KR100992432B1 - A combination detection method for wireless communication system with antennea array - Google Patents

A combination detection method for wireless communication system with antennea array Download PDF

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KR100992432B1
KR100992432B1 KR20077017354A KR20077017354A KR100992432B1 KR 100992432 B1 KR100992432 B1 KR 100992432B1 KR 20077017354 A KR20077017354 A KR 20077017354A KR 20077017354 A KR20077017354 A KR 20077017354A KR 100992432 B1 KR100992432 B1 KR 100992432B1
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data
mobile
joint detection
array
channel
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KR20070104570A (en
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양싱싱
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지티이 코포레이션
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station

Abstract

The present invention provides a method for detecting a joint of a wireless communication system used in an antenna array, the method comprising: estimating each antenna channel from each mobile equipment to an antenna array; Estimating each mobile facility beam forming weight; Weighting the received signal to obtain data after forming each mobile beam; And joint detection of each moving facility data using the data after the beam formation. According to the present invention, the joint detection is performed by the weighting method of the beam forming weight, thereby greatly reducing the effect of the joint detection performance drop due to the poor signal synchronization between mobile equipments, and at the same time, the joint detection algorithm is improved by improving the SNR of the output data of the joint detection. Improved performance. In addition, the present invention is simple to implement and has low computational complexity. The present invention also provides a base station that realizes the joint detection method.

Description

Joint detection method and base station for wireless communication system with antenna array {A COMBINATION DETECTION METHOD FOR WIRELESS COMMUNICATION SYSTEM WITH ANTENNEA ARRAY}

The present invention relates to a wireless communication system reception technology based on time division multiplexing (TDD), and more particularly, to a method for performing joint detection on a signal received by an antenna array in a TDD system, and a base station for realizing the method. .

In a code division multiple access (CDMA) communication system, all mobile facilities realize communication using different spreading codes in the same band at the same time. Due to the multipath transmission that exists in the actual radio signal transmission environment, there is a call-interference, or inter-code interference (ISI), between successive transmission codes of each mobile facility. At the same time, since the mobile radio channel can be changed in real time, orthogonality of spread spectrum codes between different mobile equipments cannot be guaranteed by the receiver, and thus interference, that is, multi-address interference (MAI), exists between different mobile equipment codes.

Mobile communication systems generally include two classes of receivers. One class of receivers is conventional mapping filters or RAKE receivers, which determine ISI and MAI as noise in signal transmission. The RAKE receiver can identify different transmission path signals of the same mobile equipment and combine the signals according to specified rules, but the output of the RAKE receiver still contains the MAI. In the mapping filter, since the orthogonality of spreading codes between mobile equipments cannot be guaranteed by the receiver, the output results include both ISI and MAI. Besides, it is necessary to strictly control the power factor (power) since the mapping filter cannot be used to solve the circle / root effect. The second type of receiver acquires the signal transmitted by the mobile equipment using the interference cancellation (IC) method or the joint detection (JD) method using all information of inter-code interference ISI and multi-address interference MAI. The interference cancellation method uses cascade cancellation or parallel cancellation to reduce the " clean " signal of each mobile facility by reducing the multi-address interference MAI signal from the total signal. The joint detection method simultaneously detects all mobile equipment signals using inter-code interference ISI and multi-address interference MAI information. The most preferred joint detection method is the nonlinear Maximum Likelihood Sequence Estimation (MLSE) algorithm, which uses the Viterbi algorithm to detect the optimal firing sequence of K mobile installations.

