WO2010105417A1 - 一种估计下行信道质量的方法和装置 - Google Patents

一种估计下行信道质量的方法和装置 Download PDF

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Publication number
WO2010105417A1
WO2010105417A1 PCT/CN2009/070852 CN2009070852W WO2010105417A1 WO 2010105417 A1 WO2010105417 A1 WO 2010105417A1 CN 2009070852 W CN2009070852 W CN 2009070852W WO 2010105417 A1 WO2010105417 A1 WO 2010105417A1
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WIPO (PCT)
Prior art keywords
matrix
user equipment
interference
interference noise
indicator
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Ceased
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PCT/CN2009/070852
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English (en)
French (fr)
Inventor
万蕾
李强
夏亮
孙静原
王建国
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Huawei Technologies Co Ltd
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Huawei Technologies Co Ltd
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Application filed by Huawei Technologies Co Ltd filed Critical Huawei Technologies Co Ltd
Priority to BRPI0924403A priority Critical patent/BRPI0924403A2/pt
Priority to CN200980120974.0A priority patent/CN102986269B/zh
Priority to PCT/CN2009/070852 priority patent/WO2010105417A1/zh
Priority to EP09841701.7A priority patent/EP2410785B1/en
Publication of WO2010105417A1 publication Critical patent/WO2010105417A1/zh
Priority to US13/235,023 priority patent/US8588164B2/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/20—Monitoring; Testing of receivers
    • H04B17/24—Monitoring; Testing of receivers with feedback of measurements to the transmitter
    • 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
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0023—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the signalling
    • H04L1/0026—Transmission of channel quality indication
    • 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
    • H04B7/022—Site diversity; Macro-diversity
    • H04B7/024—Co-operative use of antennas of several sites, e.g. in co-ordinated multipoint or co-operative multiple-input multiple-output [MIMO] systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/20—Control channels or signalling for resource management
    • H04W72/21—Control channels or signalling for resource management in the uplink direction of a wireless link, i.e. towards the network
    • 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
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality

Definitions

  • the present invention relates to the field of wireless communication technologies, and in particular, to a method and apparatus for estimating downlink channel quality. Background technique
  • the network device In order to perform efficient radio resource scheduling, the network device must obtain sufficient and accurate downlink channel state information, and the state information mainly includes downlink signal to interference and noise ratio (SINR) information of all frequency bands.
  • SINR downlink signal to interference and noise ratio
  • the current LTE R8 specification relies on the measurement reporting of the user equipment UE.
  • the process of measuring the report mainly includes: the network device sends a certain reference signal for downlink channel measurement to the UE in the coverage area; after receiving the downlink reference signal, the UE obtains downlink channel information (CSI) by measurement and calculation, Based on the measured channel response and interference information, the downlink SINR in all frequency bands is calculated, and then the measured downlink SINR is quantized into a channel quality indication (CQI, Channel Quality Indication) and fed back to the network device according to a certain rule.
  • CSI downlink channel information
  • CQI Channel Quality Indication
  • the network device mainly performs radio resource scheduling according to the channel quality identifier CQI fed back by the UE. Therefore, the accuracy of the feedback information will directly determine the accuracy and efficiency of the scheduling.
  • the network device since the downlink SINR is changed in the time-frequency domain, in order to obtain accurate CQI feedback, the SINR must be divided into multiple sub-bands in the frequency domain, and the CQIs of multiple sub-bands are fed back. Furthermore, in order to track the time-varying characteristics of the SINR, the UE needs to periodically perform feedback of the CQI. These have brought about an increase in overhead spending. Summary of the invention
  • the embodiment of the invention provides a method and a device for estimating the downlink channel quality, and the network side directly performs the estimation of the downlink channel quality, which can greatly save the feedback cost of the user equipment.
  • the method for estimating downlink channel quality includes: The downlink channel quality indicator or the interference indicator fed back by the user equipment; the weak interference noise matrix of the user equipment is estimated from the downlink channel quality indicator or the interference indicator fed back by the user equipment; the time-frequency channel matrix of the serving cell and the time-frequency of the strong interfering cell are obtained. A strong interference matrix is obtained, and the time-frequency interference noise matrix of the user equipment is obtained from the estimated weak interference noise matrix and the time-frequency strong interference matrix; and the downlink channel quality is estimated according to the time-frequency channel matrix and the time-frequency interference noise matrix.
  • the network device includes: an indicator receiving unit, configured to receive a downlink channel quality indicator or an interference indicator that is fed back by the user equipment; a weak interference noise estimating unit, configured to perform a downlink channel quality indicator or an interference indicator that is fed back from the user equipment.
  • the weak interference noise matrix of the user equipment is estimated;
  • the time-frequency matrix acquisition unit is configured to acquire the time-frequency channel matrix of the serving cell and the time-frequency strong interference matrix of the strong interference cell, and estimate the weak interference noise matrix and the time-frequency
  • the strong interference matrix obtains a time-frequency interference noise matrix of the user equipment;
  • the channel quality estimation unit is configured to estimate the downlink channel quality according to the time-frequency channel matrix and the time-frequency interference noise matrix.
  • a user equipment provided by the embodiment of the present invention includes: an indicator acquiring unit, configured to obtain a downlink channel quality indicator or an interference indicator; and a feedback unit, configured to feed back the index obtained by the indicator acquiring unit to the network device.
  • the downlink channel quality indicator or the interference indicator fed back by the user equipment is received by the network device, and the weak interference noise matrix of the user equipment is estimated according to the feedback indicator, because the weak interference noise matrix changes in time and frequency.
  • the downlink channel quality can be estimated according to the time-frequency channel matrix of the serving cell obtained by the network device and the time-frequency strong interference matrix of the strong interfering cell, and the weak interference noise matrix estimated at the feedback time;
  • the feedback indicator is only used to estimate the weak interference noise matrix. It does not need to track the time-varying characteristics of the SINR.
  • the granularity and accuracy of the feedback indicator are not high, so the feedback overhead of the user equipment can be greatly saved.
  • FIG. 1 is a schematic flowchart of a method for estimating a downlink channel quality according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of a wireless communication system according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of a network device according to an embodiment of the present disclosure.
