INVITED
PAPER
Multiuser MIMO-OFDM
for Next-Generation
Wireless Systems
Multiple-Input Multiple-Output (MIMO) wireless systems using OFDM promise to
provide the needed performance for future consumer products. This paper reviews
existing MIMO-OFDM systems, discusses their limitations, and examines the
use of Genetic Algorithms (GAs) as a tool to handle large numbers of users.
By Ming Jiang, Member IEEE,andLajosHanzo,Fellow IEEE
ABSTRACT
|
This overview portrays the 40-year evolution of
orthogonal frequency division multiplexing (OFDM) research.
The amelioration of powerful multicarrier OFDM arrangements
with multiple-input multiple-output (MIMO) systems has nu-
merous benefits, which are detailed in this treatise. We
continue by highlighting the limitations of conventional
detection and channel estimation techniques designed for
multiuser MIMO OFDM systems in the so-called rank-deficient
scenarios, where the number of users supported or the number
of transmit antennas employed exceeds the number of receiver
antennas. This is often encountered in practice, unless we limit
the number of users granted access in the base station’s or
radio port’s coverage area. Following a historical perspective
on the associated design problems and their state-of-the-art
solutions, the second half of this treatise details a range of
classic multiuser detectors (MUDs) designed for MIMO-OFDM
systems and characterizes their achievable performance. A
further section aims for identifying novel cutting-edge genetic
algorithm (GA)-aided detector solutions, which have found
numerous applications in wireless communications in recent
years. In an effort to stimulate the cross pollination of ideas
across the machine learning, optimization, signal processing,
and wireless communications research communities, we will
review the broadl y appli cable principles of va rious GA-assisted
optimization techniques, which were recently proposed also
for employment in multiuser MIMO OFDM. In order to stimulate
new research, we demonstrate that the family of GA-aided
MUDs is capable of achieving a n ear-optimum performance at
the cost of a significantly lower computational complexity than
that imposed by their optimum maximum-likelihood (ML) MUD
aided counterparts. The paper is concluded by outlining a
range of future research options that may find their way into
next-generation wireless systems.
KEYWORDS
|
Channel est imation; genetic algorithm (GA);
multiple-input multiple-output (MIMO); multiuser detection/
detector (MUD); orthogonal frequency division multiplexing
(OFDM); space division multiple access (SDMA)
I. MOTIVATION AND INTRODUCTION
TO MULTIPLE-INPUT MULTIPLE-
OUTPUT (MIMO)-ORTHOGONAL
FREQUENCY DIVISION MULTIPLEXING
(OFDM) SYSTEMS
During the past decades, wireless communication has
benefitted from substantial advances and it is considered
as the key enabling technique of innovative future
consumer products. For the sake of satisfying the
requirements of various applications, significant techno-
logical achievements are required to ensure that wireless
devices have appropriate architectures suitable for sup-
porting a wide range of services delivered to the users.
In the foreseeable future, the large-scale deployment
of wireless devices and the requirements of high-
bandwidth applications are expected to lead to tremen-
dous new challenges in terms of the efficient exploitation
Manuscript received December 15, 2006; revised April 2, 2007.
M. Jiang is with Samsung Electronics Research Institute, TW18 4QE Staines, U.K.
(e-mail: ming.jiang@samsung.com).
L. Hanzo is with the School of Electrical and Computer Science (ECS), University of
Southampton, SO17 1BJ Southampton, U.K. (e-mail: lh@ecs.soton.ac.uk;
http://www-mobile.ecs.soton.ac.uk).
Digital Object Identifier: 10.1109/JPROC.2007.898869
1430 Proceedings of the IEEE |Vol.95,No.7,July2007 0018-9219/$25.00
2007 IEEE
of the achievable spectral resources. Among the existing
air-interface techniques, orthogonal frequency division
multiplexing (OFDM) [1]–[4] has shown a number of
advantages and has attracted substantial interest. New
wireless techniques, such as ultra wideband (UWB) [5],
advanced source and channel encoding as well as various
smart antenna techniques, for example space-time codes
(STCs) [6], space division multiple access (SDMA) [1] and
beamforming, as well as other multiple-input multiple-
output (MIMO) [7], [8] wireless architectures are capable of
offering substantial gains. Hence, researchers have focused
their attention on the next generation of wireless broadband
communications systems, which aim for delivering multi-
media services requiring data rates beyond 2 Mbps.
