Digital Signal Processing Reference
In-Depth Information
OFDM Band
Desired signal channel
White noise
Colored noise
Frequency
FIgure 1.6
Representation of OFDM frequency channel response and noise spectrum. Spec-
trums for both white and colored noise are shown.
Note that since both the desired signal's channel and interferer conditions change
rapidly, depending on the application, both short-term and long-term estimates are
desirable. Long-term estimates provide information on long-term fading statistics due
to shadowing and lognormal fading as well as average interference conditions. On the
other hand, short-term estimates provide measurements of instantaneous channel and
interference conditions. Applications like adaptive channel assignment and handoff
prefer long-term statistics, whereas applications like adaptive demodulation, adaptive
interference cancellation, etc., prefer short-term statistics.
For some applications, a direct measure of channel quality from channel estimates
would be sufficient for adaptation. As mentioned above, channel estimates only provide
information about the desired signal's power. It is a much more reliable estimate than
RSS information, as it does not include the other impairments as part of the desired
signal power. However, it is less reliable than SNR (or SINR) estimates, since it does not
provide information about the noise or interference powers with respect to the desired
signal's power.
Channel estimation for wireless communications systems has a very rich history. A
significant amount of work has been done for various systems. In many systems, known
information (like pilot symbols, pilot channels, pilot tones, training sequences, etc.) is
transmitted along with the unknown data to help the channel estimation process. Blind
channel estimation techniques that do not require known information transmission
have also been studied extensively. For details on channel estimation for wireless com-
munications systems, refer to [
47
,
48
]
and the
references
listed therein.
1.3.2.3 Measures after Channel Decoding
Channel quality measurements can also be based on postprocessing of the data (after
demodulation and decoding). BER, symbol error rate (SER), FER, and CRC information
are some of the examples of the measurements in this category. BER (or FER) is the ratio
of the bits (or frames) that have errors relative to the total number of bits (or frames)
received during the transmission. The CRC indicates the quality of a frame, which can
be calculated using parity check bits through a known cyclic generator polynomial. FER
can be obtained by averaging the CRC information over a number of frames. In order to
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