtocells can ever play
a dominant role in the network itself depends not only on the
technical challenges discussed above, but on a number of basic
economic and market questions, which are now surveyed.
1) Operator Business Case: The business case for femto-
cells has been made by a number of studies [111], [112]. The
basic value proposition is that the cost of the femtocell itself
is greatly outweighed by the savings from offloading traffic
from the macrocellular networks [113]. These findings appear
to be true across a range of market segments from residential
to enterprise users. By some models, operators can realize
as much as a 10x return from femtocells. In addition, new
entrant operators or operators deploying new 4G technologies,
can leverage femtocells to delay costly initial capital costs on
macrocellular network.
2) Subscriber and ISP Incentives: With femtocells, the
operator is not the only player with an economic stake in
the network: subscribers and enterprises become responsible
for installing the femtocells while private ISPs provide the
backhaul. Unlike the operator, the economic incentives for
these parties are less clear.
Private ISPs that supply the backhaul connection to femto-
cells will be forced to carry additional traffic, particularly if the
femtocells are open access. If femtocells become the dominant
cellular technology, these ISPs will end up responsible for a
large portion of all mobile traffic. How ISPs would respond
remains to be seen. Will ISPs enforce bandwidth or data
limits, will they increase charges to subscribers, or perhaps
enter arrangements with the cellular operators? How would
such maneuvers affect the overall cost and business case for
femtocells?
End users also face economic questions since they are the
ones to purchase and install the femtocells. Femtocells provide
a value for the overall network capacity by offloading traffic
from the macrocells and increasing the overall number of cells.
But, an individual subscriber is not directly concerned with the
overall network capacity, only his or her quality of experience.
These objectives may not be aligned, particularly in questions
on whether femtocells should be open access and how the
femtocells allocate resources between the owners and public
users.
Developing an economic framework in which these diverse
participants can both derive individual value while encour-
aging efficient use of the overall system resources will be
a central research problem for femtocells going forward. An
interesting line of academic work has considered various pric-
ing and game theoretic approaches [114], [115]. This theme is
explored in three articles in this special issue [55], [60], [68],
that reveal interesting interplay between the economic aspects
of pricing and the physical layer aspects of wireless network
interactions.
3) Femto vs. WiFi and Whitespace: Femtocells offer a very
different approach to that of WiFi and especially whitespace.
Femtocells are provided by wireless operators as a managed
service compared to the best-effort service offered by WiFi
and possibly whitespace. Although today many people accept
this best effort approach to mobile broadband, it is our
view that users will want a mobile broadband experience
with the level of reliability they have come to expect from
wired broadband. As WiFi networks become ever more dense,
their performance will continue to degrade since the 802.11
standards do not support coordination across different access
points. In addition, subscribers want a single number to call for
customer service, which is typically difficult with WiFi today.
The seamless integration with the cellular network is a unique
selling point for femtocells and provides value that users are
likely willing to pay for. These managed services include the
ability for the wireless operator to provide comprehensive end-
to-end management, including data on where you are, what
hardware you are using, how you are connected and various
other management parameters.
Whitespace and WiFi are competing for the home wireless
spectrum and thus with devices that are streaming high defi-
nition video on multiple bands, as well as wireless speakers,
remote controls and baby monitors. All this makes the home
of the future rather congested in the WiFi bands at least.
Whitespace is even considerably more speculative, and some
studies suggest that there is very little – if any – whitespace
in many key US markets. Further, whitespace approaches are
still not even approved outside of the US, with only the UK
seriously considering their use, and then primarily for rural
broadband.
Having above described femtocells as a competitor to WiFi
it is interesting to note that recent trials using a converged gate-
way architecture that combined WiFi and 3G wireless modems
demonstrated how the technologies could be combined to take
advantage of both forms of connectivity to further enhance
data throughput and overall reliability. Several companies are
likely to simultaneously push both technologies for offloading.
In short, we see WiFi and femtocells as complementary
approaches to moving data off the cellular network and expect
both to be very successful in the years to come.
4) Regulatory Aspects: Femtocells present several unique
regulatory challenges, particularly since the operator loses
some of the direct control of the access point relative to its
control of base stations in traditional operator-managed net-
works. Of course, operators will retain a considerable degree
of control, since femtocells are generally remotely configured
and managed from the operator’s core network. However,
reliable procedures must be in place to ensure authentication,
location verification and compliance to standards and spectral
emission requirements. Some of the issues though are similar
to those for handsets that operate in the provider’s network
while being manufactured and owned by third parties. A
summary of these challenges can be found in [116].
