Digital Signal Processing Reference
In-Depth Information
service, which again implies less power consumption. As can be seen, adaptation algo-
rithms lead to improved performance, increased capacity, lower power consumption,
increased radio coverage area, and eventually better overall wireless communications
system design.
Many adaptation schemes require a form of measurement (or estimation) of various
quantities (parameters) that might change over time. These estimates are then used to
trigger or perform a multitude of functions, like the adaptation of the transmission and
reception. For example, Doppler spread and delay spread estimations, signal-to-noise
ratio (SNR) estimation, channel estimation, BER estimation, cyclic redundancy check
(CRC) information, and received signal strength measurement are some of the com-
monly used measurements for adaptive algorithms. As the interest in the adaptation
schemes increases, so does the research on improved (fast and accurate) parameter esti-
mation techniques.
In this chapter, an overview of commonly used adaptation techniques and their appli-
cations for wireless mobile radio systems is given. Some of the commonly used param-
eters and their estimation using baseband signal processing techniques are explained
in detail. Also, the current and future research issues regarding the improved param-
eter estimation and extensive use of adaptation techniques are discussed throughout
the chapter. Note that there has been a significant amount of research on adaptation
of wireless communications systems. This chapter is not intended to cover all these
developments, but rather, it is intended to provide the readers an overview and con-
ceptual understanding of adaptation techniques and related parameter estimation algo-
rithms. More emphasis is given on signal processing perspectives of the adaptation of
wireless communications systems.
1.2
Overview of Adaptation Schemes
In wireless mobile communications systems, information is transmitted through a radio
channel. Unlike other guided media, the radio channel is highly dynamic. The transmit-
ted signal reaches the receiver by undergoing many effects, corrupting the signal, and
often placing limitations on the performance of the system.
Figure 1.1
illustrates a wireless communications system that includes some of the
effects of the radio channel. The received signal strength varies depending on the dis-
tance relative to the transmitter, shadowing caused by large obstructions, and fading
due to reflection, diffraction, and scattering. Mobility of the transmitter, receiver, or
scattering objects causes the channel to change over time. Moreover, the interference
conditions in the system change rapidly. Most important of all, the radio channel is
highly random and the statistical characteristics of the channel are environment depen-
dent. In addition to these changes, the traffic load, type of services, and mobile user
characteristics and requirements might also vary in time. Adaptive techniques can be
used to address all of these changing conditions.
The adaptation strategy can be different depending on the application and ser-
vices. Constant BER constraint for a given fixed transmission bandwidth and constant
throughput constraint are two of the most popular criteria for adaptation. In constant
BER, a desired average or instantaneous BER is defined to satisfy the acceptable quality
Search WWH ::
Custom Search