Figure 112007054770408-pct00001
to be. If there is a large quantity of moving equipment, joint detection cannot be performed in real time. In 1993, Klein and Baier submitted a zero-forcing block liner equalization (ZF-BLE) optimal joint detection algorithm, which greatly reduced computational complexity. The ZF-BLE algorithm completely eliminates the inter-code interference ISI and multi-address interference MAI, that is, reduces the values of ISI and MAI to zero, so the calculation is a zero forcing and no shift estimation. However, among the signal results obtained through the ZF-BLE algorithm, the noise affects the output of the final discrimination circuit due to the color noise, resulting in the performance drop of the ZF-BLE algorithm. Subsequently, Jung et al. Presented a minimum mean square error block equalization (MMSE-BLE) joint detection algorithm, which minimized the error between the estimate and the actual value using the MMSE rule. This algorithm reduces the influence of color noise on the discrimination circuit by allowing the ZF-BLE algorithm to spread through one Wiener estimator and to correlate the noise in the result. Jung et al. Further developed the ZF-BLE algorithm and the MMSE-BLE algorithm to detect the Zero Forcing Block Decision Feedback Equalizer (ZF-BDFE) joint detection algorithm and the Minimum 'Mean Square Error Block Decision Feedback Equalizer (MMSE-BDFE) joint detection. Algorithms were submitted and the performance of the ZF-BDFE and MMSE-BDFE algorithms was superior to that of the ZF-BLE and MMSE-BLE algorithms, but the computational complexity was increased.

Although the joint detection method is superior to the mapping filter method in terms of performance, in the TDD system, the joint detection method is affected by signal synchronization and channel estimation accuracy, so that the signal synchronization between mobile devices is poor or the channel estimation is poor. There is a big impact on the performance of the detection method, which also increases with the increase in the number of mobile installations. Therefore, the problem of overcoming the above disadvantages has emerged as a problem to be solved rapidly in improving the reliability of the joint detection method.

The present invention provides a wireless communication system joint detection method used in an antenna array in order to solve the above problems existing in the prior art, thereby reducing the effects due to poor signal synchronization and channel estimation error of the mobile equipment, joint detection It aims to improve the signal-to-noise ratio (SNR) of the input data.

Another object of the present invention is to provide a base station for realizing the joint detection method.

The present invention provides a wireless communication system joint detection method for an antenna array, the detection method comprising the steps of: estimating each antenna channel from each mobile equipment to the antenna array; Estimating each mobile facility beam forming weight; Weighting the received signal to obtain data after forming each mobile beam; And joint detecting the moving equipment data using the data after the beam formation.

Preferably, the estimating each beamforming weight of the mobile device is realized by any one of a fixed beam search method, a maximum power method, a maximum signal interference ratio method, and an adaptive weight estimation method.

Preferably, in the joint detecting step, generating each mobile equipment composite channel impact response using the channel estimation and the mobile equipment spread spectrum interference code; Weighting the composite channel impact response; And detecting each mobile equipment data using the weighted composite channel impact response and data after the respective mobile equipment beams are formed.

The present invention also provides a base station for realizing a joint detection method, the base station comprising: an RF receiver / transmitter for performing a frequency change under sampling on an antenna array received signal received by a mobile facility; And a baseband processor for performing baseband processing on the sampling data, the baseband processor further comprising: a channel estimator for estimating a channel from each mobile device to each antenna; A weight estimator for estimating the beamforming weight of each mobile apparatus by the estimated channel; And a signal processor for acquiring each mobile equipment data by performing joint detection.

Advantageously, the signal processor further comprises: a first generator for executing a convolutional algorithm on the channel estimate to produce a composite channel impact response; A second generator for generating a weighted composite channel impact response by weighting the beamforming weight with respect to the composite channel impact response; A third generator for generating a system array using the weighted composite channel impact response; A fourth generator for generating an inverse array of the system array; A data waiter that performs weighting of the beamforming weights on the sampling data; A mapping filter for executing a mapping filter on the system array and the post-weighting data; And a fifth generator for generating respective mobile equipment data by the inverse array and the mapping filter result.

1 is a flow chart of a joint detection method of an embodiment of the present invention.

2 is a structural block diagram of a base station for implementing the joint detection method of FIG. 1 according to an embodiment of the present invention.

3 is a perspective view of a signal processor of the base station of FIG. 2.

Detailed description of the preferred embodiments of the present invention in conjunction with the following drawings to make the above object, features and advantages of the present invention.

