Digital block processor for processing a plurality of transmission channels in a wireless radiotelephony system

A digital block receiver system, in a cellular/wireless FM radiotelephony system, receives and heterodyne a block of cellular/wireless receive channels to a very low block IF signal by analog processing. This block IF signal is applied to a precision high speed A/D converter and converted to a digitized time series. A window function is applied to the digitized time series and a high speed FFT is applied to frequency isolate the individual channels. The active channels are digitally processed by a DSP to recover the FM channel modulation.

FIELD OF THE INVENTION 
This invention relates to wireless telecommunication systems having a 
plurality of communication channels each having a single FM carrier at a 
separate frequency dedicated to that channel. It is particularly concerned 
with the reverse link radio transceiver of such a wireless 
telecommunication system located at a stationary signal radiation site. 
BACKGROUND OF THE INVENTION 
Presently the reverse link signal processors of a wireless telephone 
communication system such as a cell site or a microcell require a separate 
radio transceiver for each transmission channel in service. In a cell site 
serving up to 30 channels, 30 individual transceivers are required. These 
transceivers, designated radio channel units (RCUs), are individually 
expensive and represent a major portion of the cell site or microcell 
cost. Common equipment serving a plurality of channels at RF levels may be 
shared to reduce cost, but separate receiving equipment is required at the 
IF level for each channel. 
SUMMARY OF THE INVENTION 
A digital block receiver system, in a cellular/wireless FM radiotelephony 
system, receives and heterodynes a block of cellular/wireless receive 
channels to a very low IF by analog processing. This block IF signal is 
applied to a precision high speed A/D converter and converted to a 
digitized time series. A window function is applied to the digitized time 
series and a high speed FFT is applied to frequency isolate the individual 
channels. The active channels are processed by a digital signal processor 
to recover the FM channel modulation. 
In particular applications telecommunication channels may encompass analog 
FM voice signals; analog FM supervisory tones; analog FM signalling tones; 
and digital FSK data messages. These channels may, in accord with the 
principles of the invention all be processed as a block. 
A computationally efficient method of separating and demodulating the 
signals of the processed block signal uses the power spectra obtained from 
the Fourier transform output coefficients to recover the frequency 
modulated carrier of each channel. 
In accordance with the invention the instantaneous FM carrier frequency is 
determined by computing the first moment of the Fourier transform power 
spectrum associated with each channel to be recovered. A power masking 
operation may be optionally applied and individual spectra that 
significantly exceed the mask are assumed to be excessively noise 
contaminated and are rejected for purposes of the recovery operation. The 
first moment calculation is repeated without the excessively noisy spectra 
to achieve an improved estimation of the of the instantaneous FM carrier 
frequency.

DETAILED DESCRIPTION 
An illustrative wireless telephone system is shown in the FIG. 1. A mobile 
switching center 101 (MSC) is connected, via a trunk or microwave link, to 
three cell sites 102, 103 and 104. It interconnects these cell sites 
102-104 to a public switched land telephone network 105. Each cell site 
102-104 services a defined geographical service area. The illustrative 
cell site 102 is connected to a microcell 106 located within its service 
area and a picocell (an in building wireless system) serving a building 
107 within the service area. These connections may be implemented using 
fiber optics, metallic wire, point-to-point microwave links or a 
combination of these connections. 
The cell site 102 serves as a macrobase station which provides telephone 
service to personal communication devices of pedestrians 111 and mobile 
radio telephone service to mobile vehicles 112 within its service area. In 
addition it serves as a control center servicing the picocell of building 
107 and microcell 106 (serving the pedestrian 113) and interconnecting 
them to the MSC 101. 
Each of the macrocells 102-104, microcells and picocells includes one or 
more antenna for transmitting and receiving radio signals. Antenna 115 
serves the macrobase 102. Micro cell 106 has the antenna 116. The picocell 
includes in-building antennas (not shown). Voice and data signals are 
received by one or more of these antennas as one or more RF block signals. 
Some receive channels may be dedicated to voice or to data or in the 
general case a channel may handle both voice and data signals. 
An analog FM digital block receiver, receiving the reverse link 
transmission of one of the cell service areas of FIG. 1, is shown in FIG. 
