WO2012034487A1 - 一种调整赋形颗粒度的方法、装置及系统 - Google Patents

一种调整赋形颗粒度的方法、装置及系统 Download PDF

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WO2012034487A1
WO2012034487A1 PCT/CN2011/079414 CN2011079414W WO2012034487A1 WO 2012034487 A1 WO2012034487 A1 WO 2012034487A1 CN 2011079414 W CN2011079414 W CN 2011079414W WO 2012034487 A1 WO2012034487 A1 WO 2012034487A1
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sub
bands
granularity
vector
correlation
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PCT/CN2011/079414
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English (en)
French (fr)
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索士强
张静
张健飞
韩波
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电信科学技术研究院
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00Baseband systems
    • H04L25/02Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202Channel estimation
    • H04L25/0204Channel estimation of multiple channels
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00Arrangements for detecting or preventing errors in the information received
    • H04L1/0001Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0023Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the signalling
    • H04L1/0026Transmission of channel quality indication

Definitions

  • the present invention relates to the field of communications, and in particular, to a method, device and system for adjusting shaped granularity. Background technique
  • Beamforming is a signal preprocessing technique based on antenna array.
  • BF generates a directional beam by adjusting the weighting system of each element in the antenna array, so that significant array gain can be obtained.
  • Shaped granularity is a parameter that needs to be determined when using the BF transmission method, and is compromised between the amount of computation and performance.
  • the system bandwidth is divided into a plurality of consecutive sub-bands according to the shaped granularity, each sub-band width is equal to the shaped granularity, and the same shaped weight vector is used for beamforming on one sub-band.
  • one or two sub-bands are allowed to have a width smaller than the shaped particle size.
  • BF is divided into single stream BF and double stream BF.
  • the so-called flow refers to the number of data streams transmitted simultaneously in the system.
  • the single data stream is transmitted in a single stream in the system, and the two streams in the system are dual-stream BF.
  • each sub-band there are two shaping weight vectors in each sub-band corresponding to the shaped granularity, one corresponding to the number of transmission streams and one corresponding to the number of transmission streams.
  • the weighting vector used on different subbands may vary.
  • the terminal when the terminal performs the sounding reference signal (SRS) in turn, the smaller the shaping granularity selected by the network side, the better.
  • SRS sounding reference signal
  • the interference between the two code words is relatively small; however, when the terminal side does not perform SRS rotation, the effect of the shape granularity on the system performance is not obvious, then, in order to greatly reduce the amount of calculation, The network side should try to choose a large typical granularity.
  • the network side when the terminal is in high-speed motion, the network side cannot completely track the channel change. At this time, the effect of the shape granularity on the system performance is also not obvious, then choose Small shaped granules do not bring performance gains, but can also reduce the amount of computation.
  • the correlation of channels of different terminals is different, and the correlation of channels of the same terminal changes with time, and therefore, the shaped granularity corresponding to the channel state is also different.
  • the configuration on the network side is to use a fixed shaped granularity (usually selected according to the worst/most typical scene), and does not consider the adaptive change of the shaped granularity, therefore, it is impossible to distinguish Channel change between terminals, and the same end
  • the change of the channel of the terminal with time in this way, often causes the configuration of the shaped granularity to not match the current state of the channel, thereby making the channel unable to reach the maximum gain, thereby reducing the overall performance of the system.
  • Embodiments of the present invention provide a method, apparatus, and system for adjusting shaped granularity for selecting matching shaped granularity based on channel conditions to optimize system performance.
  • a method of adjusting the shape of a shaped particle comprising:
  • the frequency domain width of each subband is a current shaped granularity; and the channel correlation of the plurality of subbands is used, and the channel correlation is used to represent the channel between the subbands Consistency of response;
  • the channel correlation is compared with a preset condition, and the current shaped granularity is adjusted according to the comparison result.
  • a device for adjusting the shape of a shaped particle comprising:
  • a determining unit configured to determine a plurality of sub-bands in which the frequency domain resources of the system are divided, and a frequency domain width of each sub-band is a current shaped granularity
  • a statistical unit configured to calculate channel correlation of the multiple subbands, where the channel correlation is used to represent consistency of channel responses between subbands;
  • an adjusting unit configured to compare the channel correlation with a preset condition, and adjust a current shaping granularity according to the comparison result.
  • a system for adjusting a shaped granularity comprising: a thousand base stations, wherein the base station is configured to determine a plurality of sub-bands in which frequency domain resources are divided, and a frequency domain width of each sub-band is a current shaped granularity, And correlating channel correlations of the plurality of sub-bands, the channel correlation is used to represent consistency of channel responses between the sub-bands, and comparing the channel correlation with preset conditions, and shaping the current according to the comparison result The graininess is adjusted.
  • the channel correlation is calculated for the thousands of sub-bands that are divided based on the shaped granularity in the system, and the channel correlation is used to characterize the consistency of the channel response between the sub-bands, thereby reflecting the channel state.
  • the change then, the obtained channel correlation is compared with the preset condition, and the current shaped granularity is adjusted according to the comparison result, so that the adaptive adjustment of the shaped granularity based on the channel state change is realized, Thereby effectively improving the shaping gain of the system, thereby improving the system performance.