  • FIG. 4 is a schematic structural diagram of a user equipment according to an embodiment of the present invention. detailed description
  • an embodiment of the present invention provides a method for estimating a downlink channel quality, including: Step 11: A network device receives a downlink channel quality indicator or an interference indicator that is fed back by a user equipment; Step 12: A downlink that the network device feeds back from the user equipment A weak interference noise matrix of the user equipment is estimated in the channel quality indicator or the interference indicator;
  • Step 13 The network device acquires a time-frequency channel matrix of the serving cell and a time-frequency strong interference matrix of the strong interfering cell, and obtains a time-frequency interference noise of the user equipment by using the estimated weak interference noise matrix and the time-frequency strong interference matrix.
  • Step 14 The network device estimates the downlink channel quality according to the time-frequency channel matrix and the time-frequency interference noise matrix.
  • step 11 if the network device receives the downlink channel quality indicator fed back by the user equipment, before the feedback, the user equipment may acquire the channel quality identifier CQI of one or more serving cells in the measurement cell set, and use the wideband channel.
  • step 12 when the network device receives the broadband CQI fed back by the user equipment, acquiring the user A strong interference matrix of the device; assuming that the equivalent weak interference noise matrix of the user equipment is a real diagonal matrix, the equivalent interference noise matrix is obtained from the equivalent weak interference noise matrix and the strong interference matrix; according to the feedback wideband CQI inverse operation, The diagonal value of the equivalent weak interference noise matrix is obtained; and the weak interference noise matrix of the user equipment is estimated from the diagonal value of the equivalent weak interference noise matrix.
  • step 11 if the network device receives the interference indicator fed back by the user equipment, before the feedback, the user equipment estimates the downlink channel according to the downlink reference signal of the camped cell and calculates an interference noise matrix from other cells and background noise.
  • the one or more diagonal elements in the interference noise matrix are taken out, quantized, and fed back to the network device.
  • step 12 after receiving the quantized diagonal element fed back by the user equipment, the network device calculates a strong interference matrix of the user equipment according to the downlink channel information of the strong interfering cell of the user equipment at the moment; from the diagonal The strong interference matrix is removed from the elements, and the remaining estimates of the weak interference noise matrix of the user equipment.
  • the method for estimating the downlink channel quality receives the downlink channel quality indicator or the interference indicator fed back by the user equipment by using the network device, and estimates the weak interference noise matrix of the user equipment according to the feedback indicator, because the weak interference noise matrix is The time-frequency change is very slow.
  • the downlink interference channel quality can be estimated according to the weak interference noise matrix estimated by the feedback time and the time-frequency channel matrix of the serving cell and the time-frequency strong interference matrix of the strong interference cell acquired by the network device;
  • the indicator fed back by the user equipment is only used to estimate the weak interference noise matrix, it is not necessary to track the time-varying characteristics of the SINR, and the granularity and accuracy of the feedback indicator are not high, so the feedback overhead of the user equipment can be greatly saved.
  • the network side can overcome the defects of the original CQI feedback and provide a channel quality estimation with fine granularity and high precision.
  • the LTE+ system enters new features, for example, CoMP (Coordinated Multiple Point transmission and reception) mode, or multi-user multiple input and multiple output (MU-MIMO, Multiple-User) Multiple-Input Multiple-Output mode, etc.
  • CoMP Coordinatd Multiple Point transmission and reception
  • MU-MIMO Multi-user multiple input and multiple output
  • MU-MIMO Multiple-User
  • Multiple-Input Multiple-Output mode etc.
  • the UE can still only feed back the single-cell broadband CQI, which maintains the compatibility of the user equipment and the low complexity achieved.
  • cell 1 and cell 3 serve the UE at the same time, and constitute a serving set of the UE.
  • the UE is also interfered by the cell 2 of the strong interfering cell.
  • a strong interfering cell is defined as a non-resident cell or a serving cell resist cell 1 , cell 2 , and cell 3 that form a UE with a large-scale fading below a certain threshold value, and constitute a measurement cell set of the UE ( Measurement set)
  • Cell 4 and cell 5 are weak interfering cells of the UE.
  • the UE still estimates and feeds back the CQI of the single serving cell (using cell 1 as the serving cell), and the eNB calculates the interference matrix of the UE according to the downlink channel information of cell 1, cell 2, and cell 3 to the UE, and Calculate the SINR and CQI that cell 1 and cell 3 serve together.
  • Step 21 The UE does not consider multiple common serving cells, and only uses the MMSE (Minimum Mean Square Error) algorithm to calculate the SINR according to the downlink channel, the precoding matrix, and the received signal of the cell 1.
  • the calculation method is as follows:
  • Step 22 The UE quantizes the SINR calculated in step 21 into CQI, and feeds back to the eNB.
  • Step 23 After receiving the CQI, the eNB selects multiple strong interference cells (cell 2, cell according to the time).
  • the step 23 further includes:
  • Step 232 the interference signals from cell 4 and cell 5 are weak interference signals, and it can be assumed that the weak interference matrix corresponding to them is a real diagonal matrix:
  • the noise matrix is also set to a diagonal matrix, so the equivalent noise matrix can be set to
  • the weak interference noise matrix of the user equipment is estimated from the diagonal values ⁇ 2 , ⁇ 2 2 of the equivalent weak interference noise matrix.
  • Step 24 The eNB acquires downlink channel information of the UE serving cell (cell 1 and cell 3), a corresponding precoding matrix, scheduling information, a strong interfering cell (cell 2) downlink channel information, and a step by step on a certain time-frequency resource.
  • the weak interference noise matrix obtained in 23, and the SINR of the UE on this time-frequency resource is calculated according to the information, and quantized into CQI.
  • the step 24 further includes:
  • Step 241 The eNB acquires downlink channel information of the strong interfering cell (cell 2) of the serving cell of the UE to the UE on a scheduled time-frequency resource, and calculates a time-frequency strong interference matrix of the cell to the UE:
  • CoMP's macro diversity transmission mode in which case two serving cells (celll, cell 3) send the same data to the UE (if other CoMP modes are used, the following method of calculating the time-frequency channel matrix H(t, /)) Want # ⁇ corresponding changes).
  • the eNB generates a time-frequency channel matrix according to the downlink information of the serving cell to the UE/), H 3 (t, /), and the precoding matrix P, (t, f), P 3 (t, /):
  • Step 242 A weak interference noise matrix corresponding to the weak interference signal of the other interfering cells, whose change in the time domain and the frequency domain is slow, so that the time-frequency resource is equal to the one calculated in step 23 .
  • Time-frequency interference noise matrix obtained by the eNB is
  • ⁇ R IN k IN , t, f,, and (t, /) are brought into (3) (4) to obtain the S earn on the time-frequency resource.