2. Such a radio receiver may be located at the central cell control site, 
microcell location or the picocell location for providing wide area, local 
area and in-building service. The reverse link signals are intercepted by 
one or more antennas 201 connected to the relevant receiving site and 
applied to an analog processing circuit 202. The analog processing circuit 
202 is operative to amplify and filter the received block of channel 
signals and heterodyne the block signal to a low intermediate frequency 
(IF). The low IF is important to limit the required Nyquist sampling rate 
used by the subsequent Analog-to-Digital converter 205. The analog 
circuitry of the block receiver must be highly linear to prevent 
intermodulation products within the block signal that are strong enough to 
limit the dynamic range of the receiver to an undesirable low level. The 
lower edge frequency of the IF block signal must be sufficiently high to 
avoid the folding of low frequency signal energy into the IF block signal 
and thereby limit the receiver's dynamic range. 
The Analog-to-Digital converter 205 converts the IF block signal into a 
digital form comprising a digitized time series. A single 
Analog-to-Digital converter is required for each receive diversity path 
when real demodulation is used. In the event that complex demodulation is 
used, two Analog-to-Digital converters are required for each diversity 
path. The Analog-to-Digital converter 205 must have sufficient accuracy to 
avoid the generation of excessive quantizing noise and intermodulation 
products that would limit the dynamic range of the block receiver. The 
sampling rate must have a sufficiently high frequency to satisfy the 
Nyquist sampling criteria for the highest frequency included in the IF 
block signal. 
The digitized time series output of the Analog-to-Digital converter 205 is 
applied to a window function processor 207 to improve selectively between 
the individual channels in the IF block signal and to enhance FM detection 
performance. In selecting window criteria the effect of a strong signal in 
one channel interfering with a weak signal in an adjacent or nearby 
channel must be considered. An example of such a situation, providing 
acceptable performance, is shown in the graph of FIG. 3. In FIG. 3 with 
the measurement conditions 304, an unmodulated FM carrier at an IF of 900 
KHz is shown having a leakage signal 301 averaged over a channel centered 
at 960 KHz that is 78 dB down from the 900 KHz signal. For a channel 
centered at 990 KHz, the leakage signal 302 is down 81 db. 
The windowed signals are applied to a fast Fourier transform (FFT) 
processor 209. The FFT 209 processes the windowed signals to isolate in 
frequency the individual channels within the received IF block signal. The 
derived FFT parameters are optimized in size (points), span (time) and 
execution rate to enhance FM detection by the FM detector apparatus 211. 
The FM detection apparatus 211 is illustratively a stored program 
controlled processor such as a DSP (digital signal processor). It is 
programmed to recover the FM modulating signal from the FFT output power 
spectra derived from the IF block signal. FM detection is based on the 
fact that the first moment of the FFT power spectra associated with a 
particular channel provides a highly accurate estimate of the FM carrier 
instantaneous frequency for that channel, under modulation and measurement 
conditions to be specified herein below and explained with reference to 
the flow graph of FIG. 16. Because the instantaneous frequency is directly 
proportional to the amplitude of the modulating waveform, the result is a 
highly accurate FM detection process. 
Calculation of the first moment is performed, in response to stored control 
instructions, or by hardwired logic circuitry, for all channels of 
interest that are included in the IF block signal. Calculation of the FFT 
is periodically executed over successive windows of the receiver block 
predetection digitized time series, and a post detection baseband time 
series for each channel of interest is thereby produced. 
Several conditions must be satisfied to achieve a highly accurate and 
sensitive FM detection process. First, in order to achieve an acceptable 
degree of post detection linearity and voice band amplitude flatness, 
detection conditions are selected that provide an effective time span of 
the window preceding the FFT apparatus that is less than 1/4 cycle of the 
highest baseband modulating frequency present that produces peak deviation 
conditions. Here the effective time span is the window width at which 50% 
of the window weighting is obtained. 
Second, the window that precedes the FFT apparatus also must exhibit 
frequency domain sidelobes that are lower than the minimum acceptable post 
detection signal-to-noise ratio. 
Third, in order to further obtain acceptable uncompensated linearity in the 
detected signal the first moment calculation must incorporate power 
spectra that are offset, relative to the channel center frequency, by an 
amount at least equal to the sum of the peak frequency deviation and the 
highest modulating frequency present that produces peak deviation 
conditions. 