  • 1 is a schematic structural diagram of a communication system architecture according to an embodiment of the present invention
  • 2 is a schematic structural diagram of a base station according to an embodiment of the present invention
  • FIG. 3 is a flowchart of adjusting a current shaped granularity by a base station according to an embodiment of the present invention. detailed description
  • the method used in the embodiment of the present invention is: determining a plurality of sub-divided resources of the system frequency domain resource Band, the frequency domain width of each subband is the current shaped granularity, and the channel correlation of the plurality of subbands is counted. Then, the channel correlation is compared with a preset condition, and the current shaped granularity is adjusted according to the comparison result. .
  • the so-called channel correlation is used to represent the consistency of the channel response between the sub-bands, thereby reflecting the change of the channel state. For example, if the channel responses on the two sub-bands are identical or different by a constant multiple, the two sub-bands The channel correlation is 1.
  • shape granularity which is a concept in the process of calculating the weight vector, is due to the feature decomposition of the matrix involved in the calculation of the weight vector, in order to reduce the amount of computation, usually in the adjacent G physical resource blocks ( In the Physical Resource Block, PRB, the same shape weight vector is used, and corresponding to a feature vector obtained when the matrix feature is decomposed, then the above-mentioned G PRBs may be referred to as shaped granularity.
  • PRB Physical Resource Block
  • a system for performing shaped granularity adjustment includes: a thousand base stations and a terminal, where the base station is configured to determine a plurality of sub-bands in which the system frequency domain resources are divided, each of the sub-bands The frequency domain width of the band is the current shaped granularity, and the channel correlation of the plurality of sub-bands is used, the channel correlation is used to characterize the consistency of the channel response between the sub-bands, and the channel correlation and the preset condition are For comparison, the current shaped granularity is adjusted according to the comparison result.
  • an apparatus for performing shaping granularity adjustment such as a base station, includes: a determining unit 20, a statistical unit 21, and an adjusting unit 22, where
  • the determining unit 20 is configured to determine a plurality of sub-bands in which the frequency domain resources of the system are divided, and the frequency domain width of each sub-band is the current shaped granularity;
  • the statistic unit 21 is configured to calculate channel correlation of the multiple subbands, where the channel correlation is used to represent consistency of channel responses between subbands;
  • the adjusting unit 22 is configured to compare the channel correlation with the preset condition, and adjust the current shaping granularity according to the comparison result.
  • the network side when the system performs pre-processing, the network side needs to select the initial shaped granularity.
  • the initial shaping granularity is selected, but is not limited to the following two.
  • Mode 2 Static adaptive setting, that is, the initial shape granularity of different users in the same cell can be selected separately Corresponding fixed value.
  • the network side After the initial shaped granularity is selected, the network side needs to adjust the initial shaped granularity according to changes in the network environment, for example, spatial correlation of the channel, frequency selectivity, etc. Further, when the network environment is further When changing, the network side also needs to adjust the adjusted shape granularity again. Then, referring to FIG. 3, in the embodiment of the present invention, the detailed process of adjusting the current shaping granularity of the system by the base station on the network side is as follows:
  • Step 300 Determine a plurality of subbands in which the frequency domain resources of the system are divided, and a frequency domain width of each subband is a current shaped granularity.
  • the current shaped granularity according to the subband division of the system frequency domain resource may be an initial shaped granularity or an adjusted shaped granularity.
  • Step 310 Count channel correlation of multiple subbands.
  • the channel correlation of the multiple sub-bands is implemented in multiple manners.
  • the following manner is used as an example, specifically:
  • the correlation coefficient of the shaping weight vector between the shaping weight vectors used for each sub-band on each adjacent sub-band is separately calculated, and the correlation coefficient is calculated based on the matching weight vector of all adjacent sub-bands to characterize the channel correlation.
  • a specified parameter may be an average of the weighting vector correlation coefficients of all adjacent sub-bands, a maximum value of the shape-of-vector correlation coefficients of all adjacent sub-bands, and all adjacent sub-bands
  • the minimum value of the vector correlation coefficient of the shaping weight, or the correlation coefficient of the shaping weight vector of all adjacent sub-bands, the number of the correlation weight vector correlation coefficient greater than the preset threshold value accounts for the total number of correlation coefficients of the shaping weight vector proportion.
  • the correlation coefficient of the weighting vector between the shaping weight vectors used for each subband of any set of adjacent subbands is counted, including:
  • the weighting vector correlation coefficient between the weighting vector of each subband of any set of adjacent subbands is counted
  • the correlation coefficient of the shaping vector between each of the weighting vectors of each sub-band on any adjacent sub-band is separately counted.
  • the weighting vector correlation coefficient between the shaping weight vectors used in each subband of any set of adjacent subbands includes: the weighting vector of each subband of any set of adjacent subbands The modulus of the inner product of the vector; or the norm of the difference of the normalized vector of the shape weight vector for each subband of any set of adjacent subbands, where the so-called shaping right
  • the vector normalized vector is obtained by normalizing the shape weight vector according to its first element.
  • Step 320 Comparing the channel correlation with the preset condition, and adjusting the current shaped granularity according to the comparison result.
  • step 320 when step 320 is performed, the specified parameter for characterizing the channel correlation is compared with a preset threshold. If it is determined that the specified parameter is greater than or equal to the set threshold, the preset step is followed. Increasing the current shaped granularity, if it is determined that the specified parameter is less than the set threshold, the current shaped granularity is reduced according to the preset step size;
  • the preset step size can be a fixed step size or a variable step size.
  • the correlation coefficients of the shaping weight vectors between the weighted weight vectors for each subband of the three adjacent subbands are respectively 0.8, 0.76, 0.72, and the calculation is used for characterization.