  • Step 243 the eNB quantizes the SINR obtained in step 242 into CQI.
  • the network side estimates the downlink channel quality.
  • step 23 and step 24 the eNB needs to measure all the cells (cell 1, 6112 and 06113) in the cell set to the downlink channel information.
  • the eNB can pass the upper and lower channels. The channel reciprocity obtains this information.
  • the eNB can obtain the downlink channel quantization feedback by the UE, or obtain it by other means.
  • the algorithm for detecting the SINR at the UE side is not limited to the MMSE algorithm.
  • the eNB can still estimate the weak interference matrix and CQI as long as the eNB uses the UE-based algorithm in steps 23 and 24. .
  • the CQI fed back by the UE is not limited to the CQI of the camping cell when the UE is separately served, and may also feed back the CQI when any one or more cells in the measurement set of the UE are simultaneously serving the UE, as long as the step is In the 23rd, the corresponding change S of the eNB side and the selection of the strong interfering cell can estimate the weak interference matrix k N .
  • the feedback CQI is only used to estimate the weak interference noise matrix, and the change in the time domain and the frequency domain is slow, when the CQI is calculated on the eNB side by using the method, the CQI period fed back by the UE can be large, and The granularity of the UE measuring CQI in the frequency domain can also be large.
  • a feedback mode in the LTE R8 specification is: sub-band CQI + sub-band PMI (Precoding Matrix Indicator) + RI ( Rank Indicator), where the sub-band CQI feedback period is smaller than RI and sub- Feedback cycle with PMI.
  • the feedback mode can be adjusted to: wideband CQI + subband PMI + RI, and in addition, the feedback period of the wideband CQI can exceed the feedback period of PMI and RI.
  • the following description assumes that there are two receiving antennas on the UE side, and four transmit antennas on the eNB side.
  • the UE still estimates and feeds back the CQI of the single serving cell (cell 1 as the serving cell), and the eNB calculates the strong interference matrix of the UE according to the downlink channel information of the cell 1, cell 2, and cell 3 to the UE, and Calculate the SINR and CQI that cell 1 and cell 3 serve together.
  • Step 32 The UE extracts one or more diagonal elements in the interference noise matrix in step 31, performs quantization, and feeds back to the eNB. In this embodiment, the first diagonal element may be performed. Quantify feedback.
  • Step 33 After receiving the diagonal element of the interference noise matrix fed back by the UE, the eNB calculates the strong-drying of the UE according to the downlink channel information between the UE and the UE (the cell 2 and the cell 3) and the UE, and removes the strong interference. Residual interference, estimate weak interference noise matrix The residual interference is a unit matrix, and there is only one unknown, so it can be easily obtained:
  • Step 34 The eNB acquires downlink channel information, corresponding precoding matrix, scheduling information, strong interfering cell (cell 2 ) downlink channel information, and steps from the UE serving cell (cell 1 and cell 3) on a certain time-frequency resource.
  • the interference noise matrix d(t, /) obtained in 33, and the SINR of the UE on this time-frequency resource is calculated according to the information, and quantized into CQI.
  • the UE measures and feeds back.
  • the diagonal elements of the interference matrix only need to feed back a wideband measurement over the entire frequency band. At the same time, the feedback period can be long.
  • the overhead of the CQI that the UE needs to feed back can be greatly saved. While reducing the feedback overhead, it can overcome the defects of the original CQI feedback and provide fine-grained and high-precision channel quality estimation. Moreover, after the LTE+ system introduces new features, for example, in the CoMP and MU-MIMO modes, the UE can still feed back only the single-cell broadband CQI, maintaining the compatibility of the UE and achieving low complexity.
  • an embodiment of the present invention provides a network device, including:
  • the indicator receiving unit 1 is configured to receive a downlink channel quality indicator or an interference indicator fed back by the user equipment;
  • the weak interference noise estimating unit 2 is configured to estimate a weak interference noise matrix of the user equipment from a downlink channel quality indicator or an interference indicator fed back by the user equipment;
  • the time-frequency matrix obtaining unit 3 is configured to obtain a time-frequency channel matrix of the serving cell and a time-frequency strong interference matrix of the strong interfering cell, and obtain the user equipment by the estimated weak interference noise matrix and the time-frequency strong interference matrix.
  • Time-frequency interference noise matrix
  • the channel quality estimating unit 4 is configured to estimate the downlink channel quality according to the time-frequency channel matrix and the time-frequency interference noise matrix.
  • the weak interference noise estimating unit 2 includes any of the following modules:
  • the quality indicator estimating module 21 is configured to: when receiving the broadband CQI fed back by the user equipment, acquiring A strong interference matrix of the equipment; assuming that the equivalent weak interference noise matrix of the user equipment is a real diagonal matrix, the equivalent interference noise matrix is obtained from the equivalent weak interference noise matrix and the strong interference matrix; and the broadband CQI inverse according to the feedback Computing, obtaining a diagonal value of the equivalent weak interference noise matrix, and estimating a weak interference noise matrix of the user equipment from a diagonal value of the equivalent weak interference noise matrix;
  • the interference indicator estimation module 22 is configured to: after receiving the diagonal element quantized by the interference noise matrix fed back by the user equipment, calculate a strong interference matrix of the user equipment according to the downlink channel information of the strong interference cell of the user equipment at the moment; The strong interference matrix is removed from the diagonal elements, and the remaining weak interference noise matrices of the user equipment are estimated.
  • the quality indicator estimation module 21 is used to estimate the weak interference noise when the network device receives the downlink channel quality indicator fed back by the user equipment, and the interference indicator estimation module 22 is used by the network device to receive the interference indicator fed back by the user equipment. Weak interference noise estimation. For the specific calculation formulas, refer to the foregoing method embodiments, and details are not described herein again.
  • an embodiment of the present invention provides a user equipment, including:
  • the indicator obtaining unit 41 is configured to obtain a downlink channel quality indicator or an interference indicator.
  • the feedback unit 42 is configured to feed back the indicator obtained by the indicator acquiring unit to the network device.
  • the indicator obtaining unit 41 includes any one of the following modules:
  • a quality indicator obtaining module 411 configured to acquire a channel quality identifier CQI of one or more serving cells in the measurement cell set;
  • the interference indicator obtaining module 412 is configured to acquire one or more diagonal elements in the interference noise matrix of the camped cell.