Fourth, in order to obtain a highly sensitive FM detection process, the 
first moment calculation must exclude power spectra that are offset, 
relative to the channel center frequency, by an amount that exceeds the 
sum of the peak frequency deviation and the highest modulating frequency 
present that produces peak deviation conditions. For enhanced sensitivity 
the first moment calculation must in addition dynamically reject those 
power spectra that are excessively distorted by noise. 
The first of the above conditions, defining the window effective time span, 
places an upper bound on the highest baseband modulation frequency present 
that produces peak deviation conditions. For the existing North American 
Analog FM FDMA mobile telephone standard (herein after designated 
STANDARD) this frequency is 3 KHz (maximum voice band frequency). The 
rationale for this first condition is graphically shown in the FIG. 4 
which defines the effective window time span 401 and the true and measured 
peak value 402 and 403 of a modulating sinewave. In the calculation of the 
first moment, the instantaneous frequency of the FM carrier is observed 
through the time window. If this instantaneous frequency varies during the 
window span the first moment calculation is an approximation of the 
average instantaneous frequency. As shown in FIG. 4, if the effective 
window 401 is centered at a time corresponding to the true peak 402 of the 
waveform, the instantaneous frequency (ordinate point) estimated will be 
less than the true frequency and a non- linearity will occur. This 
compressive effect is symmetrical in both time and instantaneous frequency 
deviation and therefore produces odd harmonics of the illustrative sine 
wave shown. The 1/4 cycle criterion establishes a threshold which if 
exceeded would cause a rapid reduction in FM detection linearity. 
The graph of FIG. 5 demonstrates the rational for the second condition 
restricting the window sidelobes. As the FM carrier deviates in frequency 
in response to the modulating signal, large deviations may cause power 
spectra to fall in the sidelobe structure of the Fourier transformed 
window. If the frequency sidelobes of the window function are too high, 
the derived instantaneous carrier frequency may be in significant error. 
The error will appear as a noise like ripple 501 and 502 such as is shown 
in the FIG. 5. The fine structure of this noise like ripple 501 and 502 is 
a function of the modulating waveform and the sidelobe structure of the 
window. In the case of the existing STANDARD, applicable to cellular 
radiotelephone systems, the first sidelobe must be maintained at least 65 
dB down in order to achieve acceptable selectivity between adjacent 
channels as illustrated in FIG. 3. This sidelobe level is more than 
adequate to satisfy the second condition. 
To further achieve a high degree of post detection linearity, the third 
condition requires that the first moment calculation be in accord with 
Carson's rule which specifies the minimum bandwidth needed for 
satisfactory FM transmission. 
The linearity errors treated by conditions one, two and three are partially 
correlated within the measured instantaneous frequency obtained in the 
first moment calculation. To achieve enhanced linearity, the partial 
correlation property can be exploited by means of an error compensation 
method. The instantaneous frequency estimated error as a function of the 
measured instantaneous frequency can be obtained under typical modulation 
conditions. The estimated error can be stored in a DSP table and used to 
partially correct the measured values. 
To achieve a high degree of FM detection sensitivity, the fourth condition 
restricts the use of power spectra that fall beyond the minimum bandwidth 
established by Carson's rule. For enhanced detection sensitivity, 
excessively noisy power spectra that fall within this minimum bandwidth 
are dynamically excluded from the first moment calculations by means of a 
multipass power masking process. The rationale for the fourth condition 
and a description of the power masking process is provided in the 
specification herein below accompanied by FIGS. 6 through 11 inclusive. 
The power spectra for a 30 KHz channel centered at an IF of 900 KHz is 
shown graphically in FIG. 6 for the measurement conditions specified 611. 
Seven power spectra, 601-607, are associated with the channel. These 
spectra, 601-607, are spaced 7.5 KHz apart and are symmetrical about the 
channel center frequency 610. This graph applies to an unmodulated FM 
carrier. Five of the spectra, 601-605, fall on main lobe 609 of the 
Fourier transformed window while two of the spectra points, 606-607, fall 
at the first null points. In the case of FIG. 6 the estimate of the 
instantaneous frequency is substantially exact. Condition four is, 
however, violated by the two spectra, 606-607, in FIG. 6 that are placed 
7.5 KHz outside the channel boundary. The effect of these two spectra 
606-607, on FM detection sensitivity and linearity is subsequently 
described herein below. 
