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Description  |
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TECHNICAL FIELD
The present invention relates to a receiving method which is applied, for
example, to mobile communications and by which a base station receives
from L (where L is an integer equal to or greater than 2) communicators
signals spectrum-spread by short- and long-period spreading code sequences
and separates at least one of the received signals and, more particularly,
to a receiving method which subjects a despreading code sequence of the
received signal to decorrelation to obtain an interference-cancelled
despread output.
PRIOR ART
Because of excellent interference resistance and security protection
features of spread spectrum communication techniques, a code division
multiple access (CDMA) communication system employing the spread spectrum
communication scheme is now being studied more and more actively toward
practical utilization in various communication systems. A problem of the
CDMA system is a near-far problem that the power of a signal received by
the district center greatly varies with the location of the communicator.
In the CDMA system, since a plurality of communicators share the same
frequency band, a signal transmitted from one of them becomes an
interference wave which degrades the speech quality of a transmitted
signal from another communicator.
For example, when a communicator near the base station and a communicator
at a remote place simultaneously conduct communications, the signal from
the former is received by the base station at a high power level, whereas
the signal from the latter is received at a low power level. This means
that the communication between the communicator at the remote location and
the base station is seriously degraded by interference from the
communication with the nearby communicator. As a solution to this near-far
problem, there has been studied a transmitter power control scheme. With
the transmitter power control scheme, the power of the signal that the
receiving station receives, or the signal power versus interference power
ratio which is determined by the received power, is controlled to be
constant regardless of the location of the communicator, by which uniform
speech quality can be obtained in the service area.
A typical communication system in which the near-far problem constitutes a
main factor of the degradation of characteristics is a mobile
communication system. In W. C. Y. Lee, "Overview of Cellular CDMA", IEEE
Trans. VT, Vol. VT-40, pp. 291-302, 1991, there is analyzed how the ratio
of areas in a zone over which communications can be made with
predetermined speech quality (which ratio will hereinafter be referred to
as a site ratio) is improved by the above-mentioned transmitter power
control in the mobile communication system. Moreover, there has also been
reported a trial calculation that the frequency utilization factor could
be increased up to about 20 times higher than in the North American AMPS
mobile communication system by the implementation of high-speed
transmitter power control responsive to variations of fading which occurs
in radio wave propagation environments of mobile communications (For more
detailed information, see K. S. Gilhousen, I. M. Jacobs, R. Padovani, A.
J. Viterbi, L. A. Weaver, Jr. and C. E. Wheatly III, "On the Capacity of a
Cellular CDMA system," IEEE Trans. VT, Vol. VT-40, pp. 303-312, 1992).
However, the site ratio after the transmitter power control is greatly
affected by control errors which are caused by various factors. For
example, in E. Kudoh and T. Matsumoto, "Effect of Transmitter Power
Control Imperfections on Capacity in DS/CDMA Cellular Mobile Radios,"
Proc. of IEEE ICC '92, Chicago, pp. 310.1.1-6, 1992, there is discussed
the influence of control error on the relative frequency utilization
factor in the aforementioned mobile communication system. This literature
states that a 1 dB control error would decrease the relative frequency
utilization factor down to 29% (up link) and 31% (down link).
On the other hand, Ruxandra Lupas and Sergio Verdu at Princeton University
of the United States have recently revealed, with respect to a binary
asynchronous CDMA system which is exposed to additive Gaussian noise, the
class of a linear filter which permits the estimation of transmitted
signals from signals received from respective communicators even if the
received signals differ in power. The filter of this class is called an
inverse-correlation filter. The amount of processing or throughput of this
inverse-correlation filter increases only in proportion to the number N of
simultaneous communicators and does not markedly increase exponentially.
This is disclosed in R. Lupas and S. Verdu, "Near-Far Resistance of
Multiuser Detectors in Asynchronous Channels," IEEE Trans. COM, Vol.
