WO2011082502A1 - 基站设备及其方法和通信系统 - Google Patents

基站设备及其方法和通信系统 Download PDF

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Publication number
WO2011082502A1
WO2011082502A1 PCT/CN2010/000025 CN2010000025W WO2011082502A1 WO 2011082502 A1 WO2011082502 A1 WO 2011082502A1 CN 2010000025 W CN2010000025 W CN 2010000025W WO 2011082502 A1 WO2011082502 A1 WO 2011082502A1
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Prior art keywords
ratio
covariance matrix
interference
predetermined threshold
noise
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PCT/CN2010/000025
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English (en)
French (fr)
Inventor
李亚麟
曹伟
樊迅
林凌峰
李春亭
王勇
Original Assignee
上海贝尔股份有限公司
阿尔卡特朗讯
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Application filed by 上海贝尔股份有限公司, 阿尔卡特朗讯 filed Critical 上海贝尔股份有限公司
Priority to EP10841846.8A priority Critical patent/EP2523365A4/en
Priority to PCT/CN2010/000025 priority patent/WO2011082502A1/zh
Priority to US13/520,482 priority patent/US8862168B2/en
Priority to JP2012547418A priority patent/JP5497916B2/ja
Priority to CN201080034483.7A priority patent/CN102474333B/zh
Priority to BR112012016623A priority patent/BR112012016623A2/pt
Priority to KR1020127020458A priority patent/KR101405028B1/ko
Publication of WO2011082502A1 publication Critical patent/WO2011082502A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/0026—Interference mitigation or co-ordination of multi-user interference
    • H04J11/0036—Interference mitigation or co-ordination of multi-user interference at the receiver
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/541—Allocation or scheduling criteria for wireless resources based on quality criteria using the level of interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/345—Interference values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04J—MULTIPLEX COMMUNICATION
    • H04J11/00—Orthogonal multiplex systems, e.g. using WALSH codes
    • H04J11/0023—Interference mitigation or co-ordination
    • H04J11/005—Interference mitigation or co-ordination of intercell interference
    • H04J11/0059—Out-of-cell user aspects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
    • H04L2025/03375—Passband transmission
    • H04L2025/03414—Multicarrier
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
    • H04L2025/03375—Passband transmission
    • H04L2025/0342—QAM
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L2025/0335—Arrangements for removing intersymbol interference characterised by the type of transmission
    • H04L2025/03426—Arrangements for removing intersymbol interference characterised by the type of transmission transmission using multiple-input and multiple-output channels

Definitions

  • Embodiments of the present invention relate to wireless communications, and more particularly to a base station apparatus and method and communication system therefor. Background technique
  • interference rejection combining (IRC) algorithms can be used to greatly eliminate interference from neighboring cells.
  • IRC interference rejection combining
  • MMSE minimum mean square error
  • a base station apparatus including: a covariance matrix obtaining unit that forms a covariance matrix of interference and noise vectors from received signals from a plurality of user equipments; a ratio calculation and comparison unit, based on the association
  • the variance matrix calculates a relative ratio between the interference and the noise in the received signal, and compares the ratio with a predetermined threshold; the adjusting unit reduces the non-covariance in the covariance matrix if the ratio is less than a predetermined threshold a value of a diagonal element; when the ratio is greater than or equal to a predetermined threshold, the equalization matrix is used to perform equalization based on the covariance matrix, and when the ratio is less than the predetermined threshold, the adjusted covariance matrix is utilized.
  • the minimum mean square error algorithm equalizes the received signal.
  • the ratio calculation and comparison unit calculates a power ratio of interference and noise in the received signal as the relative ratio. According to an embodiment of the invention, the ratio calculation and comparison unit calculates the sum of the off-diagonal elements of the upper triangular portion of the covariance matrix of the interference and noise vectors divided by the sum of the diagonal elements as the relative ratio.
  • the adjusting unit reduces the value of the off-diagonal element of the covariance matrix to zero when the relative ratio is less than a predetermined threshold.
  • the ratio calculation and comparison unit calculates an amplitude ratio of interference and noise in the received signal as the relative ratio.