  • the average of the weighting vector correlation coefficients of all adjacent sub-bands of the channel correlation is 0.75, and the average value is compared with the set threshold value.
  • the current shaped granularity is increased, that is, the adjusted shaped granularity is 6PRB, and if the average value is determined to be less than the set threshold, according to the preset step size, for example, 1PRB, The current shaped granularity is reduced, that is, the adjusted shaped granularity is 3PRB; wherein, when the preset step size is a variable step size, the step value can be referred to between the average value and the set threshold value. The difference is selected as the corresponding value.
  • the calculation of the shaping weight vector is performed in units of 1 PRB, and the current shaping granularity is 4PRB, and the PRBs in the three sub-bands are PRB1 ⁇ PRB12 in turn, when any PRB is taken.
  • the weighting vector calculated above is used as the shaping weight vector on the subband to which it belongs, only the shaping weight vector on PRB1, PRB3, PRB5, PRB7, PRB9, PRB11 can be calculated, so that when adjusted according to the adjustment
  • the shaped weight vector calculated on PRB1 is used on PRB1 ⁇ PRB6, and the calculated weighting vector calculated on PRB2 is used on PRB7 ⁇ PRB12, if the shaped granularity is reduced
  • the weighting vector calculated on PRB1 is used on PRB 1 and PRB2
  • the weighting vector calculated on PRB3 is used on PRB3 and PRB4.
  • the weighting vector calculated on PRB5 is Used on PRB5 and PRB6, the weighting vector calculated on PRB7 is used on PRB7 and PRB 8.
  • the weighting vector calculated on PRB9 is used on PRB9 and PRB 10.
  • the weighting vector calculated on PRB11 isUsed on PRB11 and PRB 12. In this way, the recalculation of the shaping weight vector due to the update of the shaped granularity is avoided, the calculation amount of the system is reduced, and the resource consumption is reduced.
  • step 320 there are also differences according to the number of streams transmitted by the system, including:
  • the weighting vector correlation coefficient between the weighting vector of each sub-band on any adjacent sub-band is counted, for example, in the adjacent sub-band 1 On the subband 2, the subband 1 ⁇ transmits the data stream with the shaping weight vector W1, and the subband 2 ⁇ transmits the data stream with the shaping weight vector W2, then the correlation coefficient R12 of the shaping weight vector between the statistics W1 and W2 is related. .
  • step 320 when step 320 is performed,
  • the R12 correlation is compared with the set threshold for characterizing the channel correlation of the subband 1 and the subband 2, and when the threshold value is set by R12, the current shaped granularity is increased according to the preset step size.
  • the current shaping granularity is reduced according to the preset step size.
  • the correlation weight vector correlation coefficients between each level of the weighting vector for each sub-band on any adjacent sub-band are separately counted.
  • the system uses the dual-flow BF method, and on the adjacent sub-band 1 and sub-band 2, the feature vector set obtained by eigen-decomposed based on the covariance matrix of the channel on the sub-band 1 has the largest and the second largest eigenvalue.
  • the feature vectors are W1 and W' l respectively, and in the feature vector set obtained by feature decomposition based on the covariance matrix of the subband 2, the two feature vectors of the largest and second largest feature values are W2 and W'2, respectively.
  • each feature vector corresponds to the corresponding level, then In this embodiment, it is required to calculate the correlation weight vector correlation coefficient R12 between W1 and W2, and the shape weight vector correlation coefficient R'12 between W'1 and W'2.
  • step 320 when step 320 is performed,
  • R12 correlation and R'12 correlation are used as specified parameters for characterizing the channel correlation of subband 1 and subband 2, compared with the set threshold, when R12 is related to the threshold, and R'12 is related.
  • For the threshold value increase the current shape granularity according to the preset step size.
  • R12 is related to ⁇ set threshold value
  • R' 12 is related to ⁇ set threshold value
  • the current assignment is reduced according to the preset step size. Shape granularity.
  • any subband when calculating the weighting vector used for the subband, at least the following two methods can be used:
  • the frequency domain width of one subband is N*G PRBs, and then divided into N small subbands, then the frequency domain of each small subband
  • the width is G PRBs.
  • the shaping weight vector W on the small sub-band can be calculated based on the corresponding G PRBs, and the W used on any of the small sub-bands is used as the sub-band to which it belongs.
  • the shape weight vector is the shape weight vector.
  • the network side performs the calculation of the shaping weight vector based on the SRS signal sent by the terminal side, and the SRS uses the frequency hopping mode, and the frequency domain width occupied by the SRS transmission is 4 PRB, and the current subband, That is, the frequency domain width of the shaped granularity is 8 PRB, and the sub-band can be divided into two small sub-bands with a bandwidth of 4 PRB.
  • the network side needs to wait for the SRS channel estimation results of the adjacent two small sub-bands, and by using the above method 2, the shaped granularity and the shaping weight vector frequency domain average granularity are separated, in any one In the subband, if the SRS signal is received on any of the small subbands, the shaping vector update calculation can be performed, and the shaping weight vector of the entire subband is used in the time domain effective time of the shaping weight vector. Used to avoid reliance on SRS hopping bandwidth.
  • H and H are the channel responses corresponding to the kth subcarrier on subband 1 and subband 2, respectively, where H, 1 GC MRXM ⁇ , U K 2 e C M ⁇ , M «, ⁇ respectively Number of receiving antennas and transmitting antennas
  • the trace of the matrix, or the channel correlation defining subband 1 and subband 2 is
  • the channel correlation between any two adjacent subbands in the system bandwidth can be obtained according to the first method described above, and then calculated based on the obtained channel correlation of each adjacent subband.
