1. Field of the Invention
The invention generally relates to an adaptive array antenna-based radio receiver of a base station used in a CDMA communications system and, more specifically, to an antenna signal processing system, provided in such a radio receiver, for receiving reception signals from a plurality (M) of antennas and detecting and extracting a channel signal from each of a plurality (N) of users or mobile stations.
2. Description of the Prior Art
Generally speaking, a user of a cellular radio or mobile telephone system communicates through a base station the service area of which includes the location of the user. Such a base station acquires a channel for communication with each of the terminals or users within the service area of the base station so as to set the environments to enable simultaneous multiple communications. Recently, CDMA (code-division multiple access) is attracting great attention as one of such multiplexing techniques.
In a DCMA system, multiplexing is achieved by using, for a plurality of users, respective different spreading codes. For example, a transmission signal for each of the N users is expressed as:xi(t)=α·ci(t)·di(t)·exp(j2πft),  (1)
where α is a propagation coefficient, ci(t) is a spreading code allocated to an i-th user, ci(t) is a datum to be transmitted, f is the frequency of the carrier wave, and i=1, 2, 3, . . . , N, where N is the number of users the receiver can provide with radio telephone service. However, we usually omit the subscripts, simply denoting, e.g., x(t), c(t) and d(t) except when the discussion involves any relationship between different communications or channels. The data or the value of the transmission signal is updated every unit period Td of time. Similarly, the spreading code c(t) is updated every period Tc of time. The ratio between the data update period Td and the spreading code update period Tc is referred to as spreading gain G. The spreading gain G=Td/Tc is usually so set as to be an integer equal to or more than one.
In a CDMA system, the transmission data signals d1(t), d2(t), . . . , dN(t) of N users served by a certain base station are multiplied by respective spreading codes c1(t), c2(t), . . . , cN(t). For each ci(t) of the spreading codes (or possible channels), a CDMA receiver is provided with a spreading code-matched filter MFi for extracting the data di(t) from the received signal. The extracted signal or the signal, in the base band, passed through each matched filter MFi is given as:yi(t)=α·G·di(t).  (2)
In this way, using matched filters enable simultaneous reception of signals from a plurality of users. Though the number of users served by a base station is limited by the number of spreading codes and the amount of interference among channels, a rapid increase in the number of subscribers of mobile telephone service requires each base station to accommodate more subscribers. In order to cope with this situation, various receivers each incorporating an adaptive array antenna have been proposed so far.
There are reports concerning CDMA receivers with an adaptive array antenna in the following references:    (1) Tanaka, Higuchi, Sawahashi and Adachi, “Indoor Transmission Test Characteristics of DS-CDMA Adaptive Array Antenna Diversity”, IEICE (The Institute of Electronics, Information and Communication Engineers), Radio Communication System Society Technical Report RCS98-53, June 1998, pp. 19-24.    (2) Tanaka, Harada, Sawahashi and Adachi, “Outdoor Transmission Test of Adaptive Antenna Array Diversity Reception in DS-CDMA” IEICE, Radio Communication System Society Technical Report RCS99-10, April 1999, pp. 19-24.    (3) Harada, Tanaka, Ihara, Sawahashi and Adachi, “The Results of Indoor Transmission Test of Adaptive Antenna Array Transmission Diversity in a W-CDMA down link” IEICE, Radio Communication System Society Technical Report RCS99-157, November 1999, pp. 115-121.    (4) Ohgane and Ogawa, “The Adaptive Array and Mobile Communications (II)”, IEICE Trans., Vol. 82, No. 1, January 1999, pp. 55-61.
Also, though various adaptive array algorithms have been proposed so far, the SMI (Sample Matrix Inversion) algorithm, the RLS (Recursive Least Squares) algorithm and the LMS (Least Mean Square) algorithm are better used among others as described in reference (4). The SMI and RLS algorithms, which both involve the calculation of correlation matrices of input signals, are fast in convergence but requires a large amount of calculations, while the LMS algorithm is less in the amount of calculations but slow in convergence. In this connection, all of references (1) through (3) use the LMS algorithm.
FIG. 1 is a schematic block diagram showing a structure of a conventional adaptive array antenna portion in a multi-user CDMA receiver. In FIG. 1, the adaptive array antenna portion 1 comprises M radio portions 10-1 through 10-M which each include an antenna (not shown) constituting an antennal array (not shown), and an antenna signal procession system 20. The antenna signal procession system 20 comprises N adaptive array signal processors 100-1 through 100-N provided for available channels CH1 through CHN or the users supported by the CDMA receiver or the base station including the CDMA receiver (M=4 in this specific example). In each of the radio portions 10, a reception signal received by the antenna is subjected to a frequency conversion and a synchronous detection to become a complex baseband signal xj (j=1, 2, . . . , M), which has an in-phase component as the real part and a quadrature component as the imaginary part. The complex baseband signals x1 through xM (x4 in this example) output from the radio portions 10 are supplied to each signal processor 100-i.