  • a method for a base station apparatus comprising the steps of: forming a covariance matrix of interference and noise vectors from received signals from a plurality of user equipments; calculating based on a covariance matrix Receiving a relative ratio between the interference and the noise in the signal, and comparing the ratio to a predetermined threshold; decreasing the value of the non-diagonal element in the covariance matrix if the ratio is less than a predetermined threshold; When the ratio is greater than or equal to a predetermined threshold, the interference rejection combining algorithm is used to perform equalization based on the covariance matrix, and when the ratio is less than the predetermined threshold, the received signal is equalized by the minimum mean square error algorithm based on the adjusted covariance matrix.
  • the power ratio of interference and noise in the received signal is calculated as the relative ratio.
  • the sum of the off-diagonal elements of the upper triangular portion of the covariance matrix of the interference and noise vectors is divided by the sum of the diagonal elements as the relative ratio.
  • the value of the off-diagonal element of the covariance matrix is reduced to zero when the relative ratio is less than a predetermined threshold.
  • the amplitude ratio of interference and noise in the received signal is calculated as the relative ratio.
  • a communication system comprising a base station device as described above.
  • a base station device as described above.
  • an IRC algorithm based reception scheme For example, when the user is in an area with a high signal-to-interference ratio (SIR), the advantages of the IRC algorithm can be fully utilized, and the advantages of the MMSE algorithm can be fully utilized when the user is in an area with a low signal-to-interference ratio (SIR).
  • SIR signal-to-interference ratio
  • SIR signal-to-interference ratio
  • FIG. 2 is a block diagram showing the structure of a receiving device according to an embodiment of the present invention.
  • Figure 3 shows a flow chart of a method in accordance with an embodiment of the present invention
  • FIG. 4 shows a relative ratio Ratio R of the interference and noise in the received signal ; a curve to the SIR;
  • FIG. 5 shows a receiver, an MMSE algorithm based receiver and an IRC algorithm based receiver of the embodiment of the present invention. Performance curve.
  • the IRC algorithm is generally effective.
  • the MMSE algorithm is effective when the target MS is in the cell center.
  • the MMSE algorithm and the IRC algorithm need to be implemented in different functional modules, so supporting two algorithms in one receiver will result in a highly complex structure.
  • the prior art cannot adaptively switch between the MMSE algorithm and the IRC algorithm. Highly complex structures hinder the widespread use of IRC algorithms. Therefore, when the interference signal power is large, for example, in the serving cell edge scenario, system performance can only be sacrificed.
  • whether to switch between the MMSE algorithm and the IRC algorithm is determined by determining a relative ratio (e.g., a ratio of power) between the interference and the noise in the received signal. This makes the system's throughput performance high regardless of whether the user equipment appears at the edge of the serving cell or at the center of the serving cell.
  • a relative ratio e.g., a ratio of power
  • the signal r received at the base station (BS) can be expressed as:
  • r Hs + z , ( 1 ) where s is the signal of the target mobile station (MS) and H is the channel matrix between the target MS and the BS, and z is the interference signal and noise.
  • the IRC algorithm can be expressed as:
  • MMSE minimum mean square error
  • N is the power matrix of the noise, expressed in the following format:
  • ⁇ , 2, ..., ⁇ is the estimated noise power on the ith antenna of the base station BS.
  • the mode of the off-diagonal element is much smaller than the mode of the diagonal element. Therefore, the value of the non-diagonal element can be set to zero without significantly affecting the algorithm.
  • R z becomes a diagonal matrix, and the IRC algorithm is reduced to the MMSE algorithm.
  • the equalization portion in the receiver of the embodiment of the present invention is uniformly expressed as:
  • the defined signal to interference ratio is:
  • the throughput vs. SIR curve is shown in Figure 5. If only the IRC algorithm is used, the throughput vs. SIR curve is shown in Figure 5. If the MMSE algorithm is used alone, the throughput vs. SIR curve is shown in Figure 5. It can be seen from Figure 5 that the IRC algorithm is superior to the MMSE algorithm at low SIR and inferior to the MMSE algorithm at high SIR.
  • a ratio Raticy is defined to adaptively switch between the MMSE algorithm and the IRC algorithm, as follows -
  • Ratio (8)
  • the above equation is the sum of the off-diagonal elements of the upper triangular portion of the noise and interference Z's covariance matrix R z divided by the sum of the diagonal elements, that is, the received signal A measure of the relative magnitude of interference power and noise power.