  • a specified parameter of channel correlation of a plurality of subbands within the bandwidth the specified parameter may be an average value of channel correlations, a maximum value among channel correlations, a minimum value among channel correlations, or a channel correlation The ratio of the number of channel correlations greater than the preset threshold to the total number of channel correlations is not described here.
  • R 2 ]H, 2 3 ⁇ 4 2 , normalize the two covariance matrices using their first element to obtain 1 and 2 , and define the channel correlation of subband 1 and subband 2 as 2
  • the channel correlation between any two adjacent subbands in the system bandwidth can be obtained according to the second method described above, and then used to characterize the system based on the obtained channel correlation of each adjacent subband.
  • the specified parameter may be an average value of channel correlations, a maximum value among channel correlations, a minimum value among channel correlations, or a channel correlation
  • the ratio of the number of channel correlations greater than the preset threshold to the total number of channel correlations is not described here.
  • the channel correlation of multiple sub-bands can also be calculated according to the following method, and the current shaped granularity is compared according to the obtained channel correlation and the preset condition. Make adjustments. Specifically:
  • the calculation interval specifies the shape weight vector correlation coefficient between the shape weight vectors used on the two sub-bands of the frequency domain width, and the weighting vector correlation coefficient is directly used as a parameter for characterizing the channel correlation.
  • the above-mentioned shaping weight vector correlation coefficient can be compared with a preset threshold value. If the preset threshold value is not exceeded, the specified frequency domain width is used as the newly set current shaping granularity.
  • the calculation method of the correlation coefficient of the shaping vector and the calculation method of the shaping vector can be performed by referring to the schemes described in step 310 and step 320, and details are not described herein again.
  • the subband width is 4PRBs
  • the 4PRB is continued as the current shaped granularity. If the value related to W12 is not less than the preset threshold, the weighting vector correlation between subband 1 and subband 3 can be calculated again.
  • the coefficient W13 is related. If the value of the W13 correlation is less than the preset threshold, the 8PRB is used as the current shaped granularity. If the value of the W13 correlation is still not less than the preset threshold, the subband 1 and the subband 4 may continue to be calculated.