FIG. 7 illustrates the same measurement conditions 711 shown in FIG. 6 
except that the FM carrier is modulated at a low rate and the 
instantaneous frequency is shifted to a point 12 KHz below the center 
frequency. As before the power spectra 701-707 are fixed in frequency, but 
now the points have shifted along the Fourier transform of the window as 
it follows the movement of the modulated FM carrier. Two of the spectra, 
706-707, in FIG. 7, shift into the window sidelobe structure but the error 
is negligible because the sidelobes are very low as specified under 
condition two. However, the first moment calculation does exhibit a slight 
error because the number of spectra, 701-707, associated with the channel 
have been limited to seven. Hence the first moment calculation of the 
instantaneous frequency will be slightly higher than the actual 
instantaneous frequency, but this error is so slight that the modulated 
signal may be substantially recovered. 
The relationship between the FM detection linearity and the use of spectra 
beyond the FM carrier peak frequency deviation is shown graphically in the 
FIGS. 8 and 9 representing in both figures intermodulation products, 801, 
802, and 901, 902, resulting from a two tone test. In both FIGS. 8 and 9 
the test conditions are in compliance with the first, second and third 
conditions and with the conditions specified 803 in FIG. 8. FIG. 9 is in 
compliance with condition four, while FIG. 8 is not. FIG. 8 shows two 
voice band tones and associated intermodulation products using seven power 
spectra and FIG. 9 shows the voice band response using five power spectra. 
It is readily apparent from comparison of these graphs that the FM 
detection linearity is highly sensitive to the use of power spectra at or 
beyond the channel edges in accordance with condition three. It is also 
apparent from FIG. 9, that when five power spectra are used in compliance 
with all four of the conditions, acceptable telecommunications quality 
linearity will be achieved. 
As indicated herein above, with respect to the fourth condition, the first 
moment calculation can be repeated to constitute a multi-pass operation. A 
single pass operation is operative, but only when full FM detection 
sensitivity is not required. In situations requiring a higher degree of 
sensitivity, the first moment calculation is repeated one or more times. 
In the multiple pass operation the power spectra are dynamically tested to 
determine if they are excessively corrupted by noise or interference. If 
such is the case they are excluded from first moment calculations. 
The first pass FM detection process produces an estimate of the FM carrier 
instantaneous frequency based on the first moment of the power spectra 
associated with the channel. If no additional passes are performed this 
first pass estimate becomes the final estimate. 
For performing additional passes, a power spectra mask is generated based 
on the instantaneous carrier frequency estimate of the previous pass and 
the local mean power of the spectra located adjacent in frequency to the 
previous estimate. 
For a very low baseband modulation frequency or very low frequency 
deviation conditions, the power spectra will fall on the main lobe contour 
710 or in the sidelobe region as shown in the FIG. 7. This contour 710 is 
the Fourier transform of the window function. Under differing modulation 
conditions the contour 710 may be spread in width, but will continue to 
follow the movement of the FM carrier is accordance with the amplitude of 
the modulating waveform. 
This contour 710 can be simulated under maximum width or spreading 
conditions in a noise free environment. These conditions include (1) the 
modulating waveform is a sinewave that produces the maximum allowed peak 
frequency deviation, (2) the modulating waveform is a sinewave with 
frequency at the maximum value permitted for those signals that produce 
the maximum allowed peak frequency deviation, and (3) the FM carrier is 
experiencing its maximum rate of change of frequency. For a sinewave 
modulating signal the maximum rate of change occurs at zero crossings of 
the sinewave. 
Under the STANDARD the peak frequency deviation is +/-12 KHz and maximum 
voice band frequency is 3 KHz. A parabolic-like mask 1002 in conformity 
with the preceding conditions is illustrated in the FIG. 10. In the 
illustrative example of FIG. 10 the maximum value 1001 of the power mask 
1002 is centered on the estimate 1003 of the instantaneous frequency 
obtained from the previous pass, and the average power of the spectra 
located adjacent to the estimate of the instantaneous frequency obtained 
from the previous pass. Four spectra, 1011-1014, are used to obtain the 
average power and seven spectra, 1011-1017, are associated with the 
channel. In the illustrative example the FM carrier to noise ratio is +5 
dB; the signal is highly corrupted by noise. 