  • Other ways of determining the relative proportion of interference and noise in the received signal can also be used by one of ordinary skill in the art. '
  • Ratk ⁇ decreases as the SIR grows.
  • FIG. 2 shows a schematic structural diagram of a receiver according to an embodiment of the present invention.
  • a receiver according to an embodiment of the present invention includes: a covariance matrix obtaining unit 21 that forms a covariance matrix of interference and noise vectors from received signals from a plurality of user equipments; a ratio calculation and comparison unit 22 And calculating a relative ratio between the interference and the noise in the received signal based on the covariance matrix, and comparing the ratio with a predetermined threshold: the adjusting unit 23, which is in the case where the ratio is less than a predetermined threshold
  • the value of the off-diagonal element in the variance matrix is adjusted, for example, the value of the non-diagonal element is reduced to, for example, 0 ; the equalizer unit 24, which equalizes based on the IRC algorithm when the ratio is greater than or equal to a predetermined threshold, When the ratio is less than the predetermined threshold, the received signal is equalized based on the MMSE algorithm.
  • the receiving device of the base station can adaptively switch between the IRC algorithm and the MMSE algorithm, thereby The system's throughput performance is kept at a high level.
  • the scale calculation and comparison unit 22 calculates the relative proportion of the interference and the noise in the received signal using the above equation (8) based on the covariance matrix of the interference and noise vector (or matrix), and calculates the scaled ratio with a predetermined threshold. Compare. If the calculated ratio is less than the threshold, the adjusting unit 23 reduces the off-diagonal elements of the covariance matrix to, for example, 0, and then equalizes the received signal with the MMSE algorithm based on the adjusted covariance matrix in the equalizer unit 24. . If the calculated ratio is less than the threshold, the covariance matrix is not adjusted, but the received signal is equalized using the IRC algorithm directly in the equalizer unit 24 based on the unadjusted covariance matrix.
  • the covariance matrix obtaining unit 21 determines vectors of interference and noise components from the received signals and calculates a covariance matrix of the interference and noise vectors.
  • step S12 the scale calculation and comparison unit 22 calculates the relative ratio between the interference and the noise in the received signal based on the covariance matrix using the above formula (8), for example, the relative ratio of the powers of the two. According to another embodiment of the invention, the relative proportion of the amplitude of the interference and noise in the received signal can also be calculated.
  • step S13 the scale calculation and comparison unit 22 compares the calculated ratio with a predetermined threshold, for example, 0.3.
  • the adjusting unit 23 reduces the off-diagonal elements of the covariance matrix to 0 in step S14.
  • the equalizer unit 24 equalizes the received signal using the MMSE algorithm based on the adjusted covariance matrix.
  • step S14 the received signal is equalized directly in the equalizer unit 24 using the IRC algorithm based on the covariance matrix.
  • the performance at low SIR is much better than that of the MMSE equalizer, and is close to the performance of the IRC equalizer; at the same time, similar to the performance of the MMSE in the case of high SIR, Better than IRC equalizer.
  • Figure 5 shows the performance comparison results.
  • the scheme of the embodiments of the present invention is more robust when there are interference signals from other cells.
  • Using the unified receiver architecture of the embodiment of the present invention the advantages of the two algorithms are obtained in a simple structure, and the performance is obtained. Better than MMSE receiver and IRC receiver.
  • a unified receiver architecture in accordance with an embodiment of the present invention can be used in a MU-MIMO communication system.
  • the solution of the embodiment of the present invention can be used for WiMAX, LTE (Long Term Evolution) and LTE-Advanced.
  • LTE Long Term Evolution
  • LTE-Advanced Long Term Evolution-Advanced
  • the base station proposed by the embodiment of the present invention has been described above in the form of separate functional modules, each of the components shown in FIGS. 2 and 3 can be implemented by a plurality of devices in practical applications, and multiple Components can also be integrated into a single chip or a device in a practical application.
  • the base station in embodiments of the present invention may also include any unit or device for other purposes.
  • some embodiments also include a machine readable or computer readable program storage device (eg, a digital data storage medium) and encoding machine executable or computer executable program instructions, wherein the instructions perform some of the above methods or All steps.
  • the program storage device can be a digital memory, a magnetic storage medium (such as a magnetic disk and magnetic tape), a hardware or an optically readable digital data storage medium.