  • the weighting vector correlation coefficient W14 is related, and the current shaping granularity is continuously adjusted in the same way, and so on, until the appropriate shaped granularity is selected or the maximum bandwidth of the system is reached, when the maximum system is reached. The bandwidth is still not found, and the shaped granularity is taken as the system bandwidth.
  • step 310 the manner in which the channel correlation is calculated is not limited to the one described in step 310.
  • the manner of recording in step 310 is only a preferred embodiment, and is not limited thereto.
  • the channel correlation is calculated for the thousands of sub-bands that are divided based on the shaped granularity in the system, and the channel correlation is used to characterize the consistency of the channel response between the sub-bands. Thereby, the change of the channel state is reflected. Then, the obtained channel correlation is compared with the preset condition, and the current shaped granularity is adjusted according to the comparison result, so that the shaped granularity based on the channel state change is realized. Adaptive adjustment, which effectively increases the shaping gain of the system, thereby improving system performance.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the present invention is in the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) in which computer usable program code is embodied.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Description

一种调整赋形颗粒度的方法、 装置及系统 技术领域
本发明涉及通信领域, 特别涉及一种调整赋形颗粒度的方法、 装置及系统。 背景技术
波束赋形 (Beamforming, BF )是一种基于天线阵列的信号预处理技术, BF通过调整 天线阵形中每个阵元的加权系统产生具有指向性的波束, 从而能够获得明显的阵列增益。 赋形颗粒度是在使用 BF传输方式时需要确定的参数, 从运算量和性能两者间进行折中优 化。 通常情况下, 将系统带宽按赋形颗粒度划分为多个连续的子带, 每个子带宽度等于赋 形颗粒度, 在一个子带上使用相同的赋形权矢量进行波束赋形, 当然, 有时也允许有一个 或两个子带的宽度小于赋形颗粒度。
现有技术下, BF分为单流 BF和双流 BF。 所谓流, 是指系统中同时传输的数据流的 数目, 系统内传输单个数据流则为单流 BF , 系统内同时传输两个数据流则为双流 BF。
对于单流 BF ,在每一个赋形颗粒度对应的子带存在一个赋形权矢量, 不同的子带上釆 用的赋形权矢量有所区别。
对于双流 BF ,在每一个赋形颗粒度对应的子带内均存在两个赋形权矢量,一个对应传 输流数 1 , 一个对应传输流数 2。 不同的子带上釆用的赋形权矢量可能有所不同。
对于单流 BF , 在能够完全跟踪信道变化的前提下, 为了获得明显的阵列增益, 网络侧 选择的赋形颗粒度越小越好; 但是, 当信道空间相关度很高或者频率选择性(Power Delay Profile , PDP , 即描述信道功率时延的信息)很小时, 赋形颗粒度的大小对系统性能的影 响并不明显, 那么为了大幅度的减小运算量, 网络侧则应尽量选择大的赋形颗粒度。
对于双流 BF ,在能够完全跟踪信道变化的前提下,当终端进行探测参考信号 (Sounding Reference Signal , SRS)轮流发射时, 网络侧选择的赋形颗粒度越小越好, 此时, 双流分别 使用的两码字间的千扰相对较小; 但是, 当终端侧不进行 SRS轮流发射时, 赋形颗粒度的 大小对系统性能的影响并不明显, 那么, 为了大幅度的减小运算量, 网络侧应尽量选择大 的典型颗粒度, 另一方面, 终端处于高速运动时, 网络侧无法完全跟踪信道的变化, 此时, 赋形颗粒度的大小对系统性能的影响同样不明显, 那么选择小的赋形颗粒度不会带来性能 增益, 也可以适当降低运算量。
在通信系统中, 对于某一小区而言, 不同终端的信道的相关性不同, 同一终端的信道 的相关性随时间变化, 因此, 与信道状态相适应的赋形颗粒度也各不相同。 而现有技术下, 网络侧的配置方式为釆用固定的赋形颗粒度(通常按照最恶劣 /最典型的场景进行选取), 不考虑赋形颗粒度的自适应变化, 因此, 无法区分不同终端之间信道的变化, 以及同一终 端的信道随时间的变化, 这样, 往往造成配置的赋形颗粒度与信道的当前状态不匹配的状 况, 从而令信道无法达到最大增益, 进而降低了系统的整体性能。 例如, 赋形颗粒度过大, 则会造成与信道失配过大, 而降低赋形增益, 影响系统性能; 赋形颗粒度过小, 则会带来 不必要的赋形权矢量计算, 增大运算量, 而影响系统性能。 发明内容
本发明实施例提供一种调整赋形颗粒度的方法、 装置及系统, 用以基于信道状态选择 相匹配的赋形颗粒度, 从而优化系统性能。
本发明实施例提供的具体技术方案如下:
一种调整赋形颗粒度的方法, 包括:
