The results of a study performed to investigate effective, low cost adaptive signal processing techniques for suppressing mutual satellite interference that can arise in a mobile satellite (MSAT) communication system are discussed. The study focused on the use of adaptive sidelobe cancelling as a method to overcome undesired interference caused by a multiplicity of satellite transmissions within the field of view of the ground station. Results are presented which show that the conventional sidelobe canceller produces undesired reduction of the useful signal. This effect is due to the presence of the useful component in the reference antenna element. An alternative structure, the generalized sidelobe canceller (GSC), has been proposed to overcome this difficulty. A preliminary investigation of possible implementations of the GSC was conducted. It was found that at most 8 bits would be required to implement the GSC processor under conditions in which the desired signal-to-interference ratio is 25 dB

Griffiths, Lloyd J.

Satorius, E.

English

NASA Technical Reports Server

N88-25714
ADAPTIVE INTERFERENCE TECHNIQUES
FOR MOBILE ANTENNAS
Prof. Lloyd J. Griffiths, University of Southern California and Dr. E.
Satorius, Jet Propulsion Laboratory
Dept. of EE-Systems, MC 0272
University of Southern California
Los Angeles, CA 90089-0272
ABSTRACT
This paper describes the results of a study which has
been performed to investigate effective, low cost adaptive
signal processing techniques for suppressing mutual
satellite interference that can arise in a mobile satellite
(MSAT) communication system. The study has focussed on
the use of adaptive sidelobe cancelling as a method to
overcome undesired interference caused by a multiplicity of
satellite transmissions within the field of view of the ground
station. Results are presented which show that the
conventional sidelobe canceller produces undesired
reduction of the useful signal. This effect is due to the
presence of the useful component in the reference antenna
element. An alternative structure, the generalized sidelobe
canceller (GSC), has been proposed which overcomes this
difficulty. The GSC requires one additional multiplying unit
(fixed) and one additional summing junction. It is
concluded that the GSC provides an effective means for
suppressing mutual satellite interference. A preliminary
investigation of possible implementations of the GSC has
been conducted. It was found that at most 8 bits would be
required to implement the GSC processor under conditions
in which the desired signal-to-interference ratio is 25 dB.
MSAT COMMUNICATION SYSTEM
For typical operational scenarios involving two or more satellites, mutual
satellite interference (MSI) can degrade the performance of an MSAT
communication system. In the situation where nearby satellite transmissions
cannot be sufficiently isolated from each other (spatially or in frequency),
some form of interference suppression must be incorporated at the various
receiver/transmitter sites to mitigate the effects of MSI. Furthermore, since the
relative geometry between the various transmitter and receiver terminals is
constantly changing, the interference suppression techniques must be
235
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adaptive in order to provide robust performance over a range of system
geometries. The basic geometry of interest is depicted in Figure 1.
Two MSI scenarios are shown corresponding to interference received by
ground stations (on receive) and by the satellites (on transmit). Satellite
transponders are indicated by ($1, $2) while S l(t) and S2(t ) indicate the
desired signal components and 1l(t) and 12(t) denote MSI components.
s (t)
1
$1 $2
2<.1,
M1 M2
a. Mutual interference on receive
$1 $2
S (t)
1
(t)
(t)
S (t)
M1 M2
b. Mutual interference on transmit
Fig.1. Mutual satellite interference between mobile users (M1,
M2) and proximate satellite transponders
Observe that at the earth terminal, desired signals cannot be spatially
distinguished from this interference due to the fact that both components
enter through the mainlobe of the fixed-earth terminal antenna pattern.
ADAPTIVE ARRAYS
The spatial techniques studied are based on adaptive sidelobe cancelling
(SLC). The array is assumed to be narrowband, which is a valid
approximation for MSAT applications. The SLC approach utilizes an
auxilliary antenna element, termed the reference antenna element, which is
subtracted from the primary receiving antenna after appropriate weighting.
The basic configuration is illustrated in Figure 2.
In this system, adaptation consists of adjusting the weight W(n) such that the
output power fyZ2 is minimized- Given that the interference component in the
primary input is highly correlated with the reference input, then the
minimization of output power accomplishes interference cancellation (Widrow,
1975). One simple adaptive method for minimizing lyl 2 is the LMS
236
algorithm (Widrow, 1975). This algorithm ensures that the minimum
possible output power level is obtained for the overall system.
DESIRED_/
PRIMARY '_
Xp
Figure 2.
V
m
ry
X r
l,/.TE.FE.E.OE
'_ REFERENCE
J_ W(n)
Basic MSAT adaptive SLC architecture.
If there is an appreciable amount of desired signal in the reference
channel input, this method will lead to significant signal cancellation at the
output. Effective interference cancellation is achieved only when the ratio of
interference to desired signal is substantially larger in the reference antenna
output than it is in the primary. Although this is the case for the nominal
system, significant amounts of desired signal cancellation can nevertheless
be expected to occur in MSAT geometries.
DESIRED_/
PRIMARY
X
P
Figure 3.
INTERFERENCE
REFERENCE
Generalized sidelobe canceller configuration.
237
The Generalized Sidelobe Canceller (GSLC) method of adaptive
beamforming (Buckley, 1986) offers an approach which overcomes the signal
cancellation effects observed with the basic SLC. The GSLC method utilizes