COM-38, pp. 496-508, 1990 (hereinafter identified as Literature 1).
Another effect or advantage of the application of the CDMA scheme to the
mobile communication system, other than the enhancement of the frequency
utilization factor, is to make code-management-free communications a
reality. That is, in order that the interference power from another
communicator using the same frequency or the same time slot (hereinafter
referred to as the same channel) may be kept below a predetermined level,
a conventional FDMA or TDMA system reuses the same channel in a plurality
of zones that are far enough apart from one another to avoid interference.
To perform this, the conventional FDMA or TDMA system requires channel
management for controlling the same channel interference. The channel
management includes optimization as to how the service area is split into
zones, as to how many channels are assigned to each zone and as to in
which zone each channel is reused. This inevitably makes it difficult for
a plurality of operators to operate different systems, using a certain
frequency band.
In the case of the CDMA system, the "channel" corresponds to a spreading
code. Accordingly, the magnitude of interference from a different channel
corresponds to the magnitude of the cross correlation between spreading
codes. Since the cross correlation between spreading codes does not become
completely zero with respect to a plurality of spreading codes which are
used in a given zone and a zone adjacent thereto, each channel in these
zones suffers interference by other channels. In the CDMA system employing
the spread spectrum communication scheme, such interference on the given
channel by all the other channels of the same and other zones is regarded
as equivalent noise and, in the course of despreading the received signal,
a desired signal is extracted from their combined signal. In other words,
as long as the interference from other communicators is regarded as the
equivalent noise, there is no distinction between interference from the
inside of the zone and interference from the outside of the zone. That is
to say, a spreading code assignment problem does not arise in a mobile
communication system which is designed to regard the interference from
other communicators as equivalent noise. Hence, the code-management-free
communication system can be realized. It is also possible for a plurality
of operators to operate different systems through the use of the same
frequency band when the systems are each designed to regard interference
from other communicators as equivalent noise.
Then, in order to make it possible to regard interference from other
communicators as equivalent noise, it is necessary to thoroughly randomize
the spreading code sequence. This can be implemented by spectrum spreading
with both of a short-period spreading code sequence whose period is the
time length of one of information symbols to be transmitted and a
long-period spreading code sequence whose period is the time length
corresponding to a plurality of information symbols. In this instance, the
short- and long-period spreading code sequences have the same chip rate,
and the spectrum spreading with both spreading code sequences is
accomplished by multiplying the long-period spreading code sequence for
each chip after normal spreading with the short-period spreading code
sequence, or by spreading with the short-period spreading code sequence
after spreading with the long-period spreading code sequence.
It is also possible, theoretically, to configure the aforementioned
decorrelator in a system which performs the spectrum spreading with the
short- and long-period spreading code sequences as mentioned above. In the
past, however, no concrete method has been proposed therefor.
An object of the present invention is to provide a code division multiplex
signal receiving method by which the base station receives a plurality of
asynchronous CDMA signals spread-spectrum with the short- and long-period
spreading code sequences and detects the signal received from each
communicator through inverse-correlation filtering.
DISCLOSURE OF THE INVENTION
The receiving method according to the present invention is a code division
multiplex signal receiving method which receives from L communicators, L
being an integer equal to or greater than 2, signals each spectrum-spread
with the short- and long-period spreading code sequences and separates at
least one of the received signals; the receiving method comprises the
following steps:
(a) said received signals are despread with spreading code sequences for
said L communicators, respectively, to obtain L despread output sequences;
(b) partial correlation matrixes R.sup.k+h (1), R.sup.k+h (0) and R.sup.k+h
(-1) in L.times.L dimensions, representing the cross correlation of the
spreading code sequences of said L communicators at respective symbol
timings in the range of from (k-g)th to (k+g)th ones of k symbol timings,
are calculated for h=-g, . . . , 0, . . . , g, k being a given integer and
g a fixed constant equal to or greater than 1, then a correlation matrix
R.sub.k in the range of said symbol timings, defined by the partial
correlation matrixes, are generated and its inverse or negative
correlation matrix R.sub.k.sup.-1 is calculated;
(c) said inverse correlation matrix R.sub.k.sup.-1 is multiplied by vectors
of said L despread output sequences at said (k-g)th to (k+g)th symbol
timings, obtained in said step (a); and
(d) a decision is made of a symbol with respect to the results of said
multiplication corresponding to at least one of said L communicators in
said step (c).