An empirically derived threshold 1022 is established above the mask 1002 
and individual spectra, 1016 and 1017, exceeding this value are rejected 
in recalculations of the first moment. In the illustrative example of FIG. 
10, this threshold 1022 is set 13 dB above the mask 1002 in order to 
counter the effect of noise corruption of the mask position and to assure 
that rejected spectra, 1016 and 1017, are significantly corrupted by 
noise. The two highly corrupted spectra, 1016 and 1017, located at and 
just below the lower edge of the channel are rejected and do not bias the 
second pass first moment calculation. Hence the estimate of the FM carrier 
instantaneous frequency increases in accuracy at designated point 1018 and 
the FM detection process is now considerably more sensitive. 
A typical voice band signal to noise ratio (S/N) versus IF carrier to noise 
ratio (C/N) characteristic is shown in the graph of FIG. 11, for 
conditions corresponding to the STANDARD. In the seven spectra per channel 
example the two pass FM detection process is 5 dB more sensitive than the 
one pass process at C/N=10 dB. The use of two passes and five spectra, in 
compliance with all four conditions, results in the most sensitive FM 
detection process characteristic 1101 illustrated. 
Post detection amplitude response, as a function voice band modulation 
frequency, is illustrated in the graph of FIG. 12. The response 
characteristics for the SAT and ST signals used in the STANDARD are shown 
by points, 1211 and 1212, on the curves, 1201 and 1202, corresponding to 
peak FM deviations at 2 KHz and 8 KHz, respectively. 
The amplitude roll off of FIG. 12 is caused by the same compression effects 
described under conditions one, two and three. The compression is a source 
of non-linearity, but it also affects the amplitude of the fundamental 
modulating frequency. As shown in FIG. 12, the effect of condition one is 
the dominant source of compression and amplitude roll off above a baseband 
modulation frequency of approximately 3 KHz. Above the 8.5 KHz threshold 
1215, the 1/4 cycle rule of condition one is violated; the amplitude 
response is approximately 3 dB down at this frequency. The indicated 
measurement conditions 1205 apply to FIG. 12. 
The baseband sampling rate is established by the FFT execution rate. This 
rate is determined by the Nyquist sampling criterion and must be high 
enough to avoid aliasing of the baseband modulating signal. Under the 
STANDARD, Manchester encoded blank and burst FSK data messages are sent 
from the mobile to the block receiver. These messages have a symbol width 
of 50 microseconds and at least one baseband sample is required per symbol 
for proper decoding. If the channel sample time is phase locked to the 
symbol phase, an FFT execution rate of 20 KHz is satisfactory. However 
since the individual mobiles transmit asynchronously with respect to each 
other, a sampling rate of at least 30 KHz is required and the FFT 
execution rate must satisfy this requirement. 
While the FFT must operate for all the diversity paths only the selected 
path must be processed at the full execution rate required to decode the 
Manchester encoded data messages. For non-selected diversity paths, the 
FFT execution rate must only satisfy the need to measure receive signal 
strength amplitude or quality at a rate consistent with airwave 
telecommunication system fading statistics. For the STANDARD a non- 
selected diversity path FFT execution rate of less than 5 KHz is adequate 
and the FFT processing load can be sized accordingly. 
The STANDARD uses receive signal strength as the basis for diversity path 
selection. However, with multi-pass FM detection, a channel quality 
measurement can be established based on the percentage of spectra rejected 
by the power mask. Rejection statistics can be used to estimate the 
channel C/N characteristics as shown in FIG. 15 for the measurement 
conditions 1501 indicated. 
In this figure, the power mask rejection statistics for a threshold of +7 
dB are shown for the two modulation conditions that bound the accuracy of 
the C/N estimate. At a given C/N, rejected spectra are minimized, as per 
characteristic 1511, for an unmodulated FM carrier. Rejected spectra, as 
per characteristic 1512, are maximized when the FM carrier is modulated at 
the highest modulation frequency that produces the maximum allowed peak 
deviation and at an amplitude that produces the peak deviation. For the 
conditions of FIG. 15 the C/N can be estimated to an accuracy of 
approximately +/-2 dB in the low C/N region of interest. 
