18-04-2014, 10:50 AM
Smart Antennas for Mobile Communications
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Abstract
This paper presents a tutorial on emerging tech-
nologies in the area of Smart Antennas for mobile wireless
communications, also referred to as ”space time processing”.
It was written in 1998 and published in 2000 as part as the
Encyclopedia for Electrical Engineering, John Wiley Pub-
lishing Co. Note that it does not cover the area of MIMO
systems.
INTRODUCTION
Wireless cellular networks are growing rapidly around
the world and this trend is likely to continue for several
years. The progress in radio technology enables new and
improved services. Current wireless services include trans-
mission of voice, fax and low-speed data. More bandwidth-
consuming interactive multimedia services like video-on-
demand and internet access will be supported in the fu-
ture. Wireless networks must provide these services in a
wide range of environments, spanning dense urban, subur-
ban, and rural areas. Varying mobility needs must also be
addressed. Wireless local loop networks serve fixed sub-
scribers. micro-cellular networks serve pedestrians or slow
moving users, and macro-cellular networks serve high speed
vehicle-borne users. Several competing standards have
been developed for terrestrial networks. AMPS (advanced
mobile phone system) is an example of first-generation fre-
quency division multiple access analog cellular system. Sec-
ond generation standards include GSM (Global System for
Mobile) and IS-136, using Time division multiple access
(TDMA), and IS-95 using code division multiple access
(CDMA). IMT-2000 is proposed to be the third genera-
tion standard and will use either a wide-band CDMA or
TDMA technology.
Antenna diversity
Antenna diversity can alleviate the effects of channel fad-
ing, and is used extensively in wireless networks. The basic
idea of space diversity is as follows: if several replicas of the
same information carrying signal are received over multi-
ple branches with comparable strengths and which exhibit
independent fading, then there is a high probability that
at least one (or more) branch will not be in a fade at any
given instant of time. When a receiver is equipped with two
or more antennas that are sufficiently separated (typically
several wavelengths) they offer useful diversity branches.
Diversity branches tend to fade independently, therefore, a
proper selection or combining of the branches increases link
reliability. Without diversity, the protection against deep
channel fades requires higher transmit power to ensure the
link margins. Therefore, diversity at the base can be traded
for reduced power consumption and longer battery life at
the user terminal. Also, lower transmit power decreases the
amount of co-channel interference and increases the system
capacity.
Emerging application of space-time
processing
While the use of beamforming and space diversity proves
useful in radio communications applications, an inherent
limitation of these concepts lies in the fact that the afore-
mentioned techniques exploit signal combining in the space
dimension only. Directional beamforming, in particular,
heavily relies on the exploitation of the spatial signatures
of the incoming signals but does not consider their tempo-
ral structure. The techniques which combine the signals
in both time and space can bring new leverages, and their
importance in the area of mobile communications is now
recognized [5].
The main reason for using space-time processing is that
it can exploit the rich temporal structure of digital com-
munication signals. In addition, multipath propagation
environments introduces signal delay spread, making tech-
niques that exploit the complete space-time structure more
natural.
A non parametric model
The data models above build on the parametric channel
model developed earlier. However, there is also interest in
considering the end-to-end channel impulse response of the
system to a transmitted symbol rather than the physical
path parameters. The channel impulse response includes
the pulse shaping filter response, the propagation phenom-
ena, and the antenna response as well. One advantage of
looking at the impulse response is that the effects of ISI and
CCI can be described in a better and more compact way. A
second advantage is that the non parametric channel only
relies on the channel linearity assumption.
Summary
Smart antennas constitute a promising but still emerg-
ing technology. Space-time processing algorithms provide
powerful tools to enhance the overall performance of wire-
less cellular networks. Improvements, typically by a factor
of two in cell coverage or capacity are shown to be possi-
ble according to results from field deployments using sim-
ple beamforming. Greater improvements can be obtained
from some of the more advanced space-time processing so-
lutions described in this paper. The successful integration
of space-time processing techniques will however also re-
quire a substantial evolution of the current air interfaces.
Also, the design of space-time algorithms must also be ap-
plication and environment specific.