Undoubtedly, the support of such high data rates, while
maintaining a high robustness against radio channel
impairments requires further enhanced system architec-
tures, which should aim for approaching the capacity of
MIMO-aided systems communicating over the fading
channels exemplified in Fig. 1 in the context of one or two
transmit and one, two as well as six receivers, respectively.
In a conceptually appealing, but somewhat simplistic
manner, we may argue that the one-transmitter (1Tx) and
one-receiver (1Rx) scenario is exposed to fading, since the
vectorial sum of the multiple propagation paths may add
constructively or destructively. By contrast, in case of the
2Tx and 6Rx scenario, for example, the chances are that at
least one of the independently faded diversity-links benefits
from the constructive interference of the received paths. To
elaborate a little further, the achievable MIMO capacity [9]
is exemplified for the specific scenario of 16-level quadrature
amplitude modulation (QAM) transmissions over a two-
transmitter, two-receiver MIMO system in Fig. 2. It
becomes explicit in Fig. 2 that a MIMO system designed
for achieving the maximum diversity gainVi.e. robustness
against transmission errorsVrequires a lower channel
signal-to-noise-ratio (SNR) than its counterpart dedicated
to attaining the maximum multiplexing gain, i.e., through-
put, but naturally, the lower operating SNR is maintained at
the cost of a lower bit/symbol throughput. The variable D in
Fig. 2 indicates the number of dimensions exploited by the
modulation scheme and D ¼ 2 corresponds to classic two-
dimensional QAM schemes.
In recent years various smart antenna designs have
emerged, which have found application in diverse scenar-
ios and the four most wide-spread MIMO types are briefly
summarized in Table 1. These four MIMO schemes were
designed for achieving various design goals. The family of
Spatial Division Multiplexing (SDM) [1], [10] schemes
aims for maximizing the attainable multiplexing gain, i.e.,
the throughput of a single user by exploiting the unique,
antenna-specific channel impulse responses (CIRs) of the
array elements. By contrast, SDMA arrangements [1] are
close relatives of SDM schemes, but they maximise the
number of users supported, as opposed to maximizing the
throughput of a single user by sharing the total system
Fig. 1. Instantaneous channel SNR versus both time and frequency for
a 512-subcarrier OFDM modem in the context of a single-transmitter
single-receiver as well as for MIMO-aided two-transmitter systems
using one, two and six receivers when communicating over an indoor
wireless channel. The average channel SNR is 10 dB [6].
Jiang and Hanzo: Multiuser MIMO-OFDM for Next-Generation Wireless Systems
Vol. 95, No. 7, July 2007 | Proceedings of the IEEE 1431
throughput amongst the users supported. Alternatively,
attaining the maximum possible diversity gain is the
objective of the family of space-time block coding (STBC)
[11] as well as space-time trellis coding (STTC) [12]
schemesfoundintheliterature[6].InFig.1thebeneficial
effects of second-order transmit and up to sixth-order
receiver diversity was demonstrated in the context of
STBC-aided MIMO-OFDM [13], [14], but space-time
coding MIMOs will not be considered further in this
treatise. Finally, beamforming mitigates the effects of
interfering users roaming in the vicinity of the desired user
[15], provided that their received signals are angularly
separable, as demonstrated in Fig. 3. Similarly to space-
time coding, beamforming MIMOs will not be detailed
furtherinthistreatise.
We commence by briefly introducing the basic concept
of OFDM, as a means of dealing with the problems of the
so-called frequency selective fading exemplified in Fig. 1,
when transmitting at a high rate, where the delayed and
reflected radio paths impose intersymbol interference
(ISI) on the neighboring bits. The fundamental principle
of OFDM originates from Chang [16], and over the years
a multiplicity of researchers have investigated this
Fig. 3. The multipath environments of an uplink scenario,
protraying the individual multipath components of the desired
signals, the line-of-sight interference and the associated
base station antenna array beam patterns [15].
Fig. 2. The capacity of the MIMO uncorrelated Rayleigh-fading
channel and additive white gaussian noise (AWGN) channel for
classic 16 QAM (M ¼ 16, D ¼ 2) and for so-called four-dimensional
signalling (M ¼ 32, D ¼ 4) [9].