Other regulatory issues concern spectrum. Since femtocells
can co-exist in the same spectrum as macrocells, there is
no need for specific femtocell spectral allocations. Although
initial deployments have used separate or partially separate
bands for femtocell deployment there is significant pressure
on operators to move to shared carrier deployments. This
is driven by the demand and lack of spectrum that opera-
tors have. Operators also have a need for an approach that
seamlessly works across countries and regions, minimizing
configuration and special settings, thus minimizing operational
costs. Nevertheless, there has been some interest in femtocell
specific allocations. For example, the UK regulator OfCom has
ANDREWS et al.: FEMTOCELLS: PAST, PRESENT, AND FUTURE 505
proposed to allocate a portion (as much as 2 x 20 MHz) of
the 2.6 GHz band specifically for low-power use [117]. Given
the nature of cross-tier interference, spectrum allocation and
co-channel deployments for femtocells remains an on-going
challenge for wireless operators.
VI. CONCLUSIONS
The cellular industry has rarely seen more exciting times:
as the demand for cellular data services skyrockets and the
network topology undergoes the most significant changes since
the birth of cellular, researchers and industry alike will not
often be bored. Femtocells typify this renaissance with their
organic plug-and-play deployment, highly democratic cost,
and the possible chaos they introduce to the network. This
article – and special issue – argue though that fears about
femtocells negative effects are overblown. Whether or not
they live up to the hype and help move the data avalanche
to being a backhaul problem is as yet unclear; but it seems
to the authors that there is nothing fundamental preventing
very dense femtocell deployments, and that the economic
and capacity benefits femtocells provide appear to justify the
optimistic sales forecasts.
VII. ACKNOWLEDGEMENTS
A large number of people generously contributed to this
special issue, including the authors, reviewers, and JSAC
editorial staff. The guest editors appreciate the enthusiastic
response from both academia and industry to this special issue.
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Jeffrey G. Andrews (S’98, M’02, SM’06) received
the B.S. in Engineering with High Distinction from
Harvey Mudd College in 1995, and the M.S. and
Ph.D. in Electrical Engineering from Stanford Uni-
versity in 1999 and 2002, respectively. He is an As-
sociate Professor in the Department of Electrical and
Computer Engineering at the University of Texas at
Austin, where he was the Director of the Wireless
Networking and Communications Group (WNCG)
from 2008-12. He developed Code Division Multiple
Access systems at Qualcomm from 1995-97, and
has consulted for entities including the WiMAX Forum, Microsoft, Apple,
Clearwire, Palm, Sprint, ADC, and NASA.
Dr. Andrews is co-author of two books, Fundamentals of WiMAX
(Prentice-Hall, 2007) and Fundamentals of LTE (Prentice-Hall, 2010), and
holds the Earl and Margaret Brasfield Endowed Fellowship in Engineering at
UT Austin, where he received the ECE department’s first annual High Gain
award for excellence in research. He is a Senior Member of the IEEE, served
as an associate editor for the IEEE Transactions on Wireless Communications
from 2004-08, was the Chair of the 2010 IEEE Communication Theory
Workshop, and is the Technical Program co-Chair of ICC 2012 (Comm.
Theory Symposium) and Globecom 2014. He has also been a guest editor
for two recent IEEE JSAC special issues on stochastic geometry as well as
the current one.
Dr. Andrews received the National Science Foundation CAREER award in
2007 and has been co-author of five best paper award recipients, two at Globe-
com (2006 and 2009), Asilomar (2008), the 2010 IEEE Communications
Society Best Tutorial Paper Award, and the 2011 Communications Society
Heinrich Hertz Prize. His research interests are in communication theory,
information theory, and stochastic geometry applied to wireless cellular and
ad hoc networks.
Holger Claussen (M’01, SM’10) is head of the
Autonomous Networks and Systems Research De-
partment at Bell Labs, Alcatel-Lucent, for Ireland
and the United Kingdom. He received his Dipl.-
Ing. (FH) and M.Eng. degrees in electronic engi-
neering from the University of Applied Sciences in
Kempten, Germany, and the University of Ulster,
United Kingdom, respectively. He received a Ph.D.
degree in signal processing for digital communi-
cations from the University of Edinburgh, United
Kingdom, for his work on low complexity mul-
tiple input-multiple output (MIMO) receiver architectures. Afterwards, Dr.
Claussen joined Bell Labs in Swindon, United Kingdom, as Research Engi-
neer in 2004. He became Department Head in the lab in Dublin, Ireland, in
2009.
At Bell Labs, Dr. Claussen has been working on auto-configuration and
dynamic optimization of networks, self-deploying networks, distributed al-
gorithms, flat cellular network architectures, fourth-generation (4G) systems,
mobility, resource management, end-to-end network modeling, and improving
energy efficiency of networks. More recently he has been directing research
and technology transfer of self-management and efficient networking so-
lutions. This has been commercialized as the Alcatel-Lucent BSR-Femto
product. Dr. Claussen is author of more than 40 publications and 70 filed
patent applications. He is senior member of the IEEE, member of the IET,
and the Alcatel-Lucent Technical Academy.