  • the feedback unit 42 includes any of the following modules:
  • the first feedback module 421 is configured to: forward the channel quality identifier CQI obtained by the quality indicator obtaining module to the network device by using a wideband channel quality identifier CQI + a sub-band precoding matrix identifier PMI + a rank identifier RI feedback mode; or
  • the second feedback module 422 is configured to quantize the one or more diagonal elements acquired by the interference indicator acquiring module and then feed back to the network device. Receiving, by the network device, a downlink channel quality indicator or an interference indicator that is fed back by the user equipment, and estimating a weak interference noise matrix of the user equipment according to the feedback indicator, because the weak interference noise matrix changes slowly in time and frequency, and thus can be obtained according to the network device.
  • the time-frequency channel matrix of the serving cell and the time-frequency strong interference matrix of the strong interfering cell, and the weak interference noise matrix estimated at the feedback time estimate the downlink channel quality; and the index of the user equipment feedback is only used to estimate the weak
  • the interference noise matrix does not need to track the time-varying characteristics of the SINR, and the granularity and accuracy of the feedback indicator are not high, so the feedback overhead of the user equipment can be greatly saved.
  • the network side can overcome the defects of the original CQI feedback and provide a channel quality estimation with fine granularity and high precision.
  • the LTE+ system introduces new features, for example, when using the CoMP mode, or adopting the MU-MIMO mode, the UE can still feed back only the single-cell broadband CQI, maintaining user equipment compatibility and achieving low complexity. .
  • the technical solution provided by the embodiment of the present invention can be applied to all wireless communication systems using time-frequency domain selective scheduling based on channel state information.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).
  • Each functional unit in the embodiment of the present invention may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above integrated modules can be implemented in the form of hardware or in the form of software functional modules.
  • the integrated module if implemented in the form of a software functional module and sold or used as a standalone product, may also be stored in a computer readable storage medium.
  • the above-mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

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Description

一种估计下行信道质量的方法和装置 技术领域
本发明涉及无线通信技术领域， 具体而言是涉及一种估计下行信道质量 的方法和装置。 背景技术
为了进行高效的无线资源调度， 网絡设备必须获取充分、 准确的下行信 道状态信息， 该状态信息主要包括所有频带上的下行信干噪比 （SINR, Signal-Interference-Noise ratio )信息。 为了得到 SINR信息， 当前的 LTE R8 规范要依靠用户设备 UE的测量上报。