In the above receiving method, the process of calculating said inverse
correlation matrix R.sub.k.sup.-1 at each symbol timing k+1 after the
symbol timing when said inverse correlation matrix was calculated in said
step (b) comprises the following steps:
(i) partial correlation matrixes R.sup.k+g (-1) and R.sup.k+g+1 (0) and the
inverse correlation matrix R.sub.k.sup.-1 calculated at the symbol timing
k are used to generate from said inverse correlation matrix an inverse
correlation matrix R.sub.k,k+1.sup.-1 extended by one symbol timing; and
(ii) said inverse correlation matrix R.sub.k.sup.-1 at the symbol timing
k+1 is calculated from said extended inverse correlation matrix
R.sub.k,k+1.sup.-1.
The present invention takes into consideration only the influence of the
information symbol vector at the k-th symbol timing on the despread output
vectors preceding and succeeding it, that is, only a period of time for
sufficient convergence of the intersymbol interference and neglects the
other symbol timings, thereby permitting the detection of the information
symbol through decorrelation.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a timing chart showing transmission symbol sequences by a
plurality of communicators.
FIG. 2 is a diagram showing a determinant indicative of the relationship
between transmission symbol sequences by a plurality of communicators,
taking into account the cross correlation of spreading code sequences, and
despread outputs of the corresponding received signals.
FIG. 3 is a diagram showing a determinant indicative of the relationship
between transmission symbol sequences and despread outputs of the received
signals on which the present invention is based.
FIG. 4 is a block diagram illustrating the configuration of a transmitting
side device for spread spectrum communications utilizing short- and
long-period spreading code sequences.
FIG. 5 is a block diagram illustrating an example of the configuration of a
receiving device embodying the present invention.
FIG. 6 is a graph showing one example of the results of simulations on the
reception by the method of this invention and a conventional method.
FIG. 7 is a graph showing another example of the results of simulations on
the reception by the method of this invention and a conventional method.
BEST MODE FOR CARRYING OUT THE INVENTION
The weightiest reason for which it is difficult to construct a decorrelator
for the asynchronous CDMA system employing the short- and long-period
spreading code sequences is that the cross correlation between the two
sequences varies with time (or for each symbol). That is, in a CDMA system
using only the short-period spreading code sequence, the cross correlation
to another received signal in one symbol duration becomes the same for
each symbol, but in the case where the received signal is spread by the
long-period spreading code sequence, the cross correlations in respective
symbol durations in the period of the long-period spreading code sequence
differ from each other and vary. Now, consider the case where a base
station simultaneously communicates with L (L being an integer equal to or
greater than 2) communicators in asynchronous CDMA environments. It is
understood from the aforementioned Literature 1 that vectors of despread
outputs of received signals from the respective communicators in the
receiving device of the base station, arranged in order of reception,
Y=[. . . y(k-2),y(k-1),y(k),y(k+1),y(k+2). . .].sup.t
is given by Eq. (1) shown in FIG. 1. In the above, y(k) indicates vectors
of despread outputs y.sub.i (k) obtained by despreading the received
signals from the respective communicators at the k-th symbol timing with
both short- and long-period spreading codes in respective channels and
arranged with respect to i=1 to L; the vectors are expressed by the
following equation:
y(k)=[y.sub.1 (k),y.sub.2 (k), . . . , y.sub.L ].sup.t, k{-.infin.,
.infin.},
where t indicates a transposition. Furthermore, the following is a symbol
vector array:
B=[. . . b(k-2),b(k-1), b(k), b(k+1),b(k+2). . .].sup.t
where b(k)=[b.sub.1 (k),b.sub.2 (k), . . . ,b.sub.L (k)].sup.t is an
information symbol vector at the k-th symbol timing. In FIG. 2 there are
shown at rows #1 to #L information symbol sequences transmitted from
communicators #1 to #L. In this instance, the received power of the signal
from each communicator is normalized to 1 without losing generality.