508 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 3, APRIL 2012
Mischa Dohler is now leading the Intelligent En-
ergy [IQe] group at CTTC in Barcelona, with focus
on Smart Grids and Green Radios. He is work-
ing on wireless sensor, machine-to-machine, femto,
cooperative, cognitive and docitive networks. Prior
to this, from June 2005 to February 2008, he has
been Senior Research Expert in the R&D division
of France Telecom, France. From September 2003
to June 2005, he has been lecturer at King’s College
London, UK. At that time, he has also been London
Technology Network Business Fellow receiving ap-
propriate Anglo-Saxon business training, as well as Student Representative
of the IEEE UKRI Section and member of the Student Activity Committee
of IEEE Region 8 (Europe, Africa, Middle-East and Russia).
He obtained his PhD in Telecommunications from King’s College London,
UK, in 2003, his Diploma in Electrical Engineering from Dresden University
of Technology, Germany, in 2000, and his MSc degree in Telecommunications
from King’s College London, UK, in 1999. Prior to Telecommunications, he
studied Physics in Moscow. He has won various competitions in Mathematics
and Physics, and participated in the 3rd round of the International Physics
Olympics for Germany. In the framework of the Mobile VCE, he has pio-
neered research on distributed cooperative space-time encoded communication
systems, dating back to December 1999. He has published 138 technical
journal and conference papers at a citation h-index of 24 and citation g-index
of 49, holds 13 patents, authored, co-edited and contributed to 19 books,
has given 25 international short-courses, and participated in standardisation
activities. He has been TPC member and co-chair of various conferences, such
as technical chair of IEEE PIMRC 2008 held in Cannes, France. He is EiC of
ETT and is/has been holding various editorial positions for numerous IEEE
and non-IEEE journals. He is Senior Member of the IEEE and Distinguished
Lecturer of IEEE ComSoc. He is fluent in 6 languages.
Sundeep Rangan (M’02) received the B.A.Sc. at
the University of Waterloo, Canada and the M.Sc.
and Ph.D. at the University of California, Berkeley,
all in Electrical Engineering. He has held postdoc-
toral appointments at the University of Michigan,
Ann Arbor and Bell Labs. In 2000, he co-founded
(with four others) Flarion Technologies, a spin off
of Bell Labs, that developed Flash OFDM, one of
the first cellular OFDM data systems. Flarion grew
to over 150 employees with trials worldwide. In
2006, Flarion was acquired by Qualcomm Technolo-
gies where Dr. Rangan was a Director of Engineering involved in OFDM
infrastructure products. He joined the ECE department at Poly in 2010.
His research interests are in wireless communications, signal processing,
information theory and control theory.
Mark C. Reed received his B. Eng. (Honors) in
Electronic Engineering from the Royal Melbourne
Institute of Technology (RMIT) in 1990, and Ph.D.
in Communication Engineering from the University
of South Australia, Australia in 2000. He is an Asso-
ciate Professor (Adj.) at the College of Engineering
and Computer Science (CECS) at the Australian
National University (ANU) and Founder and CEO
of InterfereX Communications Pty. Ltd., a company
specializing in improving system performance for
small cells. He has previously been a Principal
Researcher and Project Leader at NICTA where he led a research- inspired
commercial project on femtocells. This project was first to demonstrate a
real-time hardware realization of uplink interference cancellation at radio
frequencies for a 3G/WCDMA femtocell modem. Mark previously worked
for Ascom Systec AG and developed a real-time world- first Satellite-UMTS
demonstrator for the European Space Agency. He has also led a team at
NICTA in the development of an advanced real- time wireless proof-of-
concept mobile WiMAX modem demonstration system.
Mark’s research interests include applications of iterative techniques to
signal processing problems, fundamental limits of heterogeneous wireless
networks, modem signal acquisition, and signal tracking techniques. Mark
pioneered the area of iterative (turbo) detection techniques for WCDMA
base station receivers and has more than 64 publications and eight patent
applications. He has a mix of real- world industrial experience as well as
research experience where he continues to put his techniques into practice. He
won the Australian Information Industry Association Award (iAward, Merit
- R&D Category) at the National level in 2010. He is also the recipient of
Engineers Australia IREE Neville Thiele Award in 2007.
Mark was responsible for Sponsorship and Travel Grants for the IEEE ISIT
- 2004, was co-chair of the Acorn Wireless Winter School (2005, 2006), and
Publication Chair and member of the TPC for IEEE VTC - 2006. He is a
Senior Member of the IEEE and from 2005-2007 he was an Associate Editor
for the IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY.