测量上报的过程主要包括： 网絡设备发送一定的用于下行信道测量的参 考信号给所覆盖区域的 UE; UE接收到下行参考信号后， 通过测量计算得到 下行信道信息 ( CSI, channel state information ), 才艮据测量得到的信道响应和 干扰信息， 计算出所有频带上的下行 SINR, 然后根据一定的规则将测量到的 下行 SINR量化为信道质量标识（ CQI, Channel Quality Indication )反馈给网 絡设备。
在实现本发明的过程中，发明人研究发现： 网絡设备主要是根据 UE反馈 的信道质量标识 CQI进行无线资源的调度。 因此反馈信息的准确与否将直接 决定着调度的准确度和效率。一方面，由于下行 SINR是时频域变化的， 因此， 要得到准确的 CQI反馈， 必须将 SINR在频域上分割为多个子带， 同时反馈 多个子带的 CQI。 此外， 为了跟踪 SINR的时变特性， UE需要周期性地进行 CQI的反馈。 这些都带来了上行开销的增长。 发明内容
本发明实施例提供一种估计下行信道质量的方法和装置， 由网絡侧直接 进行下行信道质量的估计， 能够大大节省用户设备反馈开销。
具体的， 本发明实施例提供的估计下行信道质量的方法， 包括： 接收用 户设备反馈的下行信道质量指标或干扰指标； 从用户设备反馈的下行信道质 量指标或干扰指标中估算出用户设备的弱干扰噪声矩阵； 获取服务小区的时 频信道矩阵和强干扰小区的时频强干扰矩阵， 并由估算出的弱干扰噪声矩阵 和时频强干扰矩阵， 获取用户设备的时频干扰噪声矩阵； 根据时频信道矩阵 和时频干扰噪声矩阵， 估计下行信道质量。
本发明实施例提供的网絡设备， 包括： 指标接收单元， 用于接收用户设 备反馈的下行信道质量指标或干扰指标； 弱干扰噪声估算单元， 用于从用户 设备反馈的下行信道质量指标或干扰指标中估算出用户设备的弱干扰噪声矩 阵； 时频矩阵获取单元， 用于获取服务小区的时频信道矩阵和强干扰小区的 时频强干扰矩阵， 并由估算出的弱干扰噪声矩阵和时频强干扰矩阵， 获取用 户设备的时频干扰噪声矩阵； 信道质量估计单元， 用于根据时频信道矩阵和 时频干扰噪声矩阵， 估计下行信道质量。
本发明实施例提供的一种用户设备， 包括： 指标获取单元， 用于获取下 行信道质量指标或干扰指标； 反馈单元， 用于将所述指标获取单元获取的指 标反馈给网絡设备。
通过上述技术方案的描述可知， 通过网絡设备接收用户设备反馈的下行 信道质量指标或干扰指标， 根据该反馈的指标估算出用户设备的弱干扰噪声 矩阵， 由于弱干扰噪声矩阵在时频上变化很慢， 因此可以根据网絡设备获取 到的服务小区的时频信道矩阵和强干扰小区的时频强干扰矩阵， 以及反馈时 刻估算出的弱干扰噪声矩阵， 对下行信道质量进行估计； 同时由于用户设备 反馈的指标仅用于估计弱干扰噪声矩阵， 不需要跟踪 SINR的时变特性， 对反 馈指标的粒度和精度要求不高， 因此可以大大节省用户设备的反馈开销。 附图说明 施例或现有技术描述中所需要使用的附图作一简单地介绍， 显而易见地， 下 面描述中的附图仅仅是本发明的一些实施例， 对于本领域普通技术人员来讲， 在不付出创造性劳动性的前提下， 还可以根据这些附图获得其他的附图。 图 1为本发明实施例提供的一种估计下行信道质量方法的流程示意图； 图 2为本发明实施例提供的一种无线通信系统的示意图；
图 3为本发明实施例提供的一种网絡设备的结构示意图；
图 4为本发明实施例提供的一种用户设备的结构示意图。 具体实施方式
为使本发明的目的、 技术方案、 及优点更加清楚明白， 下面结合附图并 举实施例， 对本发明提供的技术方案进一步详细描述。 显然， 所描述的实施 例仅仅是本发明一部分实施例， 而不是全部的实施例。 基于本发明中的实施 例， 本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实 施例， 都属于本发明保护的范围。
参见图 1 , 本发明实施例提供一种估计下行信道质量的方法， 包括： 步骤 11 , 网絡设备接收用户设备反馈的下行信道质量指标或干扰指标； 步骤 12, 网絡设备从该用户设备反馈的下行信道质量指标或干扰指标中 估算出用户设备的弱干扰噪声矩阵；
步骤 13 , 网絡设备获取服务小区的时频信道矩阵和强干扰小区的时频强 干扰矩阵， 并由该估算出的弱干扰噪声矩阵和该时频强干扰矩阵， 获取用户 设备的时频干扰噪声矩阵；
步骤 14, 网絡设备根据该时频信道矩阵和该时频干扰噪声矩阵， 估计下 行信道质量。
在步骤 11中，如果网絡设备接收的是用户设备反馈的下行信道质量指标， 则在反馈之前， 用户设备可以获取测量小区集合中的一个或多个服务小区的 信道质量标识 CQI, 并以宽带信道质量标识 CQI +子带预编码矩阵标识 PMI + 秩标识 RI反馈模式反馈宽带 CQI给网絡设备， 而且宽带 CQI 的反馈周期可 以大于或等于该子带 PMI和该 RI的反馈周期。
在步骤 12中， 网絡设备接收到该用户设备反馈的宽带 CQI时， 获取用户 设备的强干扰矩阵； 假设用户设备的等效弱干扰噪声矩阵为实对角阵， 由该 等效弱干扰噪声矩阵和该强干扰矩阵得到等效干扰噪声矩阵； 根据反馈的宽 带 CQI逆运算， 求解得到该等效弱干扰噪声矩阵的对角线值； 由该等效弱干 扰噪声矩阵的对角线值估算出用户设备的弱干扰噪声矩阵。
在步骤 11中， 如果网絡设备接收的是用户设备反馈的干扰指标， 则在反 馈之前， 用户设备根据驻留小区的下行参考信号， 估计下行信道并计算出来 自其它小区以及背景噪声的干扰噪声矩阵， 将该干扰噪声矩阵中的一个或多 个对角线元素取出， 进行量化后反馈给网絡设备。
在步骤 12中， 网絡设备收到用户设备反馈的该量化后的对角线元素后， 根据该时刻用户设备的强干扰小区的下行信道信息， 计算用户设备的强干扰 矩阵；从该对角线元素中除去该强干扰矩阵，剩余的估算出用户设备的弱干扰 噪声矩阵。
本发明实施例提供的估计下行信道质量的方法， 通过网絡设备接收用户 设备反馈的下行信道质量指标或干扰指标， 根据该反馈的指标估算出用户设 备的弱干扰噪声矩阵， 由于弱干扰噪声矩阵在时频上变化很慢， 因此可以根 据反馈时刻估算出的弱干扰噪声矩阵以及网絡设备获取到的服务小区的时频 信道矩阵和强干扰小区的时频强干扰矩阵， 对下行信道质量进行估计； 同时 由于用户设备反馈的指标仅用于估计弱干扰噪声矩阵，不需要跟踪 SINR的时 变特性， 对反馈指标的粒度和精度要求不高， 因此可以大大节省用户设备的 反馈开销。
并且， 在降低反馈开销的同时， 根据获取到的时频资源上的下行信道信 息， 网絡侧可以克服原有的 CQI反馈的缺陷， 提供粒度精细且精度高的信道 质量估计。