It is evident that when the received power from each communicator differs,
the information symbol vector b(k) needs only to be replaced by a weighted
vector Wb(k), where the weighting factor W is an L.times.L orthogonal
matrix. n(k)=[n.sub.1 (k),n.sub.2 (k), . . . ,n.sub.L (k)].sup.t is a
noise vector. R.sup.k (0), R.sup.k (1), R.sup.k (-1) are partial
correlation matrixes of the corresponding spreading code sequences of
communicators from #i to #j (where 1.ltoreq.i, j.ltoreq.L) which form a
complex space C.sup.L.times.L in L.times.L dimensions, at the k-th symbol
timing, and elements of these matrixes are given by the following equation
:
R.sub.ij.sup.k (m)=.intg.S.sub.i.sup.k (t-.tau..sub.i)S*.sub.j.sup.k
(t+mT-.tau..sub.i)dt, m=-1,0,1 (2)
where * indicates a complex conjugate, T the symbol length and .intg. an
integration from -.infin. to .infin. of the time t. Furthermore,
.tau..sub.i is a relative delay time of the i-th communicator, which is
set to 0=.tau..sub.1 .ltoreq..tau..sub.2. . . .ltoreq..tau..sub.L <T
without losing generality. These partial correlation matrixes satisfy the
following equation:
R.sup.k (-1)=R.sup.k+1 (1).sup.H
where H indicates a complex conjugate transposition. S.sub.i.sup.k (t) is a
spreading code sequence at the k-th symbol timing of the i-th communicator
(the products of long- and short-period spreading code sequences in that
symbol duration), and it is set to zero except in a symbol duration which
is defined by a time duration [(k-1)T, kT]. Accordingly, the integration
in Eq. (2) needs only to be conducted over the duration [(k-1)T, kT] in
practice. Since the period of the long-period spreading code sequence is
the time length of a plurality of symbols as referred to previously, the
spreading code sequence s.sub.i.sup.k differs for each symbol in a
plurality of symbol durations.
Since the despread outputs Y of the signals from L communicators can be
expressed by Eq. (1), the vector B in which pieces of transmitted
information are arranged in order of reception can be determined by
solving Eq. (1) after determining the vector Y in which the despread
outputs are arranged in order of time. However, Eq. (1) is a linear
equation of an unlimited dimension, and hence cannot directly be solved.
Then, by cutting out only parts influenced by the k-th symbol from
respective terms of Eq. (1) without taking into account the aforementioned
other symbol timings, we have Eq. (3) shown in FIG. 3. In this case, 2g+1
is a period of time within which the intersymbol interference sufficiently
converges, and g needs only to be set to a fixed value in the range of
from 2 to 4, for example; this is called a truncation length. Letting the
despread output vector on the left-hand side of Eq. (3), the partial
correlation matrix (hereinafter referred to simply as a correlation
matrix) on the right-hand side, the symbol vector and the noise vector be
represented by Y.sup.k, R.sub.k, B.sup.k and N.sup.k, respectively, Eq.