  • the implementation also includes a programming computer that performs the steps of the above method.

Description

基站设备及其方法和通信系统 技术领域
本发明的实施例涉及无线通信， 具体涉及一种基站设备及其方法和通信系 统。 背景技术
目前， 利用基站 BS上配备的多根天线， 可以使用干扰拒绝合并 （IRC)算 法来大大地消除来自相邻小区的干扰。但是， 当干扰功率相对较低时， IRC算法 的性能就没有那么突出。
与此同时， 传统的最小均方误差（MMSE)算法在较低干扰的场景中， 例如 服务小区中心位置处， 其性能远远优于 IRC算法。
因此， 需要开发一种新的接收机结构， 以便能够自适应地在 MMSE和 IRC 两种算法之间切换， 从而充分利用两种算法的优点。 发明内容
本发明的目的是提供一种接收设备及其方法和通信系统，能够使得无论用于 处于服务小区中心的场景，还是用于处于服务小区边缘的场景都能够获得较好的 性能。
在本发明的一个方面， 提出了一种基站设备， 包括： 协方差矩阵获得单元， 从来自多个用户设备的接收信号中形成干扰和噪声矢量的协方差矩阵；比例计算 与比较单元， 基于协方差矩阵计算接收信号中干扰和噪声二者之间的相对比例， 并且将该比例与预定的阈值相比较；调整单元，在该比例小于预定的阈值的情况 下减小该协方差矩阵中的非对角元素的值；均衡器单元，在该比例大于等于预定 阈值时，基于该协方差矩阵利用干扰拒绝合并算法进行均衡，而在该比例小于该 预定阈值时， 基于调整后的协方差矩阵利用最小均方差算法对接收信号进行均 衡。
根据本发明的实施例，所述比例计算与比较单元计算接收信号中干扰和噪声 的功率比， 作为所述相对比例。 根据本发明的实施例，所述比例计算与比较单元计算干扰与噪声矢量的协方 差矩阵的上三角部分的非对角线元素之和除以对角线元素之和，作为所述相对比 例。
根据本发明的实施例，所述调整单元在所述相对比例小于预定阈值时，将所 述协方差矩阵的非对角元素的值减小到零。
根据本发明的实施例，所述比例计算与比较单元计算接收信号中干扰和噪声 的幅值比， 作为所述相对比例。
在本发明的另一方面， 提出了一种， 一种用于基站设备的方法， 包括步骤： 从来自多个用户设备的接收信号中形成干扰和噪声矢量的协方差矩阵；基于协方 差矩阵计算接收信号中干扰和噪声二者之间的相对比例，并且将该比例与预定的 阈值相比较；在该比例小于预定的阈值的情况下减小该协方差矩阵中的非对角元 素的值；在该比例大于等于预定阈值时，基于该协方差矩阵利用干扰拒绝合并算 法进行均衡，而在该比例小于该预定阈值时，基于调整后的协方差矩阵利用最小 均方差算法对接收信号进行均衡。
根据本发明的实施例，计算接收信号中干扰和噪声的功率比，作为所述相对 比例。
根据本发明的实施例，计算干扰与噪声矢量的协方差矩阵的上三角部分的非 对角线元素之和除以对角线元素之和， 作为所述相对比例。
根据本发明的实施例，在所述相对比例小于预定阈值时，将所述协方差矩阵 的非对角元素的值减小到零。
根据本发明的实施例，计算接收信号中干扰和噪声的幅值比，作为所述相对 比例。
在本发明的再一方面， 提出了一种通信系统， 包括如上所述的基站设备。 利用上述的方法和设备， 能够在基于 IRC算法的接收方案和基于 MMSE的 接收方案之间自适应地切换。例如， 当用户处于信干比（SIR)较高的区域中时， 能够充分利用 IRC算法的优点， 当用户处于信干比（SIR)较低的区域中时， 能 够充分利用 MMSE算法的优点。 附图说明 通过下面结合附图说明本发明的优选实施例， 将使本发明的上述及其它目 的、 特征和优点更加清楚， 其中 - 图 1示出了典型的 IRC算法应用场景；
图 2示出了根据本发明实施例的接收设备的结构框图；