the fact that a priori information is available regarding the anticipated gain
differences between the desired signal component in the primary and in the
reference beam outputs. This information would normally be available from
the antenna patterns and is employed to combine the output from the two
antennas prior to the adaptive weight, as shown in Figure 3.
The multiplier term _/13between primary and reference is the gain required
to equalize the difference in magnitude observed for the desired response at
the primary and reference antenna outputs. The constant _' represents the
polarization difference and 13is the array gain term.
SIGNAL CANCELLATION EFFECTS
A numerical example was generated using a simple single interference
model and the signal-to-interference power ratio (SIR) at the SLC output was
computed. The example employed corresponded to a typical MSAT
application in which a 19 element primary array pointed toward the desired
signal was assumed. At the output terminals of this antenna, the undesired
interference term is approximately 15dB below that of the desired response
due to the antenna gain. A single-element reference antenna was assumed
such that the gain difference 13between the desired signal observed at the
outputs of the primary and secondary antennas was 13dB.
7O
_C)
f_
Fig. 4.
60 ¸
SO-
40-
20 ¸
lo"
O'
-IO
-40
GSLC,5NR- 20dB
__'_ GSLC,SNR- 10dB
_dB SIR ""-C"-_
SNR - k__
-_o -_o
CROSS POLARIZA_ON FACTOR dB
Adaptive sidelobe cancelling
-'1o o
performance curves.
238
Figure 4 illustrates the results as a function of the magnitude of the cross-
polarization gain factor, J1'l(with the phase of 1' set at 0°), for a typical MSAT
geometry. Two curves (marked SLC) are presented corresponding to two
different values of signal-to-noise ratio (SNR): Os2 / an 2 - 10 dB and 20 dB.
As is seen, the output SIR decreases as the cross-polarization isolation
decreases due to signal cancellation. Note also that over almost the entire
range of IYI, somewhat better SLC performance is obtained at the smaller
SNR values. This is a consequence of the desired signal component which is
present in the reference channel. In fact, a more detailed examination of the
closed form expression for SIR reveals that there exist optimal SNR values for
which the output SIR is maximized.
In analogy with the SLC performance analysis calculations, the SIR at the
GSLC output has been computed as a function of the magnitude of the cross-
polarization factor, IYI (again with the phase of 1' set at 0°). Two curves
(marked GSLC) are presented in Figure 4 corresponding to SNR = 10 dB and
20 dB. In contrast to the SLC performance curves, the GSLC output SIR
remains nearly constant as a function of the cross-polarization isolation.
70-
60-
50-
40-O
I-
OC
30-
20-
I0-
-10
-40
Fig. 5.
SNR - lOdB
-2dB MI SMATCH
25dB SIR ___,_,_
-6dB gl SMAI_
+6dB MISMATCH J
I I I
-30 -20 - 10 0
CROSS POLARIZAI'ION FACTOR OB
Effects of gain mismatch on GSLC performance.
To further understand the performance of the simplified GSLC when the
magnitude of the gain constant, IY 13J, is not known precisely, GSLC
performance curves are presented in Figure 5 corresponding to different
values of gain mismatch. As is seen, at a mismatch of + 2 dB, 25 dB output
SIR is available at the nominal 10 dB cross-polarization isolation level.
239
Comparing the SLC performance curves in Figure 4 with the GSLC curves in
Figure 5 reveals that the GSLC operating with a + 6 dB gain mismatch still
outperforms the SLC near the nominal 10 dB cross-polarization isolation
level. This demonstrates the superior performance of the GSLC in preventing
signal cancellation.
DIGITAL PRECISION REQUIREMENTS
An important consideration in the design and implementation of
digital adaptive sidelobe cancellers is the digital precision (bitwidth) required
to represent the different variables in the weight update algorithm. The
required precision is intimately related to the adaptive step size, #, utilized in
updating the adaptive weight, W(n). In particular, it has been shown (Gitlin)
that the required bitwidth, B, for updating the LMS algorithm must satisfy the
inequality:
2 -B < 2 MIS lYlRMS / IX'IRMS ,
where lYlRMS and IX'IRMS denote the root-mean-square (RMS) voltage levels
of the GSLC output and augmented reference input, respectively, and MIS is
termed the LMS algorithm misadjustment level (Widrow). For typical
implementations, lYIRMS and IX'IRMS will be comparable (i.e., due to AGC
limiting prior to digitization) and thus it is sufficient that 2-Bsatisfy 2 -B < 2
MIS. Therefore, the determination of a minimum bitwidth requirement is
equivalent to specifying a maximum tolerable misadjustment level, MIS. As a
particularly stressing example, if the output signal-to-interference ratio is
assumed to be the desired 25 dB and a fixed-weight, residual white noise
level 30 dB below the desired signal in the GSLC output is assumed, then a
value of MIS = .002 or less will ensure that the total output noise level for the
adaptive system will not exceed 25 dB below the desired signal level in the
adaptive GSLC output, i.e., an increase of no more than 5 dB over the ideal,
fixed-weight GSLC case. This value for MIS corresponds to requiring at least
B = 8 bits. This will most likely represent a worst-case bitwidth specification for
digitally implementing the adaptive GSLC.
REFERENCES
K. M. Buckley, L. J. Griffiths, "An adaptive generalized sidelobe canceller
with derivative constraints," IEEE Trans. Ant. Prop., vol. 34, pp. 311-319,
March 1986.
R. Gitlin, S. Weinstein, "On the required tap-weight precision for digitally
implemented, adaptive, mean-squared equalizers," Bell Syst. Tech. J.
vol. 58, pp. 301-321, Feb. 1979.
B. Widrow, J. McCool, M. Ball, "The complex LMS algorithm," Proc. IEEE,
vol. 63, pp. 719-720, April 1975.
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Adaptive interference techniques for mobile antennas

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