(3) can be expressed as Y.sup.k =R.sub.k B.sup.k +N.sup.k. Accordingly,
letting an inverse matrix of the correlation matrix R.sub.k be represented
by R.sub.k.sup.-1, the transmitted symbol vector B.sup.k can be expressed
by the following equation:
B.sup.k =R.sub.k.sup.-1 Y.sup.k -R.sub.k.sup.-1 N.sup.k (4)
In a first embodiment of this invention method, the inverse matrix
R.sub.k.sup.-1 (hereinafter referred to as an inverse correlation matrix)
of the correlation matrix R.sub.k is calculated for each symbol timing and
the despread output vector
Y.sup.k =[y(k-g),y(k-g+1), . . . ,y(k+g-1),y(k+g)].sup.t
is multiplied by the inverse matrix to obtain an estimated vector
B'.sup.k =[b'(k-g),b'(k-g+1), . . . ,b'(k), . . . , b'(k+g-1),
b'(k+g)].sup.t
of the information symbol vector
B.sup.k =[b(k-g),b(k-g+1), . . . ,b(k+g-1),b(k+g)].sup.t
As is evident from Eq. (4), if each element of the noise vector N.sup.k is
sufficiently smaller than the despread output and the truncation length is
sufficiently larger than it, the estimated vector B'(k) can be regarded as
matching the information symbol vector B(k).
Incidentally, since Eq. (3) is a modified form of Eq. (1) which is used to
estimate the information symbol vector b(k), there is no guarantee of
accuracy in estimated values of symbol vectors b(k.+-.1), . . . at the
other symbol timings k.+-.1, k.+-.2, . . . , k.+-.g which are
simultaneously obtained by multiplying the vector Y.sub.k by the inverse
correlation matrix R.sub.k.sup.-1. Therefore, for the estimation of the
symbol vectors b(k.+-.1), . . . , it is necessary that the inverse
correlation matrix of Eq. (3) at other symbol timings be determined for
each symbol timing. However, the matrix R.sub.k is a (2g+1)L by (2g+1)L
matrix; the computation of the inverse matrix of such a large size for
each symbol timing involves a significantly large amount of processing,
and hence is not preferable from the practical viewpoint.
In a second embodiment of this invention method, the computation of the
(2g+1)L by (2g+1)L inverse matrix is performed only once and, at each
subsequent timing, the inverse correlation matrix is updated by the scheme
described below, by which the computational complexity involved is
extremely reduced. This scheme is called a sliding escalator algorithm.
Sliding Escalator Algorithm
Now, assume that the inverse correlation matrix R.sub.k.sup.-1 is preknown.
Consider the determination of an inverse correlation matrix
R.sub.k+1.sup.-1 one symbol timing after that R.sub.k.sup.-1. Referring to
FIG. 3, matrixes, except the upper-left 2gL by 2gL partial matrix (in the
broken-line block 3.sub.k, k+1) of the correlation matrix R.sub.k+1, that
is, one column of the rightmost partial correlation matrix and one row of
the lowermost partial correlation matrix, match the lower-right 2gL by 2gL
partial correlation matrixes in the correlation matrix R.sub.k. Then, a
(2g+2)L by (2g+2)L correlation matrix formulated with parts common to the
correlation matrixes R.sub.k and R.sub.k+1 overlapped, that is, a
correlation matrix R.sub.k, k+1 extended from the correlation matrix
R.sub.k by one symbol timing, is given by the following equation (5):
##STR1##
Here, it is mathematically shown with ease that if the inverse correlation
matrix R.sub.k.sup.-1 is used, the extended inverse correlation matrix
R.sub.k,k+1.sup.-1 could be derived from the right-hand side of the first
equality sign in Eq. (5) as expressed by the following equation:
##STR2##
Furthermore,
s.sub.k =[R.sup.k+g+1 (0)-r.sub.k.sup.H R.sub.k.sup.-1 r.sub.k ].sup.-1(8)