图 3示出了根据本发明实施例的方法的流程图；
图 4示出了接收信号中的干扰和噪声的相对比例 RatioR;对 SIR的曲线； 图 5示出了本发明实施例的接收机、 基于 MMSE算法的接收机和基于 IRC 算法的接收机的性能曲线。 具体实施方式
下面将说明本发明的多种实施例。随后的说明提供了对这些实施例的全面理 解的详细细节。但是， 本领域的技术人员应当了解， 无需一些所述细节也可以实 施本发明。此外， 可能不会示出或详细说明一些公知的结构或者功能， 以免不必 要地使本发明多种实施例的相关说明不清楚。
如图 1所示， 当目标 MS处于 0号服务小区的边缘、来自相邻的 1号小区的 移动站 MS (干扰 MS) 的干扰较大时， IRC算法通常都较为有效。 但是， 在目 标 MS处于小区中心时， MMSE算法比较有效。
如前所述， 由于现有的接收机中采用两种均衡方法， MMSE算法和 IRC算 法需要在不同的功能模块中实现，因此在一个接收机中支持两种算法将会导致高 复杂度的结构。 然而， 现有的技术不能在 MMSE算法和 IRC算法之间进行自适 应地切换。 高复杂度的结构阻碍了 IRC算法的广泛应用。 因此， 在干扰信号功 率较大时， 例如在服务小区边缘场景下， 就只能牺牲系统性能。
根据本发明的实施例，通过确定接收信号中干扰和噪声二者之间的相对比例 (例如功率的比例） 来确定是否在 MMSE算法和 IRC算法之间切换。 这样使得 无论用户设备出现在服务小区的边缘还是出现在服务小区的中心，系统的吞吐性 能都较高。
根据本发明的实施例， 在基站 （BS)接收的信号 r 可以表示为：
r = Hs + z , ( 1 ) 其中， s是目标移动站（MS)的信号， H 是目标 MS和 BS之间的信道矩阵， 而 z是干扰信号和噪声。
一方面， IRC算法可以表示为：
S = (HtfR;'H + l)-' HwR:'r (2) 其中， 是2的协方差矩阵， 采用下面的格式:
R. =
Figure imgf000006_0001
通常是根据由导频信号获得的信道估计结果来计算的。如果 z的主要分量是干 扰， 则 Rz中的非对角元素将会相对较大， 而对角元素较小。 如果 Z的主要分量 是噪声， 则 艮大程度上接近于对角矩阵， 非对角元素的值接近于零。
另一方面， 最小均方误差 （MMSE)算法可以表示如下-
Figure imgf000006_0002
其中 N 是噪声的功率矩阵， 采用如下的格式表示： .
Figure imgf000006_0003
其中 σ = ,2,..., Ν是在基站 BS的第 i根天线上估计的噪声功率。
在较低的干扰功率的情况下，非对角元素的模远远小于对角元素的模。因此， 可以置非对角元素的值为零， 而不会对该算法造成明显的影响。 由此， Rz变成 了对角矩阵， IRC算法蜕化为 MMSE算法。
基于这样的观察结果， 本发明实施例的接收机中的均衡部分统一表示成：
(ΗΗΙ^Η +】)— ' H"R:V …… (6) 其中， 对^进行自适应的切换， 从而实现在噪声占主要分量和干扰占主要分量 的不同场景下， 自适应地在 MMSE和 IRC算法之间的切换。 图 4示出了在以下配置的情况下， 干扰与噪声之间的相对比例！^ 与 SIR 之间的关系： BS配备 4根天线， QPSK调制、 MS的速度为 3km/h, SNR为 -4dB。
根据本发明的实施例， 定义信干比 （SIR) 为：
eTO—目标 MS的功率 、
干扰 MS的功率
如果只使用 IRC算法，吞吐量对 SIR的曲线如图 5所示。如果单独使用 MMSE 算法， 吞吐量对 SIR的曲线如图 5所示。 从图 5中可以看出 IRC算法在低 SIR 时优于 MMSE算法， 而在高 SIR时劣于 MMSE算法。
根据本发明的实施例， 定义一个比例 Raticy以便在 MMSE算法和 IRC算法 之间进行自适应切换， 如下-