1 is a flowchart illustrating a joint detection method of an embodiment of the present invention. As shown in FIG. 1, procedure 101 estimates the channel of each antenna from each mobile equipment to the antenna array using the training sequence. Since a wireless communication system generally requires estimating a channel using a training sequence, in this embodiment, all mobile facilities are performed by performing channel estimation on data received using a training sequence already known to each mobile device. Can obtain channel estimates at each antenna. The specific process is as follows. In the wireless communication system, K mobile equipments can communicate, and the base station antenna array includes N antennas, and the training sequence of each mobile equipment is known. The numerical value of the training sequence of all mobiles received in one burst

Figure 112007054770408-pct00002
If we assume

Figure 112007054770408-pct00003

among them,

Figure 112007054770408-pct00004
Is a vector of the channel estimation schemes of all mobile devices of the i th antenna, i.e.
Figure 112007054770408-pct00005
to be. The channel estimate can be obtained through equation (1).

Figure 112007054770408-pct00006

In the CDMA TDD system, the M matrix composed of the training sequences of all mobile equipments can be represented as a cyclic matrix, and thus the equation (1) can be solved by the fast Fourier transform (FFT).

Figure 112007054770408-pct00007

among them,

Figure 112007054770408-pct00008
Denotes all the elements of the first column of the M matrix.

Since the mobile equipment includes the relative position information of the antenna array in the channel estimation, in step 105, the beamforming weight of each mobile equipment can be calculated using the channel estimated by the array signal processing method. The beamforming weight estimation may be any one of a fixed beam search method, a maximum output method, a maximum signal-to-interference ratio method, or an adaptive weight estimation method. The method is a technique already known to those skilled in the art.

In step 110, the data after the beamforming of each mobile device is obtained by weighting the received data using the beamforming weight of each mobile device. Since the beam has a constant width and the side lobe of the beam cannot be completely removed, the data after beam formation cannot be completely determined by the data of one mobile device and is subject to interference from other mobile device data. However, even if there is interference, since the beam is formed, the interference is greatly reduced than the interference before the beam is formed, and the data SNR is improved after the beam is formed. Specifically, the burst data portion received by the ith antenna is an array vector.

Figure 112007054770408-pct00009
In this case, the data portion after the k-th mobile equipment beam is formed

Figure 112007054770408-pct00010

among them,

Figure 112007054770408-pct00011
Is the weight of the i th antenna of the k th mobile installation.

Since the data after beam formation may include interference, the data of each mobile equipment is jointly detected using the data after beam formation. Since the interference between the mobile facilities before the joint detection has already been reduced to the maximum and the SNR of the mobile equipment data has been improved, the performance of the joint detection can be greatly improved. If each mobile device is not in the same beam, there is no effect on joint detection even if the signal synchronization is not good. In addition, even if the beam side lobe or moving equipment is in the same beam, the moving equipment in the beam is reduced, thereby improving joint detection performance.

In this embodiment, joint detection is performed as follows.

In step 115, each mobile facility forms the corresponding composite channel impact response by performing a composite product on the channel estimates for each antenna and the spread spectrum interference code of each mobile facility.

Figure 112007054770408-pct00012
Is the composite channel impact response of the i th antenna of the k th mobile equipment,
Figure 112007054770408-pct00013
, among them,
Figure 112007054770408-pct00014
Is the spread spectrum interference code of the kth mobile equipment,
Figure 112007054770408-pct00015
Is a channel estimate of the i th antenna of the k th mobile equipment.

In step 116, weighting is performed for each mobile composite impact response using the previously obtained beamforming weights of each mobile equipment, and the weighted composite channel impact response.

Figure 112007054770408-pct00016
Where m and k can take different values, and the corresponding formula is

Figure 112007054770408-pct00017

System Array with Weighted Composite Channel Impact Response in Procedure 117

Figure 112007054770408-pct00018
Forming, among which
Figure 112007054770408-pct00019
Is
Figure 112007054770408-pct00020
It is a Toeplitz array. Vector data after beam formation of each mobile equipment
Figure 112007054770408-pct00021
If d is the vector of all symbols fired by all mobile equipment, then the system structural formula is

Figure 112007054770408-pct00022

Figure 112007054770408-pct00023
This variance
Figure 112007054770408-pct00024
In the case of in-Gaussian white noise, the value using the least square method or the maximum likelihood solution is

Figure 112007054770408-pct00025

At the same time,

Figure 112007054770408-pct00026
If is an independent equivalence distribution, the minimum mean squared value (MMSE) is

Figure 112007054770408-pct00027

The above procedure can be used to obtain data for each mobile installation.