Similarly, the extended inverse correlation matrix R.sub.k,k+1 can be
derived from the right-hand side of the second equality sign in Eq. (5) as
expressed by the following equation:
##STR3##
Moreover,
u.sub.k+1 =[R.sup.k-g (0)-r.sub.k+1.sup.H R.sub.k+1.sup.-1 r.sub.k+1
].sup.-1 (11)
This equation (9) is re-defined as follows:
##EQU1##
Comparing Eqs. (9) and (12),
Q.sub.k+1 =R.sub.k+1.sup.-1 +R.sub.k+1.sup.-1 r.sub.k+1 u.sub.k+1
r.sub.k+1.sup.H R.sub.k+1.sup.-1
q.sub.k+1 =-R.sub.k+1.sup.-1 r.sub.k+1 u.sub.k+1
q.sub.k+1,k+1 =u.sub.k+1 (13)
From this,
Q.sub.k+1 =R.sub.k+1.sup.-1 +q.sub.k+1 q.sub.k+1,k+1.sup.-1
q.sub.k+1.sup.H(14)
Therefore,
Rk.sub.+1.sup.-1 =Q.sub.k+1 -q.sub.k+1 q.sub.k+1, k+1.sup.-1
q.sub.k+1.sup.H(15)
The inverse correlation matrix R.sub.k.sup.-1 is preknown as mentioned
previously. A first step is to calculate partial correlation functions
R.sup.k+g (-1) and R.sup.k+g+1 (0) in Eqs. (7) and (8) through the use of
Eq. (2). On the basis of the results of the calculation, Eq. (6) is
calculated from Eqs. (7) and (8) to obtain an extended (2g+2)L by (2g+2)L
inverse correlation matrix R.sub.k,k+1.sup.-1, and its lower right (2g+1)L
by (2g+1)L partial matrix is obtained as Q.sub.k+1 in Eq. (12).
Furthermore, partial matrixes corresponding to q.sub.k+1.sup.H, q.sub.k+1,
q.sub.k+1,k+1 in Eq. (12) are obtained from an L by (2g+1)L partial matrix
above the above-mentioned partial matrix, a (2g+2)L by L partial matrix at
the left and an L by L partial matrix at the upper left. These partial
matrixes are used to calculate Eq. (15) to obtain the inverse correlation
matrix R.sub.k+1.sup.-1. This is used to calculate R.sub.k+1.sup.-1
Y.sup.k+1 as an estimated value of the symbol vector b(k+1) at the symbol
timing k+1. While the above description has been given of the case of
obtaining the inverse correlation matrix R.sub.k+1.sup.-1 at the symbol
timing k+1 on the assumption that the inverse correlation matrix
R.sub.k.sup.1 at the symbol timing k has already been obtained, this is
exactly equivalent to obtaining the inverse correlation matrix
R.sub.k.sup.-1 at the current symbol timing k on the assumption that the
inverse correlation matrix R.sub.k-1.sup.-1 at the immediately preceding
symbol timing k-1 has been obtained by replacing k with k-1.
Thus, once the correlation matrix R.sub.k-1 in Eq. (3) shown in FIG. 3 is
calculated, the inverse correlation matrix R.sub.k.sup.-1 need not be
calculated directly from the correlation matrix R.sub.k thereafter and can
be updated at each symbol timing through the use of the inverse
correlation matrix R.sub.k-1.sup.-1 and the partial correlation matrixes
R.sup.k+h (0) and R.sup.k+g-1 (-1) at the immediately preceding symbol
timing, by calculating Eqs. (6) and (15). The computation of Eq. (8) for
s.sub.k involves the computation of an L by L inverse matrix and the
computation of an L by L inverse matrix for obtaining q.sub.k+1,k+1.sup.-1
in Eq. (15); however, since the computational complexity for the inverse
matrix computation increases with the cube of the matrix size, the amount
of operation is significantly smaller than that for the inverse matrix
computation of the correlation matrix R.sub.k which is a (2g+1)L by
(2g+1)L.
In the above, the received power from each communicator has been described
to be normalized to 1; when the received power differs with communicators,
it is necessary only to employ a diagonal matrix W using the received
power from respective communicators as diagonal elements and use Wb(k) in
place of the information symbol vector b(k).