以及，在 LTE+系统弓 I入新的特征之后，例如，釆用协同多点收发（ CoMP， Coordinated Multiple Point transmission and reception )模式, 或釆用多用户多 入多出（ MU-MIMO, Multiple-User Multiple-Input Multiple-Output )模式等等， UE仍可以只反馈单小区宽带 CQI, 保持了用户设备的兼容性以及实现的低复 杂度。
参见图 2所示的无线通信系统。 釆用 CoMP模式， cell 1和 cell3同时为 UE服务， 构成 UE的服务小区集合 (serving set), 除了服务小区， UE还受到 强干扰小区 cell 2的干扰。 强干扰小区定义为与 UE间大尺度衰落低于某个门 限值的非驻留小区（anchor cell)或非服务小区（serving cell)„ cell 1、 cell 2和 cell3 构成 UE的测量小区集合 (measurement set)。 Cell 4和 cell 5为 UE的弱干扰小 区 (weak interfering cells)。
为简单起见， 下面的描述中假设 UE端有 2根接收天线， eNB端有 4根 发送天线， 每个 UE同时最多传输 2个数据流（ data stream ), 每个 UE反馈 L ( L=l , 2 )个流的 CQI。 为了降低 UE的实现复杂度， UE仍然估计并反馈单 个服务小区的 CQI (将 cell 1作为服务小区）， eNB根据 cell 1, cell 2, cell 3到 UE的下行信道信息计算 UE的干扰矩阵， 并重计算出 cell 1 和 cell 3共同服 务的 SINR和 CQI。
该实施例包括如下步骤：
步骤 21 , UE不考虑多个共同服务小区， 仅仅根据 cell 1的下行信道、 预 编码矩阵和接收信号， 釆用 MMSE (Minimum Mean Square Error, 最小均方误 差）算法计算出 SINR, 计算方法如下：
H = ΗλΡλ ( 1 )
Figure imgf000007_0001
SIN^ = Es - (4) 其中 Ht为 cell k ( k=2,3,4,5 )和 UE之间的下行信道矩阵， I为 Cell 1为 UE服务时的预编码矩阵， n为噪声信号向量， (·) 表示求数学期望运算， R1 N 为干扰噪声矩阵， £,为 δ的第 i 列， 为发送信号功率 （本实施例中假设
Es = \
步骤 22, UE将步骤 21中计算得到的 SINR量化为 CQI, 并反馈给 eNB。 步骤 23 , eNB在接收到 CQI后，根据该时刻多个强干扰小区（cell 2, cell
3 )到该 UE之间的下行信道信息计算 UE的强干扰矩阵 ^，根据步骤 22中获 取的 CQI信息计算 UE的弱干扰噪声矩阵 。
具体地， 该步骤 23进一步包括：
步骤 231 , 当 eNB接收到 UE反馈的 CQI时， 获取 UE的驻留小区的 2 个强干扰小区 （cell2、 cell3 )到该 UE的下行信道信息 H . (j=2,3 ), 计算该 2 个强干扰小区对 UE造成的干扰所对应的强干扰矩阵：
Figure imgf000008_0001
将 UE反馈的 L个流对应的 CQI, 根据由 SINR到 CQI的逆运算映射成 SINR, ( i=l,... ,L ), 其中^为反馈得到的 SINR, 它是 UE测量的 SINR的 量化；
根据驻留小区到 UE的下行信道信息 和预编码矩阵 S生成 ^二 ^ , 并 令 £,.为 的第 i列。
步骤 232, 来自于 cell 4、 cell5的干扰信号为弱干扰信号， 可以假设它们 所对应的弱干扰矩阵为实对角阵：
Figure imgf000008_0002
其中 1^为 cell s ( s=4,5 )到 UE的大尺度衰落， I为单位阵。
而噪声矩阵 也 ^叚设为对角阵， 所以可 ^叚设等效噪声矩阵为
« XHsH +E(nnH) (7)
Figure imgf000008_0003
？
由此， eNB得到等效干扰噪声矩阵： kIN =kI +kN (8)
其中含有 L (L=l,2)个未知数。
令 ^,^= ^,将 RLN, H, , 带入（3) (4) 式， 得到由 L个方程 组成的方程组， 该方程组含有 L个未知数， 解方程组可以得到 σι 2 , σ2 2 , 如果 L=l,贝' W =σ2 2。
由该等效弱干扰噪声矩阵的对角线值 σι 2 , σ2 2估算出用户设备的弱干扰噪 声矩阵。
步骤 24, eNB在某时频资源上， 获取 UE服务小区 （cell 1和 cell 3 ) 的 下行信道信息及相应的预编码矩阵、 调度信息， 强干扰小区 （cell 2) 下行信 道信息、 以及从步骤 23 中获取的弱干扰噪声矩阵 ,并根据这些信息计算 UE在这个时频资源上的 SINR, 并量化为 CQI。
具体地， 该步骤 24进一步包括：
步骤 241, eNB在某调度时频资源上， 获取 UE的服务小区的强干扰小 区 ( cell 2 )到该 UE的下行信道信息， 计算该小区对 UE的时频强干扰矩阵：
Figure imgf000009_0001
假设釆用 CoMP的宏分集发送模式， 此时 2个服务小区 （celll、 cell 3 ) 给 UE发送相同的数据（如果釆用其它 CoMP模式， 以下计算时频信道矩阵 H(t, /)的方法要 #支相应的改动）。
eNB根据服务小区到 UE的下行信道信息 /)、 H3(t,/)和预编码矩阵 P, (t, f)、 P3 (t, /)生成时频信道矩阵：
(t, f) = H (t, m (t ) + H3 (t, f)P3 (t,f) (10)
令 S,(t,/)为 ¾ ,/)的第 i列。
步骤 242, 来自于其他干扰小区的弱干扰信号对应的弱干扰噪声矩阵 ， 它在时域和频域上的变化艮慢，所以可以认为该时频资源上的 与步骤 23中 计算的到的 相等。 eNB得到的时频干扰噪声矩阵：
Figure imgf000010_0001
^RI N = kI N、t, f、, 将 (t,/)带入（3 ) ( 4 ) 式， 得到该时频资源上 的 S赚。
步骤 243, eNB将步骤 242中得到的 SINR量化为 CQI。
至此， 实现了网絡侧对下行信道质量的估计。
对本发明实施例补充说明如下：
一，在步骤 23和步骤 24中， eNB需要用到测量小区集合中所有小区（ cell 1、 。611 2和06113 )到该1¾的下行信道信息， 在时分双工 TDD系统中， eNB 可以通过上下行信道互易性得到这一信息， 在频分双工 FDD系统中， eNB可 以通过 UE端对下行信道量化反馈得到， 或通过其它方式获得。
二， UE端检测 SINR的算法不限于 MMSE算法， 釆用别的检测算法时， 只要在步骤 23和步骤 24中， eNB釆用和 UE—致的算法， 则仍然可以估算 出弱干扰矩阵 和 CQI。