Table 1 The Four Main Applications of MIMOs in Wireless Communications
Jiang and Hanzo: Multiuser MIMO-OFDM for Next-Generation Wireless Systems
1432 Proceedings of the IEEE |Vol.95,No.7,July2007
technique, as detailed in this paper. Despite its conceptual
elegance, during its infancy the employment of OFDM has
been mostly limited to military applications due to
implementational difficulties. However, it has recently
been adopted as the Digital Audio Broadcasting (DAB) [17]
standard as well as the Digital Video Broadcasting (DVB)
[18], [19] and for a range of other high-rate applications,
such as wireless local area networks (WLANs) [20], as
detailed below. These wide-ranging applications underline
its significance as an alternative technique to conventional
channel equalization [2] in order to combat signal
dispersion.
IntheOFDMschemeofFig.4theserialdatastreamof
a traffic channel is passed through a serial-to-parallel
convertor, which splits the data-stream into K number of
low-rate parallel subchannels. The data symbols of each
subchannel are applied to a modulator, where there are K
modulators whose carrier frequencies are f
0
; f
1
; ...; f
K
.The
difference between adjacent channels is f and the overall
bandwidth W of the K modulated carriers is Kf .The
substantial benefit of this approach is that the symbol
duration of each of the K subchannels is extended by a
factor of K,whereK 1024 may be assumed and, hence,
typically each subcarrier’s signal is likely to remain
unaffected by the multipath propagation. Hence, we can
dispense with classic channel equalization [2]. These K
modulated carriers are then combined to generate the
OFDM signal. We may view the serial-to-parallel (SP)
convertor, as applying every Kth symbol to a modulator.
This has the effect of interleaving the symbols forwarded to
each modulator; hence, symbols s
0
; s
K
; s
2K
; ..., are applied
to the modulator whose carrier frequency is f
0
.Atthe
receiver the received OFDM signal is demultiplexed into K
frequency bands, and the K modulated signals are
demodulated. The baseband signals are then recombined
using a parallel-to-serial (PS) convertor.
Again, the main advantage of the above OFDM concept
is that because the symbol period has been increased, the
channel’s delay spread becomes a significantly shorter
fraction of a symbol period than in the serial system,
potentially rendering the system less sensitive to ISI than
the conventional serial system. In other words, in the low-
rate subchannels the signal is no longer subject to
frequency-selective fading, hence, channel equalization
may be avoided.
At first sight it may appear to be a disadvantage of the
OFDM approach shown in Fig. 4 that an increased
complexity is imposed in comparison to a conventional
serial modem, since we are employing K modulators and
Bsquare-root-Nyquist[ filters [2] at the transmitter and K
demodulators and Bsquare-root-Nyquist[ filters at the
receiver. However, each subchannel modulator is operated
at a K-times lower symbol-rate and, hence, the system may
be viewed as a Bparallelized low-speed implementation[ of
a high-speed serial modem. As a further complexity
mitigation technique, it may demonstrated mathematically
[2] that this complexity can be further reduced by
employing a fast Fourier transform (FFT)-based imple-
mentation, where a block of K subchannels’ signal is
modulated onto the subcarriers in a single step. This is
indeed quite plausible, since the e
jkf
0
t
ðk ¼ 1; ; KÞ FFT-
kernels correspond to the subchannel modulators of Fig. 4.
The subchannel modems can use arbitrary modulation
schemes and in recent years high-throughput QAM
Fig. 4. Simplified block diagram of the orthogonal parallel modem.
Jiang and Hanzo: Multiuser MIMO-OFDM for Next-Generation Wireless Systems
Vol. 95, No. 7, July 2007 | Proceedings of the IEEE 1433
schemes have been favored. For a deeper tutorial exposure
the interested reader is referred to [1], [2].
The organization of this paper is as follows. The
portrayal of OFDM and its various applications from a
historical perspective is provided in Section II. More
specifically, Section II-A summarizes both the various
international standards based on OFDM and the main
research contributions to the OFDM literature, followed
by a brief outline of MIMO-aided OFDM systems in
Section II-B. Furthermore, in Sections III-A and B we
point out the specific limitations of existing detection
techniques and channel estimation approaches designed
for multiuser MIMO OFDM systems, respectively. As a
powerful tool proposed for finding near-optimum solu-
tions to complex nonlinear optimization problems,
genetic algorithms (GAs) [27]–[31] that were originally
advocated by the evolutionary computing community
have recently also been successfully exploited by the
wireless communication community, bridging the inter-
disciplinary gap between the two historically distinct
research communities. Aiming for providing efficient so-
lutions to the problems stated in Section III, we highlight
various GA-assisted techniques designed for multiuser
MIMO OFDM in Sections IV–VI where numerous appli-
cation examples are provided. Finally, our conclusions
and a range of future research options are offered in
Section VII.