确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前赋形颗粒度; 统计所述多个子带的信道相关性, 该信道相关性用于表征子带间的信道响应的一致 性;
将信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗粒度进行调整。
一种用于调整赋形颗粒度的装置, 包括:
确定单元, 用于确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前 赋形颗粒度;
统计单元, 用于统计所述多个子带的信道相关性, 该信道相关性用于表征子带间的信 道响应的一致性;
调整单元, 用于将所述信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗 粒度进行调整。
一种用于调整赋形颗粒度的系统, 包括若千基站, 所述基站, 用于确定系统频域资源 被划分出的多个子带, 每个子带的频域宽度为当前赋形颗粒度, 并统计所述多个子带的信 道相关性, 该信道相关性用于表征子带间的信道响应的一致性, 以及将所述信道相关性与 预设条件进行比较, 根据比较结果对当前赋形颗粒度进行调整。
本发明实施例中,针对系统内基于赋形颗粒度划分出的若千子带,计算其信道相关性, 该信道相关性用于表征子带间的信道响应的一致性, 从而反应了信道状态的变化, 接着, 将获得的信道相关性与预设条件进行比较, 并根据比较结果对当前赋形颗粒度进行调整, 这样, 便实现了基于信道状态变化的赋形颗粒度的自适应调整, 从而有效提高了系统的赋 形增益, 进而提升了系统性能。 附图说明
图 1为本发明实施例中通信系统体系架构示意图; 图 2为本发明实施例中基站功能结构示意图;
图 3为本发明实施例中基站对当前赋形颗粒度进行调整的流程图。 具体实施方式
为了能够基于信道状态为系统带宽内的各子带选择相匹配的赋形颗粒度, 从而提高系 统的性能, 本发明实施例中釆用的方法为: 确定系统频域资源被划分出的多个子带, 每个 子带的频域宽度为当前赋形颗粒度, 统计多个子带的信道相关性, 接着, 将该信道相关性 与预设条件进行比较, 根据比较结果对当前赋形颗粒度进行调整。 其中, 所谓信道相关性 用于表征子带间的信道响应的一致性, 从而体现了信道状态的变化, 例如, 若两子带上信 道响应完全相同或差一个常数倍数, 则这两子带的信道相关性为 1。
所谓赋形颗粒度, 即是赋形权矢量计算过程中的一个概念, 由于赋形权矢量计算过程 中涉及到矩阵的特征分解, 为了降低运算量, 通常在相邻的 G个物理资源块(Physical Resource Block, PRB )中使用同一个赋形权矢量, 对应矩阵特征分解时获得的一个特征矢 量, 那么, 上述 G个 PRB即可以称为赋形颗粒度。
下面结合附图对本发明优选的实施方式进行详细说明。
参阅图 1所示, 本发明实施例中, 用于进行赋形颗粒度调整的系统包括: 若千基站和 终端, 其中, 基站用于确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当 前赋形颗粒度 , 并统计上述多个子带的信道相关性, 该信道相关性用于表征子带间的信道 响应的一致性, 以及将上述信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗 粒度进行调整。
参阅图 2所示, 本发明实施例中, 用于进行赋形颗粒度调整的装置, 例如基站, 包括: 确定单元 20、 统计单元 21和调整单元 22, 其中,
确定单元 20, 用于确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当 前赋形颗粒度;
统计单元 21 , 用于统计上述多个子带的信道相关性, 该信道相关性用于表征子带间的 信道响应的一致性;
调整单元 22, 用于将上述信道相关性与预设条件进行比较, 根据比较结果对当前赋形 颗粒度进行调整。
基于上述系统架构, 本发明实施例中, 在系统执行预处理时, 网络侧需要进行初始赋 形颗粒度的选取, 本发明实施例中, 初始赋形颗粒度的选取方式包含但不限于以下两种: 方式 1 : 同一小区中所有终端的初始赋形颗粒度均设置为同一固定值。 可以按照小区 特点, 将不同小区之间的初始赋形颗粒度的取值设定为不同或相同。
方式 2: 静态自适应设置, 即同一小区中的不同用户的初始赋形颗粒度可以分别选取 相应的固定值。
初始赋形颗粒度选取完毕后, 网络侧需要根据网络环境的变化, 例如, 信道的空间相 关性、 频率选择性的变化等等, 对初始赋形颗粒度进行调整, 进一步地, 当网络环境再变 化时, 网络侧还需要对已调整的赋形颗粒度进行再次调整。 那么, 参阅图 3所示, 本发明 实施例中, 网络侧的基站对系统当前赋形颗粒度进行调整的详细流程如下:
步骤 300: 确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前赋形 颗粒度。
本发明实施例中, 对系统频域资源进行子带划分所依据的当前赋形颗粒度, 可以是初 始赋形颗粒度, 也可以是已经过调整的赋形颗粒度。
步骤 310: 统计多个子带的信道相关性。
实际应用中, 统计多个子带的信道相关性有多种实现方式, 本实施例中, 以下述方式 为例进行说明, 具体为:
分别统计每组相邻子带上各子带釆用的赋形权矢量之间的赋形权矢量相关系数, 基于 所有相邻子带的赋形权矢量相关系数, 计算用于表征信道相关性的指定参量; 其中, 该指 定参量可以为所有相邻子带的赋形权矢量相关系数的平均值、 所有相邻子带的赋形权矢量 相关系数中的最大值、 所有相邻子带的赋形权矢量相关系数中的最小值、 或者所有相邻子 带的赋形权矢量相关系数中, 大于预设门限值的赋形权矢量相关系数的数目占赋形权矢量 相关系数总数目的比例。
统计任意一组相邻子带上各子带釆用的赋形权矢量之间的赋形权矢量相关系数, 包 括:
若系统釆用单流传输方式, 则统计任意一组相邻子带上各子带釆用的一种赋形权矢量 之间的赋形权矢量相关系数;
若系统釆用多流传输方式, 则分别统计任意一组相邻子带上各子带釆用的每一级赋形 权矢量之间的赋形权矢量相关系数。
其中, 任意一组相邻子带上各子带釆用的赋形权矢量之间的赋形权矢量相关系数, 包 括: 任意一组相邻子带上各子带釆用的赋形权矢量之间的矢量内积的模值; 或者, 任意一 组相邻子带上各子带釆用的赋形权矢量的归一化矢量的的差值的范数, 其中, 所谓的赋形 权矢量的归一化矢量, 是将赋形权矢量按照其第一个元素进行归一化处理得到的。
步骤 320: 将信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗粒度进行 调整。