By using this embodiment, it is possible to reduce the effect of the joint detection performance drop due to the poor synchronization of the mobile equipment and the channel estimation error, and to improve the performance of the joint detection by improving the SNR of the input data of the joint detection.

2 is a structural block diagram of a base station capable of realizing the joint detection method of FIG. 1 according to an embodiment of the present invention.

As shown in Fig. 2, the base station includes N antenna arrays N RF receivers / transmitters 203A, 203B, ..., 203N composed of N identical Omni antenna units 201A, 201B, ..., 201N; And a base band processor 204. The antenna units 201A, 201B, ..., 201N receive the signals sent by the K mobile equipments, output them to the corresponding RF receiver / transmitters 203A, 203B, ..., 203N, and proceed with sampling to realize frequency change. . All RF receivers / transmitters 203 use the same local source to secure interworking tasks of the same base station RF receiver / sender. Each RF receiver / transmitter includes an analog data converter (ADC) such that all signals output from the RF receiver / transmitter 203 to the baseband processor 204 are data signals, and the RF receiver / transmitter 203 and processor 204 is connected via a high-speed digital bus. The RF receiver / sender 203 sends sampling data to the processor 204 for baseband processing.

The baseband processor 204 includes N channel estimators 207A, 207B, ..., 207N corresponding to N RF receivers / transmitters 203A, 203B, ..., 203N; Weight estimator 208 and signal processor 209. Receive data r 1 ,..., Changed in frequency under sampling of the RF receiver / receiver 203A, 203B, ..., 203N. , r n is output to the channel estimators 207A, 207B, ... 207N for channel estimation, and channel estimation h1,... outputs hn to the weight estimator 208. The weight estimator 208 may use the fixed beam method, the maximum power method, the maximum signal interference rate method, or any other self-adaptive algorithm to form the beamforming weights of all mobile equipment.

Figure 112007054770408-pct00028
And estimate the channel
Figure 112007054770408-pct00029
Beam forming weights
Figure 112007054770408-pct00030
And received data r 1 ,... and r n is output to the signal processor 209 to detect the weighted joint to obtain data of each mobile device.

3 is a perspective view of the signal processor 209 of the base station in FIG. As shown in FIG. 3, the signal processor 209 includes a first generator 2092 for generating a composite channel impact response; A second generator 2093 for generating a weighted composite channel impact response; A third generator 2094 for generating a system array; A fourth generator 2095 used in the inverse array to create a system array; Received data r 1 ,... a data waiter 2096 that realizes weighting for r n ; And a fifth generator 2098 for generating the mapping filter 2097 and mobile equipment data.

Channel Estimation Output by Channel Estimator 207

Figure 112007054770408-pct00031
Is inputted to the first generator 2092 to calculate the spread spectrum interference code and the composite product of each mobile equipment, and thus the composite channel impact response.
Figure 112007054770408-pct00032
. Continue to Composite Channel Impact Response
Figure 112007054770408-pct00033
Is the beamforming weight received by the weight estimator 208 at the second generator 2093.
Figure 112007054770408-pct00034
Weighted composite channel impact response by performing weighting using
Figure 112007054770408-pct00035
Acquire it. Third generator 2094 provides a weighted composite channel impact response.
Figure 112007054770408-pct00036
Create system array A using system array
Figure 112007054770408-pct00037
, among them
Figure 112007054770408-pct00038
silver
Figure 112007054770408-pct00039
It is a Toeplitz array. Inverse array of system array A in fourth generator 2095
Figure 112007054770408-pct00040
. Data waiter 2096 receives data received from RF receiver / sender 203.
Figure 112007054770408-pct00041
Beamforming weights output by the weight estimator 208
Figure 112007054770408-pct00042
Weighted by, generating received data, vector
Figure 112007054770408-pct00043
Arrange as The system array A output by the third generator 2094 and the data vector output by the data weighting machine 2096
Figure 112007054770408-pct00044
Runs the mapping filter in the mapping filter 2097, and the mapping filter
Figure 112007054770408-pct00045
Is output to the fifth generator 2098. In the fifth generator 2098, the data d of each mobile device is output using the least square method, the maximum likelihood estimation method, or the MMSE algorithm.