三， UE反馈的 CQI不限于为 UE单独服务时的驻留小区的 CQI, 也可以 反馈 UE的测量小区集合 (measurement set)中任意一个或多个小区同时为 UE 服务时的 CQI, 只要在步骤 23中 eNB侧相应的改变 S和强干扰小区的选取， 即可估算出弱干扰矩阵 kN。
四， 由于反馈的 CQI仅用于估算弱干扰噪声矩阵 , 且 在时域和频域 上的变化艮慢， 所以釆用本方法在 eNB侧计算 CQI时， UE反馈的 CQI周期 可以很大， 同时 UE在频域上测量 CQI的粒度也可很大。
例如， LTE R8规范中的一种反馈模式为： 子带 CQI+子带 PMI ( Precoding Matrix Indicator, 预编码矩阵标识） +RI ( Rank Indicator, 秩标识）， 其中子带 CQI的反馈周期要小于 RI和子带 PMI的反馈周期。但是在本发明中， 可以将 反馈模式调整为： 宽带 CQI +子带 PMI + RI, 此外， 宽带 CQI的反馈周期可 以超过 PMI和 RI的反馈周期。 仍参考图 2所示的无线通信系统。为简单起见， 下面的描述中假设 UE端 有 2根接收天线， eNB端有 4根发送天线， 每个 UE同时最多传输 2个数据 流（ data stream ), 每个 UE反馈 L (L=l, 2)个流的 CQI。 为了降低 UE的实 现复杂度， UE仍然估计并反馈单个服务小区的 CQI ( cell 1作为服务小区）， eNB根据 cell 1, cell 2, cell 3到 UE的下行信道信息计算 UE的强干扰矩阵，并 重算出 cell 1 和 cell 3共同服务的 SINR、 CQI。
该实施例包括如下步骤：
步骤 31, UE根据驻留小区 （anchor cell) 下行参考信号， 估计下行信道 并计算出来自其它小区以及背景噪声的干扰噪声矩阵： y = H ; + ^Hkxk + n ( 12)
R N=E(yyH)-EsHxH^ ^Εβ,Η^ +E{nnH) (13) 其中 y为 UE的接收信号向量， ¾为 cdlk ( k=2,3,4,5 )的发送信号向量。 步骤 32 , UE将步骤 31中干扰噪声矩阵中的一个或多个对角线元素取出 , 进行量化， 并反馈给 eNB, 在本实施例中， 可以将第一个对角线元素 ( ^^进 行量化反馈。
步骤 33, eNB收到 UE反馈的干扰噪声矩阵的对角元素后， 根据该时刻 UE强干扰小区 ( cell 2和 cell 3 ) 与 UE之间的下行信道信息计算 UE的强干 , 由除去强干扰的剩余干扰， 估计出弱干扰噪声矩阵
Figure imgf000011_0001
于剩余干扰是一个单位阵， 而且仅仅有一个未知数， 因 此可以容易的得到：
(∑ +σ») = (^w )π-(∑ Hfl" )π (14) 这是一个频域非选择性、 时域慢变的量， eNB 根据算出的剩余干扰和实 时得到的强干扰小区的下行信道， 重新组合出时频干扰噪声矩阵 ^m = k人 t,f、 + kN。
步骤 34, eNB在某时频资源上， 获取 UE服务小区 （cell 1和 cell 3 ) 的 下行信道信息及相应的预编码矩阵、 调度信息、 强干扰小区 （cell 2 ) 下行信 道信息、 以及从步骤 33 中获取的干扰噪声矩阵 d(t,/)， 并根据这些信息计 算 UE在这个时频资源上的 SINR, 并量化为 CQI。
需要注意的是， 与上一个实施例相似， 由于反馈的干扰噪声矩阵的对角 元素仅用于估算弱干扰矩阵 , 而 在时域和频域上的变化 ^艮慢， 所以 UE 测量并反馈的干扰矩阵对角元素在整个频带上只需要反馈一个宽带测量量就 可以了， 同时， 反馈周期可以很长。
通过本发明实施例的方案， 可以大大节省 UE需要反馈的 CQI的开销。 在降低反馈开销的同时， 可以克服原有的 CQI反馈的缺陷， 提供粒度精细且 高精度的信道质量估计。并且，在 LTE+系统引入新的特征之后，例如， CoMP, MU-MIMO模式下， UE仍可以只反馈单小区宽带 CQI, 保持了 UE的兼容性 以及实现的低复杂度。
参见图 3, 本发明实施例提供一种网絡设备， 包括：
指标接收单元 1 , 用于接收用户设备反馈的下行信道质量指标或干扰指 标；
弱干扰噪声估算单元 2,用于从该用户设备反馈的下行信道质量指标或干 扰指标中估算出用户设备的弱干扰噪声矩阵；
时频矩阵获取单元 3 ,用于获取服务小区的时频信道矩阵和强干扰小区的 时频强干扰矩阵， 并由该估算出的弱干扰噪声矩阵和该时频强干扰矩阵， 获 取用户设备的时频干扰噪声矩阵；
信道质量估计单元 4, 用于根据该时频信道矩阵和该时频干扰噪声矩阵， 估计下行信道质量。
该弱干扰噪声估算单元 2包括如下任一模块：
质量指标估算模块 21 , 用于接收到用户设备反馈的宽带 CQI时， 获取用 户设备的强干扰矩阵； 假设用户设备的等效弱干扰噪声矩阵为实对角阵， 由 该等效弱干扰噪声矩阵和该强干扰矩阵得到等效干扰噪声矩阵； 并根据反馈 的宽带 CQI逆运算， 求解得到该等效弱干扰噪声矩阵的对角线值， 由该等效 弱干扰噪声矩阵的对角线值估算出用户设备的弱干扰噪声矩阵；
或者， 干扰指标估算模块 22, 用于收到用户设备反馈的干扰噪声矩阵量 化后的对角线元素后， 根据该时刻用户设备的强干扰小区的下行信道信息， 计算用户设备的强干扰矩阵；从该对角线元素中除去该强干扰矩阵，剩余的估 算出用户设备的弱干扰噪声矩阵。
上述的质量指标估算模块 21用于网絡设备接收到用户设备反馈的下行信 道质量指标时进行的弱干扰噪声估算， 上述的干扰指标估算模块 22用于网絡 设备接收到用户设备反馈的干扰指标进行的弱干扰噪声估算。 具体的计算公 式可分别参见上述的方法实施例， 在此不再赘述。
参见图 4, 本发明实施例提供一种用户设备， 包括：
指标获取单元 41 , 用于获取下行信道质量指标或干扰指标；
反馈单元 42, 用于将该指标获取单元获取的指标反馈给网絡设备。
所述指标获取单元 41包括如下任一模块：
质量指标获取模块 411 ,用于获取测量小区集合中的一个或多个服务小区 的信道质量标识 CQI; 或者，
干扰指标获取模块 412,用于获取驻留小区的干扰噪声矩阵中的一个或多 个对角线元素。
所述反馈单元 42包括如下任一模块：
第一反馈模块 421 ,用于将该质量指标获取模块获取的信道质量标识 CQI 以宽带信道质量标识 CQI +子带预编码矩阵标识 PMI +秩标识 RI反馈模式反 馈给网絡设备； 或者，
第二反馈模块 422,用于将该干扰指标获取模块获取的一个或多个对角线 元素量化后反馈给网絡设备。 通过网絡设备接收用户设备反馈的下行信道质量指标或干扰指标， 根据 该反馈的指标估算出用户设备的弱干扰噪声矩阵 , 由于弱干扰噪声矩阵在时 频上变化很慢， 因此可以根据网絡设备获取到的服务小区的时频信道矩阵和 强干扰小区的时频强干扰矩阵， 以及反馈时刻估算出的弱干扰噪声矩阵， 对 下行信道质量进行估计； 同时由于用户设备反馈的指标仅用于估计弱干扰噪 声矩阵， 不需要跟踪 SINR的时变特性， 对反馈指标的粒度和精度要求不高， 因此可以大大节省用户设备的反馈开销。