本实施例中, 执行步骤 320时, 将用于表征上述信道相关性的指定参量与预设的门限 值进行比较, 若确定上述指定参量大于或等于设定门限值, 则按照预设步长增大当前赋形 颗粒度, 若确定上述指定参量小于设定门限值, 则按照预设步长减小当前赋形颗粒度; 其 中, 所谓预设步长可以为固定步长, 也可以为可变步长。
例如: 假设子带宽度为 4 PRB, 分别统计三组相邻子带上各子带釆用的赋形权矢量之 间的赋形权矢量相关系数分别为 0.8、 0.76、 0.72, 计算用于表征信道相关性的所有相邻子 带的赋形权矢量相关系数的平均值为 0.75 , 将该平均值与设定门限值进行比较, 若确定上 述平均值大于或等于设定门限值, 则按照预设步长, 例如 2PRB, 增大当前赋形颗粒度, 即调整后的赋形颗粒度为 6PRB, 若确定上述平均值小于设定门限值, 则按照预设步长, 例如 1PRB, 减小当前赋形颗粒度, 即调整后赋形颗粒度为 3PRB; 其中, 当预设步长为可 变步长时, 其步长值可以参照上述平均值与设定门限值之间的差值选取相应的取值。
进一步地, 假设在上述赋形权矢量计算中, 以 1PRB为单位进行赋形权矢量的计算, 当前赋形颗粒度为 4PRB, 记三个子带上 PRB依次为 PRB1~PRB12, 当取任一 PRB上所 计算的赋形权矢量作为其归属的子带上的赋形权矢量时, 则可以仅计算 PRB1、 PRB3、 PRB5、 PRB7、 PRB9、 PRB11上的赋形权矢量, 这样当按照调整后的结果, 例如赋形颗粒 度增大为 6PRB, 则将 PRB1上计算所得赋形权矢量在 PRB1~PRB6上使用, PRB2上计算 所得赋形权矢量在 PRB7~PRB12上使用, 若赋形颗粒度减小为 2PRB时, 则将 PRB1上计 算所得的赋形权矢量在 PRB 1和 PRB2上使用, PRB3上计算所得的赋形权矢量在 PRB3和 PRB4上使用, PRB5上计算所得的赋形权矢量在 PRB5和 PRB6上使用, PRB7上计算所 得的赋形权矢量在 PRB7和 PRB 8上使用,PRB9上计算所得的赋形权矢量在 PRB9和 PRB 10上使用, PRB11上计算所得的赋形权矢量在 PRB11和 PRB 12上使用。这样避免了由于 赋形颗粒度更新带来的赋形权矢量重新计算, 降低了系统的运算量, 减少了资源消耗。
在执行步骤 320时, 根据系统传输的流数的不同亦有所区别, 包括:
若系统釆用单流 BF方式, 则统计任意一组相邻子带上各子带釆用的一种赋形权矢量 之间的赋形权矢量相关系数, 例如, 在相邻的子带 1和子带 2上, 子带 1釆用赋形权矢量 W1传输数据流, 而子带 2釆用赋形权矢量 W2传输数据流, 则统计 W1与 W2之间的赋 形权矢量相关系数 R12相关。
相应地, 假设系统带宽内仅存在上述子带 1和子带 2 , 则在执行步骤 320时, 需要将
R12相关作为用于表征子带 1和子带 2的信道相关性的指定参量与设定门限值进行比较, 当 R12相关 设定门限值时, 按照预设步长增大当前赋形颗粒度, 当 R12相关<设定门限 值时, 按照预设步长减小当前赋形颗粒度。
若系统釆用多流 BF方式, 则分别统计任意一组相邻子带上各子带釆用的每一级赋形 权矢量之间的赋形权矢量相关系数。 例如, 系统釆用双流 BF方式, 在相邻的子带 1和子 带 2上, 基于子带 1上信道的协方差矩阵进行特征分解获得的特征矢量集合中, 特征值最 大和次大的两个特征矢量分别为 W1和 W' l , 而为基于子带 2上信道的协方差矩阵进行特 征分解获得的特征矢量集合中, 特征值最大和次大的两个特征矢量分别为 W2和 W'2, 其 中, 各子带分别对应的特征矢量集合中, 特征值最大的特征矢量视为同一级别, 特征值次 大的特征矢量视为同一级别, 以此类推, 各特征矢量分别对应相应的级别, 那么, 本实施 例中, 需要统计 W1与 W2之间的赋形权矢量相关系数 R12相关, 以及 W' l和 W'2之间 的赋形权矢量相关系数 R' 12相关。
相应地, 假设系统带宽内仅存在上述子带 1和子带 2 , 则在执行步骤 320时, 需要将
R12相关和 R' 12相关作为用于表征子带 1和子带 2的信道相关性的指定参量,与设定门限 值进行比较, 当 R12相关 设定门限值 , 且 R' 12相关 设定门限值时, 按照预设步长增 大当前赋形颗粒度, 当 R12相关<设定门限值 , 且 R' 12相关<设定门限值时, 按照预设步 长减小当前赋形颗粒度。
在上述实施例中, 针对任意一个子带, 在计算其釆用的赋形权矢量时, 至少可以釆用 以下两种方式:
1、 将任意一子带按照预设的频域宽度划分为多个小子带, 并分别计算每一个小子带 上的赋形权矢量, 接着, 对各小子带的赋形权矢量进行归一化处理, 即按其第一个元素进 行归一, 得到各小子带的归一赋形权矢量, 再取其平均值作为上述任意一子带的赋形权矢 量。
2、 将任意一子带按照预设的频域宽度划分为多个小子带, 并分别计算每一个小子带 上的赋形权矢量, 将任意一小子带的赋形权矢量作为任意一子带的赋形权矢量。
例如,假设系统当前的赋形颗粒度为 N*G个 PRB ,即一个子带的频域宽度为 N*G个 PRB , 再将其划分为 N个小子带, 则每个小子带的频域宽度为 G个 PRB , 针对任意一个 小子带, 可以基于相应的 G个 PRB计算该小子带上的赋形权矢量 W, 并且将该任意一个 小子带上使用的 W作为其归属的子带上使用的赋形权矢量。
假设本发明实施例中网络侧是基于终端侧发送的 SRS信号来进行赋形权矢量计算的, 且 SRS釆用跳频方式, 并且 SRS发射占用的频域宽度为 4 PRB , 而当前子带, 即赋形颗粒 度的频域宽度为 8 PRB , 可以将子带划分为两个频宽宽度为 4 PRB的小子带, 那么, 如果 按照现有常规的方法计算任意一个子带上使用的赋形权矢量, 则网络侧需要等待相邻的两 个小子带的 SRS信道估计结果, 而釆用上述方法 2, 将赋形颗粒度和赋形权矢量频域平均 颗粒度进行了分离, 在任意一个子带内, 在任意一个小子带上接收到了 SRS信号, 便可以 进行赋形权矢量更新计算, 并在该赋形权矢量的时域有效时间内, 将其作为整个子带的赋 形权矢量使用, 从而避免了对 SRS跳频带宽的依赖。
区别于上述实施例, 实际应用中, 在执行步骤 310时, 即计算多个子带的信道相关性 时, 也可以釆用以下方式进行, 并不限于上述一种方法, 还可以按照以下方式实施: 第一种方式为: 记 和 H 分别为子带 1和子带 2上的第 k个子载波对应的信道响 应, 其中, H,1 G CMRXM^ , UK 2 e CM^ , M«、 ^分别为接收天线和发送天线的数 目, 将 和 分别按其第一个元素归一, 归一后得到的信道响应分别记为 ή 和 分别计算子带 1和子带 2 上归一后得到的信道响应的平均值, 分别为: g1 = l H 和 H2 =— ¾Η,2 , 其中, ,^2分别为子带 1和子带 2中子载波的个数, 则定义子带 1和 子带 2 的信道相关性 ^ ) , ^ 表示矩阵的迹, 或者定义子带 1和子 带 2 的信道相关性为