As described above, the weighting joint can be detected using the base station of the present embodiment and the joint detection performance can be improved by reducing the falling influence of the joint detection performance due to the poor signal synchronization of the mobile equipment and the channel estimation error.

According to the present invention, the joint detection is performed by the weighting method of the beam forming weight, thereby greatly reducing the impact of the joint detection performance due to the poor signal synchronization between mobile equipment, and reducing the multi-address interference (MAI) due to the channel estimation inaccuracy. At the same time, the joint detection algorithm performance was improved by improving the input data SNR for joint detection. In addition, the present invention is advantageous in that the implementation is simple and the computational complexity is low.

Claims (6)

  1. Estimating for each antenna channel from each mobile equipment to the antenna array;
    Estimating the beamforming weights of the respective mobile facilities by the estimated channel;
    Weighting the received signal to obtain data after beam formation of each mobile device;
    And joint detecting the data of the respective mobile facilities by using the data after the beam formation and the estimated channel.
  2. 2. The antenna of claim 1, wherein estimating the beamforming weight of each mobile device is implemented by any one of a fixed beam search method, a maximum power method, a maximum signal interference rate method, and an adaptive weight estimation method. Wireless communication system joint detection method used in an array.
  3.        The method of claim 1, wherein the joint detection step,
    Generating a composite channel impact response of each mobile facility using the channel estimation and mobile equipment spread spectrum interference code;
    Weighting the composite channel impact response;
    And detecting data of each mobile device by using a weighted composite channel impact response and data after beam formation of each mobile device.
  4.        The method of claim 3, wherein detecting data of each mobile device comprises:
    System Array Using Weighted Composite Channel Impact Response
    Figure 112009080818424-pct00046
    Comprising the steps of, among which
    Figure 112009080818424-pct00047
    Weighted composite channel impact response
    Figure 112009080818424-pct00048
    Toeplitz array consisting of k, the total amount of mobile equipment,
    Vector data after beam forming of each mobile equipment
    Figure 112009080818424-pct00049
    If d is the vector of all mobile equipment data,
    Figure 112009080818424-pct00050
    ,
    Figure 112009080818424-pct00051
    This room is
    Figure 112009080818424-pct00052
    In Gaussian White Noise
    Figure 112009080818424-pct00053
    ;
    Figure 112009080818424-pct00054
    Is an independent covariance vector,
    Figure 112009080818424-pct00055
    Wireless communication system joint detection method used for the antenna array, characterized in that.
  5. An antenna array for receiving a signal transmitted by each mobile device;
    An RF receiver / transmitter for sampling the received signal to change a frequency; And
    A base station for realizing the joint detection method according to any one of claims 1 to 4, comprising a baseband processor for performing baseband processing on sampling data.
    The baseband processor,
    A channel estimator estimating a channel from each mobile device to each antenna;
    A weight estimator for estimating the beamforming weights of the respective mobile facilities based on the estimated channel;
    Weighting the received signal, acquiring data after beam formation of each mobile device, and joint detection using the post-beam data and the estimated channel to acquire data of each mobile device A base station for realizing a joint detection method comprising a signal processor.
  6. The method of claim 5, wherein the signal processor,
    A first generator for generating a composite channel impact response by executing a convolutional algorithm on the channel estimate;
    A second generator for generating a weighted composite channel impact response by weighting the beamforming weight with respect to the composite channel impact response;
    A third generator for generating a system array using the weighted composite channel impact response;
    A fourth generator for generating an inverse array of the system array;
    A data waiter that performs weighting of the beamforming weights on the sampling data;
    A mapping filter for executing a mapping filter on the system array and the post-weighting data;
    And a fifth generator configured to generate respective mobile equipment data based on the inverse array and the mapping filter result.
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