并且， 在降低反馈开销的同时， 根据获取到的时频资源上的下行信道信 息， 网絡侧可以克服原有的 CQI反馈的缺陷， 提供粒度精细且精度高的信道 质量估计。 以及， 在 LTE+系统引入新的特征之后， 例如， 釆用 CoMP模式， 或釆用 MU-MIMO模式时， UE仍可以只反馈单小区宽带 CQI,保持了用户设 备的兼容性以及实现的低复杂度。
本发明实施例提供的技术方案可以应用到， 使用基于信道状态信息的时 频域选择性调度的所有无线通信系统中。
最后需要说明的是， 本领域普通技术人员可以理解实现上述实施例方法 中的全部或部分流程， 是可以通过计算机程序来指令相关的硬件来完成， 该 的程序可存储于一计算机可读取存储介质中， 该程序在执行时， 可包括如上 述各方法的实施例的流程。 其中， 该的存储介质可为磁碟、 光盘、 只读存储 记忆体 ( Read-Only Memory, ROM ) 或随机存储记忆体 ( Random Access Memory, RAM )等。
本发明实施例中的各功能单元可以集成在一个处理模块中， 也可以是各 个单元单独物理存在， 也可以两个或两个以上单元集成在一个模块中。 上述 集成的模块既可以釆用硬件的形式实现， 也可以釆用软件功能模块的形式实 现。 该集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或 使用时， 也可以存储在一个计算机可读取存储介质中。 上述提到的存储介质 可以是只读存储器， 磁盘或光盘等。 上述具体实施例并不用以限制本发明， 对于本技术领域的普通技术人员 来说， 凡在不脱离本发明原理的前提下， 所作的任何修改、 等同替换、 改进 等， 均应包含在本发明的保护范围之内。

Claims

权 利 要 求 书
1、 一种估计下行信道质量的方法， 其特征在于， 包括：
接收用户设备反馈的下行信道质量指标或干扰指标；
从所述用户设备反馈的下行信道质量指标或干扰指标中估算出用户设备的 弱干扰噪声矩阵；
获取服务小区的时频信道矩阵和强干扰小区的时频强干扰矩阵， 并由所述 估算出的弱干扰噪声矩阵和所述时频强干扰矩阵， 获取用户设备的时频干扰噪 声矩阵；
根据所述时频信道矩阵和所述时频干扰噪声矩阵， 估计下行信道质量。
2、 根据权利要求 1所述的方法， 其特征在于， 所述在接收用户设备反馈的 下行信道质量指标的步骤之前包括：
用户设备获取测量小区集合中的一个或多个服务小区的信道质量标识 CQI; 用户设备以宽带信道质量标识 CQI +子带预编码矩阵标识 PMI +秩标识 RI 反馈模式反馈宽带 CQI给网絡设备。
3、 根据权利要求 2所述的方法， 其特征在于， 所述宽带 CQI 的反馈周期 大于或等于所述子带 PMI和所述 RI的反馈周期。
4、 根据权利要求 2或 3所述的方法， 其特征在于， 从所述用户设备反馈的 下行信道质量指标中估算用户设备的弱干扰噪声矩阵的步骤包括：
网絡设备接收到所述用户设备反馈的宽带 CQI时， 获取用户设备的强干扰 矩阵；
假设用户设备的等效弱干扰噪声矩阵为实对角阵， 由所述等效弱干扰噪声 矩阵和所述强干扰矩阵得到等效干扰噪声矩阵；
根据反馈的宽带 CQI逆运算， 求解得到所述等效弱干扰噪声矩阵的对角线 值；
由所述等效弱干扰噪声矩阵的对角线值估算出用户设备的弱干扰噪声矩 阵。
5、 根据权利要求 1所述的方法， 其特征在于， 所述在接收用户设备反馈的 干扰指标的步骤之前包括：
用户设备根据驻留小区的下行参考信号估计下行信道， 并计算来自其它小 区以及背景噪声的干扰噪声矩阵；
用户设备将所述干扰噪声矩阵中的一个或多个对角线元素取出， 进行量化 后反馈给网絡设备。
6、 根据权利要求 5所述的方法， 其特征在于， 所述从所述用户设备反馈的 干扰指标中估算用户设备的弱干扰噪声矩阵的步骤包括：
网絡设备收到用户设备反馈的所述量化后的对角线元素后， 根据用户设备 的强干扰小区的下行信道信息， 计算用户设备的强干扰矩阵；
从所述对角线元素中除去所述强干扰矩阵， 剩余的估算出用户设备的弱干 扰噪声矩阵。
7、 一种网絡设备， 其特征在于， 包括：
指标接收单元， 用于接收用户设备反馈的下行信道质量指标或干扰指标； 弱干扰噪声估算单元， 用于从所述用户设备反馈的下行信道质量指标或干 扰指标中估算出用户设备的弱干扰噪声矩阵；
时频矩阵获取单元， 用于获取服务小区的时频信道矩阵和强干扰小区的时 频强干扰矩阵， 并由所述估算出的弱干扰噪声矩阵和所述时频强干扰矩阵， 获 取用户设备的时频干扰噪声矩阵；
信道质量估计单元， 用于根据所述时频信道矩阵和所述时频干扰噪声矩阵， 估计下行信道质量。
8、 根据权利要求 7所述的网絡设备， 其特征在于， 所述弱干扰噪声估算单 元包括如下任一模块：
质量指标估算模块， 用于接收到用户设备反馈的宽带 CQI时， 获取用户设 备的强干扰矩阵； 假设用户设备的等效弱干扰噪声矩阵为实对角阵， 由所述等 效弱干扰噪声矩阵和所述强干扰矩阵得到等效干扰噪声矩阵； 并根据反馈的宽 带 CQI逆运算， 求解得到所述等效弱干扰噪声矩阵的对角线值， 由所述等效弱 干扰噪声矩阵的对角线值估算出用户设备的弱干扰噪声矩阵；
干扰指标估算模块， 用于收到用户设备反馈的干扰噪声矩阵量化后的对角 线元素后， 根据用户设备的强干扰小区的下行信道信息， 计算用户设备的强干 扰矩阵；从所述对角线元素中除去所述强干扰矩阵，剩余的估算出用户设备的弱 干扰噪声矩阵。
9、 一种用户设备， 其特征在于， 包括：
指标获取单元， 用于获取下行信道质量指标或干扰指标；
反馈单元， 用于将所述指标获取单元获取的指标反馈给网絡设备。
10、 根据权利要求 9所述用户设备， 其特征在于， 所述指标获取单元包括 如下任一模块： 质量指标获取模块， 用于获取测量小区集合中的一个或多个服务小区的信 道质量标识 CQI; 或者，
干扰指标获取模块， 用于获取驻留小区的干扰噪声矩阵中的一个或多个对 角线元素。
11、 根据权利要求 10所述用户设备， 其特征在于， 所述反馈单元包括如下 任一模块：
第一反馈模块， 用于将所述质量指标获取模块获取的信道质量标识 CQI以 宽带信道质量标识 CQI +子带预编码矩阵标识 PMI +秩标识 RI反馈模式反馈给 网絡设备； 或者，
第二反馈模块， 用于将所述干扰指标获取模块获取的一个或多个对角线元 素量化后反馈给网絡设备。
PCT/CN2009/070852 2009-03-17 2009-03-17 一种估计下行信道质量的方法和装置 Ceased WO2010105417A1 (zh)

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