In FIGS. 4 and 5 there are illustrated a transmitting device and a
receiving device, respectively, for use in the code division multiplex
communication system embodying the receiving method according to the
present invention. In the transmitting device of each communicator #i, as
shown in FIG. 4, transmission symbol information is fed via an input
terminal 11 to a multiplier 12, wherein it is spectrum-spread by being
multiplied by a short-period spreading code sequence SSC.sub.i fed via a
terminal 13, then the spread output is provided to a multiplier 14,
wherein it is further spectrum-spread by being multiplied by a long-period
spreading code sequence LSC.sub.i fed via a terminal 15, and the spread
output is transmitted as radio waves via a transmitter 16. The period of
the short-period spreading code sequence SSC.sub.i is equal to the symbol
duration T of the transmission information and the period of the
long-period spreading code sequence LSC.sub.i is equal to the duration of
a plurality of transmission symbols. The chips of the two spreading code
sequences are synchronized with each other. The transmission information
may also be spread first by the long-period spreading code sequence
LSC.sub.i and then by the short-period spreading code sequence SSC.sub.i.
The configuration of the transmitting side is the same as in the past.
In the receiving device embodying the present invention, as shown in FIG.
5, spread spectrum signals from L communicators are received by a receiver
21 and the receiver output is fed to a despreader 22, wherein they are
despread by matched filters or sliding correlators 22.sub.1 to 22.sub.L
with spreading code sequences SSC.sub.1, LSC.sub.1 to SSC.sub.L, LSC.sub.L
provided from a spreading code generator 23 in correspondence with the
communicators #1 to #L, at timings t.sub.1 to t.sub.L at which to maximize
the correlation. The despread output vector composed of these L sequences
of despread outputs is outputted for each symbol timing. The despread
output vector at the k-th symbol timing is y(k)=[y.sub.1 (k),y.sub.2 (k),
. . . , y.sub.L (k)].sup.t. This despread output vector y(k) is inputted
into a First-in-First-out register of (2g+1) stages, that is, a shift
register 24, and despread output vectors y(k-g), . . . , y(k+g) are held
in its respective shift stages 24g to 24g and then supplied to a
multiplier 25. The multiplier 25 forms a decorrelator 30, together with a
partial correlation matrix computing part 26 and an inverse correlation
matrix computing part 27.
On the other hand, the spreading code generator 23 generates products
LSC.sub.1.SSC.sub.1, LSC.sub.2. SSC.sub.2, . . , LSC.sub.L .SSC.sub.L of
pairs of long- and short-period spreading codes corresponding to the
communicators #1 to #L and provides them as spreading codes s.sub.1 to
s.sub.L to the partial correlation matrix computing part 26. The partial
correlation matrix computing part 26 computes relative delay times
.tau..sub.1 to .tau..sub.L of all the communicators #i=1, . . . , L on the
basis of timing signals t.sub.1 to t.sub.L fed from the correlator 22 and
computes, by Eq. (2), a partial correlation matrix of every combination
(i,j) of the communicators on the basis of the spreading code sequences
s.sub.1 to s.sub.L fed from the spreading code generator 23. In this
instance, according to the aforementioned receiving method of the present
invention, all partial correlation matrixes R.sup.g+h (1), R.sup.g+h (0)
and R.sup.g+h (-0) at the symbol timings k+h, h=-g, . . . , g are
calculated by Eq. (2) and provided to the inverse correlation matrix
computing part 27. The inverse correlation computing part 27 generates a
correlation matrix R.sub.k composed of all the partial correlation
matrixes, then computes an inverse correlation matrix R.sub.k.sup.-1,
which is inverse from the correlation matrix, and provides it to the
multiplier 25. The multiplier 25 obtains the product of the inverse
correlation matrix R.sub.k.sup.-1 and the despread output vector Y.sup.k
as estimated symbol vector information b'(k-g), . . . , b'(k+g);
respective components b.sub.1 '(k), . . . , b.sub.L '(k) of the vector
b'(k) at the symbol timing k are level-decided by a decider 28 and the
results of the decision are outputted as decoded symbols of the signals
received from the communicators #1 to #L.