The measure of channel quality can be used as the basis for selecting the 
best diversity path based on the most favorable C/N ratio rather than 
carrier strength alone. This method will result in better diversity 
selection performance under co-channel or adjacent channel interference 
conditions and will create a new parameter to assist in cellular mobile 
handoff decisions. 
In addition, the measurement of channel C/N in the selected diversity path 
can be used to mitigate the interference or impulsive noise that is heard 
during multipath propagation induced Rayleigh fading conditions. The use 
of estimated C/N is beneficial when the FM carrier drops to a level near 
or below the level of channel noise or interference. For Rayleigh fades 
that do not fall as far as the noise or interference floor, impulsive 
noise may be induced as the result of a 180 degree phase rotation that 
typically occurs at the cusp or null of the fade. The 180 degree phase 
rotation produces impulsive noise with a magnitude that is highly 
correlated with the first derivative of the FM carrier amplitude. The 
instantaneous carrier amplitude is measured at the FFT execution rate as a 
pan of the multipass FM detection process 1608 (as shown in FIG. 16). A 
combination of spectra rejection statistics and carrier amplitude first 
derivative measurements can be used to identify when impulsive noise is 
present and therefore when mitigation methods should be applied. 
Mitigation can consist of a full or partial muting during the normally 
brief periods when interference or impulsive noise is present. As an 
alternative to muting, a low level of subjectively pleasing white 
background noise may be inserted during the critical pan of the fade. 
The equation for computing the first moment of the windowed FFT power 
spectra is; 
##EQU1## 
WHERE 
EQU P.sub.k =I.sub.k.sup.2 +Q.sub.k.sup.2 
and where: 
k is an index number for individual spectra; 
N is the total number of power spectra associated with a specific channel; 
P.sub.k is a specific power spectra 
I.sub.k is a real component of the Fourier coefficient; 
Q.sub.k is the imaginary component of the Fourier coefficient; 
F.sub.0 is the reference frequency for the first moment calculation; 
Offset.sub.k is the difference between the frequency of P.sub.k and 
F.sub.0. 
In general the process of the first moment calculation is encompassed by 
the following process steps. (1) Initially form all the P.sub.k 
=I.sup.2.sub.k +Q.sup.2.sub.k values for k=1 to N. This requires 2N 
multiples and N adds. (2) Form all F.sub.0 +Offset.sub.k values for k=1 to 
N. This requires N adds and subtracts. (3) Form all (F.sub.0 
+Offset.sub.k) P.sub.k values for k=1 to N. This requires N multiples. (4) 
Form the dividend summation. This requires N-1 adds or subtracts. (5) Form 
the divisor summation. This requires N-1 adds. (6) Form the quotient using 
1 divide. These processes comprise 4N-2 adds or subtracts, 3N multiples 
and one division. 
In order to enhance the process efficiency of the first moment calculation 
the selected power spectra, 1301-1305, or 1311-1314, may be specially 
placed with respect to the channel edge frequency boundaries 1321 and 
1322. The power spectra, as shown in the diagram of FIG. 13, are evenly 
spaced and placed symmetrically with respect to the center frequency of 
the channel. If N is odd a power spectra 1303 is placed at the channel 
center frequency 1323. In addition, the power spectra placement relative 
to the channel boundaries is the same for all channels of interest in the 
received block signal. 
For the STANDARD, channels are of equal width and all channel frequency 
centers are evenly spaced from one another. The FFT produces evenly spaced 
power spectra; the desired spectra spacing is established by the ratio of 
the Analog-to-Digital sample rate to the FFT size in points. The placement 
of power spectra that is the same for all channels is accomplished for 
these conditions if the ratio of channel center spacing to power spectra 
spacing is an integer. The placement of power spectra symmetrically with 
respect to the channel center is accomplished under the preceding 
conditions by selecting a block receiver IF such that any channel center 
1323 coincides with a power spectra 1303 (N odd) or is exactly between two 
spectra, 1312 and 1313, (N even). 