II. HISTORIC BACKGROUND
A. Orthogonal Frequency Division Multiplexing
In recent years OFDM [1]–[4] has emerged as a pro-
mising air-interface technique. In the context of wired
environments, OFDM techniques are also known as
Discrete MultiTone (DMT) [32] transmissions and are
employed in the American National Standards Institute’s
(ANSI) Asymmetric Digital Subscriber Line (ADSL) [33],
High-bit-rate Digital Subscriber Line (HDSL) [34], and
Very-high-speed Digital Subscriber Line (VDSL) [35]
standards as well as in the European Telecommunication
Standard Institute’s (ETSI) [36] VDSL applications. In
wireless scenarios, OFDM has been advocated by many
European standards, such as Digital Audio Broadcasting
(DAB) [17], Digital Video Broadcasting for Terrestrial
Television (DVB-T) [18], Digital Video Broadcasting for
Handheld Terminals (DVB-H) [19], Wireless Local Area
Networks (WLANs) [20], and Broadband Radio Access
Networks (BRANs) [37]. Furthermore, OFDM has been
ratified as a standard or has been considered as a candidate
standard by a number of standardization groups of the
Institute of Electrical and Electronics Engineers (IEEE),
such as the following.
• IEEE 802.11a [38]: An extension to IEEE 802.11
[39] that applies to WLANs and provides a bitrate
of up to 54 Mbps in the 5 GHz band. In comparison
to IEEE 802.11, where frequency-hopping spread
spectrum (FHSS) or direct-sequence spread spec-
trum (DSSS) are used, IEEE 802.11a employs an
OFDM scheme which applies to wireless asyn-
chronous transfer mode (WATM) networks and
access hubs.
• IEEE 802.11g [40]: Offers wireless transmission
over relatively short distances at 20–54 Mbps in
the 2.4 GHz band. It also uses an OFDM scheme.
• IEEE 802.11n [41]: Candidate standard for next
generation WLANs, which was created from pre-
vious IEEE 802.11 standards by incorporating
MIMO techniques. It offers high-throughput wire-
less transmission at 100–200 Mbps.
• IEEE 802.16 [42]: Defines wireless services
operating in the 2–11 GHz band associated with
wireless metropolitan area networks (WMANs),
providing a communication link between a sub-
scriber and a core network, e.g., the public
telephone network and the Internet.
The first OFDM schemes date back to the 1960s, which
were proposed by Chang [16] and Saltzberg [43]. In the
classic parallel data transmission systems [16], [43], the
frequency-domain (FD) bandwidth is divided into a
number of nonoverlapping subchannels, each of which
hosts a specific carrier widely referred to as a subcarrier.
While each subcarrier is separately modulated by a data
symbol, the overall modulation operation across all the
subchannels results in a frequency-multiplexed signal.
Since the modulated signal’s spectrum is multiplied by a
rectangular window corresponding to the length of the
time-domain (TD) OFDM symbol, the subcarriers have to
be convolved with resultant FD sinc-function. Similarly to
classic ISI-free orthogonal TD Nyquist-signalling, all of the
sinc-shaped FD subchannel spectra exhibit zero-crossings
at all of the surrounding subcarrier frequencies and,
hence, the individual subchannel spectra are orthogonal to
each other. This ensures that the subcarrier signals do not
interfere with each other, when communicating over
perfectly distortionless channels, as a consequence of their
orthogonality [1].
The early OFDM schemes [16], [43], [44], [51]
required banks of sinusoidal subcarrier generators and
demodulators, which imposed a high implementation
complexity. This drawback limited the application of
OFDM to military systems until 1971, when Weinstein and
Ebert [45] suggested that the discrete Fourier transform
(DFT) can be used for the OFDM modulation and
demodulation processes, which significantly reduces the
implementation complexity of OFDM. Since then, more
practical OFDM research has been carried out. For
example, in the early 1980s Peled and Ruiz [52] pro-
posed a simplified FD data transmission method using a
cyclic prefix aided technique and exploited reduced-
complexity algorithms for achieving a significantly
lower computational complexity than that of classic
Jiang and Hanzo: Multiuser MIMO-OFDM for Next-Generation Wireless Systems
1434 Proceedings of the IEEE |Vol.95,No.7,July2007