In the case of employing the aforementioned sliding escalator algorithm
which is a second receiving method of the present invention, the partial
correlation matrix computing part 26 computes, by Eq. (2), partial
correlation functions R.sup.k+g+1 (-1) and R.sup.k+g (0) in Eqs. (7) and
(8) (assume that k in the equations which will hereinafter be referred to
is replaced with k-1) with respect to combinations of all the
communicators on the basis of the spreading code sequences s.sub.1 to
s.sub.L ; the partial correlation functions thus obtained are provided to
the inverse correlation matrix computing part 27. The inverse correlation
matrix computing part 27 calculates Eqs. (7) and (8), using these partial
correlation matrixes and the inverse correlation matrix R.sub.k-1.sup.-1
obtained with respect to the previous symbol timing k-1. Furthermore, the
computing part 27 calculates Eq. (6) by the use of the results of the
calculations to obtain a (2g+2)L by (2g+2)L extended inverse correlation
matrix R.sub.k,k+1.sup.-1 ; its lower right (2g+1)L by (2g+1)L partial
matrix is set to Q.sub.k, then q.sub.k.sup.H, q.sub.k and q.sub.k,k are
obtained from the upper right L by (2g+1)L partial matrix, the lower left
(2g+1)L by L partial matrix and the upper left L by L partial matrix and
they are used to calculate Eq. (15) to obtain the inverse correlation
matrix R.sub.k.sup.-1. The inverse correlation matrix thus obtained is
provided to the multiplier 25, wherein it is multiplied by (2g+1) despread
output vectors inputted as in the case of the first receiving method.
Then, respective elements of an estimated vector b(k)'=[b.sub.1 (k)',
b.sub.2 (k)', . . . ,b.sub.L (k)'].sup.t in the multiplied outputs are
decided by the decider 28 to obtain outputs from the L communicators at
the k-th symbol timing.
As described above, according to the present invention, signals
spectrum-spread by the short- and long-period spreading code sequences can
also be received through decorrelation.
Next, a description will be given of the results of computer simulations
carried out to demonstrate the effectiveness of the present invention. In
the simulations the primary modulation was BPSK. A Gold sequence (process
gain=31) of a 31-chip length was used as the short-period spreading code
sequence and a Gold sequence of a 511-chip length was used as the
long-period spreading code sequence. g=4 and the number L of simultaneous
communicators was five; provision was made to receive signals from all the
communicators with the same amplitude. The communications were conducted
in an asynchronous CDMA environments.
FIG. 6 shows the results of the simulations, the abscissa representing the
signal power vs. noise power (SNR) after despreading, and the ordinate the
error rate. The black circles indicate the receiving characteristic by the
conventional matched filter, and the white circles indicate the receiving
characteristic by the present invention. The broken line indicates a
theoretical value in the case of a single communicator. The error rate of
the reception by the conventional matched filter which is affected by
interference is appreciably degraded as compared with the error rate in
the case of the single communicator, whereas the characteristic of the
receiving method of the present invention substantially agrees with the
theoretical value in the case of the single communicator.
FIG. 7 similarly shows the results of simulations. In this instance, the
number L of simultaneous communicators is two and the received power of a
second communicator is set higher than that of the first communicator by
10 dB. This situation can be said to be the environment of a typical
near-far problem. The abscissa represents the signal power vs. noise power
(SNR) after despreading for the first communicator and the ordinate
represents the error rate of the first communicator. The black circles
indicate the receiving characteristic by the conventional matched filter
and the white circles indicate the receiving characteristic by the present
invention. As will be seen from FIG. 7, the error rate characteristic of
the matched filter is remarkably degraded as compared with that in the
case of the single communicator by the influence of the near-far problem,
whereas the characteristic by the receiving method of the present
invention is free from the influence of the near-far problem.
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