∑∑ι。 : ι
Ratio, …… （8 ) 上式是将上文中定义的噪声与干扰 Z的协方差矩阵 Rz的上三角部分的非对角线 元素之和除以对角线元素之和，也就是接收信号中的干扰功率与噪声功率之间相 对大小的一个度量。本领域的普通技术人员也可以使用其它的方式来确定接收信 号中干扰和噪声的相对比例。 '
如图 4所示， Ratk ^随着 SIR的增长而降低。 根据本发明的实施例， 可以将 切换点设置在 thresh。ld=0.3。因此， 当该比例小于 0.3时， Rz针对 IRC算法在均衡 器中使用。 否则， 在均衡之前将 ^中所有非对角元素设置为零。
图 2示出了根据本发明实施例的接收机的结构示意图。如图 2所示，根据本 发明实施例的接收机包括： 协方差矩阵获得单元 21， 它从来自多个用户设备的 接收信号中形成干扰和噪声矢量的协方差矩阵； 比例计算与比较单元 22， 它基 于协方差矩阵计算接收信号中干扰和噪声二者之间的相对比例，并且将该比例与 预定的阈值相比较： 调整单元 23， 它在该比例小于预定的阈值的情况下对该协 方差矩阵中的非对角元素的值进行调整， 例如将非对角元素的值减小到例如 0; 均衡器单元 24， 它在该比例大于等于预定阈值时， 基于 IRC算法进行均衡， 而 在该比例小于该预定阈值时， 基于 MMSE算法对接收信号进行均衡。 这样， 当 用户设备从服务小区的中心移动到服务小区的边缘或者从服务小区的边缘移动 到服务小区的中心的情况下， 基站的接收设备都能够自适应地在 IRC 算法和 MMSE算法之间进行切换， 从而使得系统的吞吐性能保持在较高的水平。
如上所述， 比例计算和比较单元 22基于干扰和噪声矢量 （或矩阵） 的协方 差矩阵来用上式 （8) 计算接收信号中干扰和噪声的相对比例， 并且将计算的比 例与预定的阈值进行比较。 如果计算的比例小于该阈值， 则调整单元 23将该协 方差矩阵的非对角元素减小到例如 0， 然后在均衡器单元 24中基于调整后的协 方差矩阵用 MMSE算法对接收信号进行均衡。 如果计算的比例小于该阈值， 则 不对协方差矩阵进行调整， 而是直接在均衡器单元 24中基于未调整的协方差矩 阵利用 IRC算法进行对接收信号进行均衡。
下面结合附图 3详细说明根据本发明实施例的基站的操作过程。如图 3所示， 在步骤 Sll， 协方差矩阵取得单元 21从接收信号中确定干扰和噪声分量的矢量 并且计算干扰和噪声矢量的协方差矩阵。
然后， 在步骤 S12, 比例计算和比较单元 22基于协方差矩阵利用上述的公 式 （8 )计算接收信号中的干扰和噪声二者之间的相对比例， 例如二者功率的相 对比例。根据本发明的另一实施例，也可以计算接收信号中干扰和噪声的幅值的 相对比例。
接下来， 在步骤 S13, 该比例计算和比较单元 22将计算的比例与预定的阈 值， 例如 0.3， 进行比较。
如果计算的比例小于预定的阈值， 则在步骤 S14， 调整单元 23将协方差矩 阵的非对角元素减小到 0。在步骤 S15，均衡器单元 24基于调整后的协方差矩阵 利用 MMSE算法对接收信号进行均衡。
如果计算的比例大于等于预定的阈值，则在步骤 S14,直接在均衡器单元 24 中基于协方差矩阵利用 IRC算法对接收信号进行均衡。
使用本发明实施例的统一接收机结构， 在低 SIR时的性能远优于 MMSE均 衡器的性能， 而接近于 IRC均衡器的性能； 同时， 在高 SIR的情况下与 MMSE 的性能类似， 而优于 IRC均衡器。 图 5性能比较结果。
当存在来自其他小区的干扰信号时，本发明实施例的方案更为鲁棒。使用本 发明实施例的统一接收机架构， 以简单的结构得到了两种算法的优点，并且性能 优于 MMSE接收机和 IRC接收机。
另外， 根据本发明实施例的统一接收机架构可以用于 MU-MIMO通信系统 中。