FIG. 2 is a block diagram showing a structure of each adaptive array signal processor 100-i of FIG. 1. It is assumed that the signal processors 100 use above-mentioned SMI algorithm for example. In FIG. 2, the signal processor 100-i comprises M matched filters MFi 111 which are configured to match a spreading code ci(t), an adaptive array weight calculator 112-i, M weight multipliers 113 and a signal combiner 114. The adaptive array signal processors 100-1 through 100-N are identical to each other in structure except that the matched filters MF1 through MFN of signal processors 100-1 through 100-N are so configured as to match respective spreading codes c1(t) through cN(t).
In FIG. 2, i.e., in each signal processor 100-i, the baseband signals x1 through x4 from the radio portions 10 are applied to the matched filters 111 in a one-to-one correspondence and despread into despread signals yi,1, yi,2, yi,3, and yi,1, which are supplied to the adaptive array weight calculator 112-i and to respective one of the M weight multipliers 113.
The adaptive array weight calculator 112-i calculates a correlation matrix Φi and a response vector Ui, and then calculates a weight vector Wi expressed as:Wi=Φi−1·Ui.  (3)where Φi−1 is an inverse matrix of Φi.
The correlation matrix Φi is given by:                               Φ          i                =                  E          ⁢                      {                          [                                                                                                                  y                        1                                            ⁢                                              y                        1                        *                                                                                                                                                y                        1                                            ⁢                                              y                        2                        *                                                                                                                                                y                        1                                            ⁢                                              y                        3                        *                                                                                                                                                y                        1                                            ⁢                                              y                        4                        *                                                                                                                                                                                y                        2                                            ⁢                                              y                        1                        *                                                                                                                                                y                        2                                            ⁢                                              y                        2                        *                                                                                                                                                y                        2                                            ⁢                                              y                        3                        *                                                                                                                                                y                        2                                            ⁢                                              y                        4                        *                                                                                                                                                                                y                        3                                            ⁢                                              y                        1                        *                                                                                                                                                y                        3                                            ⁢                                              y                        2                        *                                                                                                                                                y                        3                                            ⁢                                              y                        3                        *                                                                                                                                                y                        3                                            ⁢                                              y                        4                        *                                                                                                                                                                                y                        4                                            ⁢                                              y                        1                        *                                                                                                                                                y                        4                                            ⁢                                              y                        2                        *                                                                                                                                                y                        4                                            ⁢                                              y                        3                        *                                                                                                                                                y                        4                                            ⁢                                              y                        4                        *                                                                                                        ]                        }                                              (        4        )            where A* is a complex conjugate to A, and E{B} indicates a mean of matrices B for a lot of data samples. It is noted that the subscript “i” of each variable yi,j (j=1, 2, 3, 4) has been omitted in the above expression. In expression (4), each element of the matrix indicates a correlation between signals from matched filters 111. The calculation of the correlation matrix Φi, which involves an averaging for data samples, is usually conducted in a time area in which the radio propagation environment is less changeable. The value of the correlation matrix Φi is updated when the radio propagation environment has changed.
The response vector Ui is calculated by using reference signals included in the despread signals yi,1 through yi,4. Specifically, the weight calculator 112-i filters the signals yi,1 through yi,4 with respective filters each configured to match the reference signals included in the signals yi,1 through yi,4 to obtain filtered signals ui,1 through ui,4, which yields the response vector Ui as follows:                     Ui        =                              (                                                                                u                    1                                                                                                                    u                    2                                                                                                                    u                    3                                                                                                                    u                    4                                                                        )                    .                                    (        5        )            
It is noted that the subscript “i” of each variable ui,j (j=1, 2, 3, 4) has been omitted in the above expression. The calculated vector elements ui,1 through ui,4 is used by the weight multipliers 113 to multiply the despread signals Yi,1 through yi,4, respectively. The output signals from the weight multipliers 113 are combined by the combiner 114 to yield a channel signal zi associated with an i-th user or mobile station.
However, as seen from the above description, if a CDMA receiver is to support N users, then finding N weights requires N calculations for correlation matrices Φ1 through ΦN, N calculations for inverse matrices Φ1−1 through ΦN−1 of correlation matrices, N calculations for response vectors U1 through UN and N syntheses of weight vectors W1 through WN, making a total of 4N calculations. Especially, finding a correlation matrix Φi and finding an inverse matrix Φi−1 each requires a large amount of calculations, accordingly needs a large circuit and a plenty of electric power. This is a serious obstacle to introduction of the adaptive array antenna to mobile communications. Further, if the CDMA receiver is a RAKE receiver that uses a plurality of (e.g., K) radio paths and, for this, executes a weight vector calculation for each of the K radio path, then the overall weight vector calculation requires 4N·K calculations, which requires a larger circuit and more electric power.
Also, since the propagation path can always vary in mobile communications, a CDMA receiver needs a control of tracking the variation. However, the LMS algorithm is disadvantageously slow in convergence of weight vectors W1 through WN, failing to track variations in the propagation path.
Therefore, it is an object of the invention to provide an antenna signal processing system for use in an adaptive array antenna-based CDMA receiver which system can find the weight vectors with a reduced amount of calculations. The CDMA receiver may be a RAKE receiver.
It is another object of the invention to provide an antenna signal processing system for use in an adaptive array antenna-based CDMA receiver which system is fast enough in convergence of weight vectors to track the variations in the propagation path.
It is further object of the invention to provide a CDMA receiver provided with an adaptive array antenna and such an antenna signal processing system.