The first moment calculation computational efficiency is significantly 
enhanced for the preceding arrangement of spectra and channels. The 
calculation process comprises the steps of; (1) Form all P.sub.k 
=I.sup.2.sub.k +Q.sup.2.sub.k for k=1 to N. This requires 2N multiplies 
and N adds. (2) Because the power spectra are uniformly spaced in 
frequency, the F.sub.0 +Offset.sub.k terms need not be computed. F.sub.0 
is set at the channel center and F.sub.0 +Offset.sub.k is normalized by 
the uniform spacing to a predetermined integer. (no calculation needed for 
this step) (3) The (Integer.sub.k)P.sub.k product is replaced by adds or 
subtracts in the next step. (4) The dividend summation is formed by adding 
the power spectra corresponding to normalized offsets +/-1 once; offsets 
+/-2 twice, offsets +/-3 thrice, etc. for all power spectra associated 
with the channel. This requires the following adds or subtracts 
(N.sup.2 -5)/4; for N odd; N&gt;=3 
(N.sup.2 -2)/2; for N even; N&gt;=2 
(5) Form the divisor summation. This requires N-1 adds or subtracts. and 
finally (6) form the quotient using 1 divide. 
For N odd this totals; 
(N.sup.2 +8N-9)/4 adds or subtracts, 2N multiples and 1 divide. 
For N even this totals; 
(N.sup.2 +4N-4)/2 adds or subtracts, 2N multiples and 1 divide. The 
advantages achieved in computational efficiency are summarized in the 
table of FIG. 14. 
The overall methodology or flow process for the FM detection process is 
illustrated in the flow diagram of FIG. 16. In block 1601 the channel of 
interest is selected and in subsequent block 1602 the first moment 
calculation is performed in accord with the above description. In the 
block 1603 the estimation of instantaneous frequency is limited to the 
maximum value known to have been transmitted. The number of passes 
completed is compared, as per block 1604, to the number of passes 
required. The number required may be fixed or may adaptively be a function 
of the recent history of the estimated C/N as described with reference to 
FIG. 15. If one or more additional passes are required, the process flow 
proceeds to block 1606, and the required mask processing is initiated. If 
the number of passes required is satisfied, the instantaneous frequency is 
stored in memory, as per block 1605, and the next channel to be processed 
is selected. 
For the mask processing of block 1606, an index is computed for the spectra 
based on the preceding estimation of the instantaneous frequency. This 
index is used to access a table of mask and threshold values that have 
been prestored in a memory device. A count of remaining spectra is 
maintained in block 1607 and instructions of 1606 are invoked repeatedly 
until all spectra associated with the channel have been processed. A local 
mean power value is computed in block 1608 for those spectra nearest the 
preceding estimate of the instantaneous frequency. The sum of the mask and 
threshold values relative to the local mean power is computed for each 
spectra. In block 1609, each spectra is compared with the sum of the mask 
and threshold values as adjusted in accord with the local mean power. 
Spectra are marked as accepted or rejected is accordance with this 
comparison in the step of block 1609. The process flow proceeds to block 
1002 and the process is continued. 
Following the FM detection step, the diversity path with the best quality 
is selected, in selection circuitry 213, based on an estimation of the 
carrier to noise ratio for each diversity path. The C/N is estimated from 
the power spectra rejection rate experienced as a pan of the multipass 
detection process. For purposes of establishing the highest quality 
diversity path, the power mask threshold need not be set at the same level 
as used for optimum FM detection. 
Following diversity selection, the digitized time series highest quality 
path for channels of interest in the block is subjected to the expansion 
step associated with channel companding, in the expand - de- emphasis 
circuitry 215. The expanded signal is conventionally processed, in a 
detection circuit 217, to detect the individual baseband modulating 
signals that may be present. Voice processing, in the de-emphasis 
circuitry 215 and the detection circuitry 217, includes digital low pass 
filtering and decimation to shape the voice band amplitude response in 
accordance with the de-emphasis function and to remove signal and noise 
content above the voice band. For the STANDARD, conventional signal 
processing techniques are used to identify the specific SAT frequencies 
that may be present, and to identify the presence or absence of ST and 
decode Manchester encoded data messages. Because of the asynchronous 
characteristic of these encoded data messages, over sampling is required 
and interpolation of two samples that may fall within a symbol will be 
necessary. 
The information content of decoded data messages, SAT, ST as well as 
digitized voice is formatted for transmission by means of a digital data 
link interface 219 to a control location such as a cell site or macrobase 
221. The interface will be modular and capable of supporting metallic, 
fiber, microwave or a combination of these transmission media. For cases 
where the block receiver is located at a cell site or macrobase, the 
interface is directly established with the digital bus structure of the 
site.