本发明实施例的方案可以用于 WiMAX, LTE (长期演进）和 LTE-Advanced。 虽然上面以分离的功能模块的形式描述了本发明的实施例所提出的基站，但 是图 2和图 3中示出的每一个组件在实际应用中可以用多个器件实现，示出的多 个组件在实际应用中也可以集成在一块芯片或一个设备中。本领域普通技术人员 应该理解， 本发明实施方式中的基站还可包括用于其它目的的任何单元或装置。
本领域技术人员应该很容易认识到， 可以通过编程计算机实现上述方法的 不同步骤。在此， 一些实施方式同样包括机器可读或计算机可读的程序存储设备 (如， 数字数据存储介质）以及编码机器可执行或计算机可执行的程序指令， 其 中， 该指令执行上述方法的一些或全部步骤。例如， 程序存储设备可以是数字存 储器、磁存储介质（如磁盘和磁带）、 硬件或光可读数字数据存储介质。实施方 式同样包括执行上述方法的所述步骤的编程计算机。
描述和附图仅示出本发明的原理。 因此应该意识到， 本领域技术人员能够 建议不同的结构，虽然这些不同的结构未在此处明确描述或示出，但体现了本发 明的原理并包括在其精神和范围之内。此外，所有此处提到的示例明确地主要只 用于教学目的以帮助读者理解本发明的原理以及发明人所贡献的促进本领域的 构思， 并应被解释为不是对这些特定提到的示例和条件的限制。此外， 此处所有 提到本发明的原则、 方面和实施方式的陈述及其特定的示例包含其等同物在内。

Claims

权利要求书
1、 一种基站设备， 包括：
协方差矩阵获得单元，从来自多个用户设备的接收信号中形成干扰和噪声矢 量的协方差矩阵；
比例计算与比较单元，基于协方差矩阵计算接收信号中干扰和噪声二者之间 的相对比例， 并且将该比例与预定的阈值相比较；
调整单元，在该比例小于预定的阈值的情况下减小该协方差矩阵中的非对角 元素的值；
均衡器单元，在该比例大于等于预定阈值时，基于该协方差矩阵利用干扰拒 绝合并算法进行均衡， 而在该比例小于该预定阈值时，基于调整后的协方差矩阵 利用最小均方差算法对接收信号进行均衡。
2、 如权利要求 1所述的基站设备， 其中所述比例计算与比较单元计算接收 信号中干扰和噪声的功率比， 作为所述相对比例。
3、 如权利要求 2所述的基站设备， 其中所述比例计算与比较单元计算干扰 与噪声矢量的协方差矩阵的上三角部分的非对角线元素之和除以对角线元素之 和， 作为所述相对比例。
4、 如权利要求 1所述的基站设备， 其中所述调整单元在所述相对比例小于 预定阈值时， 将所述协方差矩阵的非对角元素的值减小到零。
5、 如权利要求 1所述的基站设备， 其中所述比例计算与比较单元计算接收 信号中干扰和噪声的幅值比， 作为所述相对比例。
6、 一种用于基站设备的方法， 包括步骤：
从来自多个用户设备的接收信号中形成干扰和噪声矢量的协方差矩阵； 基于协方差矩阵计算接收信号中干扰和噪声二者之间的相对比例，并且将该 比例与预定的阈值相比较；
在该比例小于预定的阈值的情况下减小该协方差矩阵中的非对角元素的值； 在该比例大于等于预定阈值时，基于该协方差矩阵利用干扰拒绝合并算法进 行均衡，而在该比例小于该预定阈值时，基于调整后的协方差矩阵利用最小均方 差算法对接收信号进行均衡。
7、 如权利要求 6所述的方法， 其中计算接收信号中干扰和噪声的功率比， 作为所述相对比例。
8、 如权利要求 7所述的方法， 其中计算干扰与噪声矢量的协方差矩阵的上 三角部分的非对角线元素之和除以对角线元素之和， 作为所述相对比例。
9、 如权利要求 6所述的方法， 其中在所述相对比例小于预定阈值时， 将所 述协方差矩阵的非对角元素的值减小到零。
10、 如权利要求 6所述的方法， 其中计算接收信号中干扰和噪声的幅值比， 作为所述相对比例。
11、 一种通信系统， 包括如权利要求〗〜 5之一所述的基站设备。
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