Figure imgf000009_0001
同理, 可以按照上述第一种方式求出系统带宽内任意两个相邻子带之间的信道相关 性, 然后, 再基于获得的各相邻子带的信道相关性, 计算用于表征系统带宽内多个子带的 信道相关性的指定参量, 该指定参量可以是各信道相关性的平均值、 各信道相关性中的最 大值、 各信道相关性中的最小值、 或者各信道相关性中大于预设门限值的信道相关性数目 占信道相关性总数目的比例, 在此不再赘述。
第三种方式: 计算子带 1 和子带 2 上信道的协方差矩阵, 分别为 R1 : ! !! !! 和
R2 = ]H,2¾2 , 对两协方差矩阵使用其第一个元素进行归一化处理, 得到 12 , 定 义子带 1 和子带 2 的信道相关性为 2|2 , 其中 |·|2表示矩阵的 2的范数。 同理, 可以按照上述第二种方式求出系统带宽内任意两个相邻子带之间的信道相关 性, 然后, 再基于获得的各相邻子带的信道相关性, 计算用于表征系统带宽内多个子带的 信道相关性的指定参量, 该指定参量可以是各信道相关性的平均值、 各信道相关性中的最 大值、 各信道相关性中的最小值、 或者各信道相关性中大于预设门限值的信道相关性数目 占信道相关性总数目的比例, 在此不再赘述。
区别于上述两种信道相关性的计算方式, 实际应用中, 还可以按照以下方式计算多个 子带的信道相关性, 并按照获得的信道相关性与预设条件的比较结果对当前赋形颗粒度进 行调整。 具体为:
计算间隔指定频域宽度的两个子带上使用的赋形权矢量之间的赋形权矢量相关系数, 将该赋形权矢量相关系数直接作为表征信道相关性的参量。 这样, 可以将上述赋形权矢量 相关系数与预设门限值进行比较, 若未超过该预设门限值, 则将上述指定频域宽度作为重 新设定的当前赋形颗粒度。 其中, 赋形权矢量相关系数的计算方式、 赋形权矢量的计算方 式, 均可以参照步骤 310和步骤 320中记载的方案执行, 在此不再赘述。
例如, 假设子带宽度为 4PRBs, 基于子带 1和子带 2之间的赋形权矢量相关系数 R 12 相关, 若 W12相关的取值小于预设门限, 则将 4PRB继续作为当前赋形颗粒度使用, 若 W12相关的取值不小于预设门限,则可以再次计算子带 1和子带 3之间的赋形权矢量相关 系数 W13相关, 若 W13相关的取值小于预设门限, 则将 8PRB作为当前赋形颗粒度使用, 若 W13相关的取值仍不小于预设门限,则可以继续计算子带 1和子带 4之间的赋形权矢量 相关系数 W14相关, 并按照同样方式继续对当前赋形颗粒度进行调整, 以此类推, 直到挑 选到合适的赋形颗粒度或达到系统的最大带宽为止, 当达到系统最大带宽而仍未找到合适 的赋形颗粒度, 则赋形颗粒度取为系统带宽。
由此可见, 信道相关性的计算方式并不仅限于步骤 310中介绍的一种, 步骤 310中记 载的方式仅为优选的实施方式, 并不局限于此。
综上所述 , 本发明实施例中, 针对系统内基于赋形颗粒度划分出的若千子带, 计算 其信道相关性, 该信道相关性用于表征子带间的信道响应的一致性, 从而反应了信道状态 的变化, 接着, 将获得的信道相关性与预设条件进行比较, 并根据比较结果对当前赋形颗 粒度进行调整, 这样, 便实现了基于信道状态变化的赋形颗粒度自适应调整, 从而有效提 高了系统的赋形增益, 进而提升了系统性能。
本领域内的技术人员应明白, 本发明的实施例可提供为方法、 系统、 或计算机程序产 品。 因此, 本发明可釆用完全硬件实施例、 完全软件实施例、 或结合软件和硬件方面的实 施例的形式。 而且, 本发明可釆用在一个或多个其中包含有计算机可用程序代码的计算机 可用存储介盾 (包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形 式。
本发明是参照根据本发明实施例的方法、 设备(系统)、 和计算机程序产品的流程图 和 /或方框图来描述的。 应理解可由计算机程序指令实现流程图和 /或方框图中的每一流 程和 /或方框、 以及流程图和 /或方框图中的流程和 /或方框的结合。 可提供这些计算机 程序指令到通用计算机、 专用计算机、 嵌入式处理机或其他可编程数据处理设备的处理器 以产生一个机器, 使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用 于实现在流程图一个流程或多个流程和 /或方框图一个方框或多个方框中指定的功能的 装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方 式工作的计算机可读存储器中, 使得存储在该计算机可读存储器中的指令产生包括指令装 置的制造品, 该指令装置实现在流程图一个流程或多个流程和 /或方框图一个方框或多个 方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机 或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理, 从而在计算机或其他 可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和 /或方框图一个 方框或多个方框中指定的功能的步骤。
显然, 本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和 范围。这样,倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内, 则本发明也意图包含这些改动和变型在内。

Claims

权 利 要 求
1、 一种调整赋形颗粒度的方法, 其特征在于, 包括:
确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前赋形颗粒度; 统计所述多个子带的信道相关性, 该信道相关性用于表征子带间的信道响应的一致 性;
将信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗粒度进行调整。
2、 如权利要求 1所述的方法, 其特征在于, 统计所述多个子带的信道相关性, 包括: 分别统计每组相邻子带上各子带釆用的赋形权矢量之间的赋形权矢量相关系数; 基于所有相邻子带的赋形权矢量相关系数, 计算用于表征所述多个子带的信道相关性 的指定参量。
3、 如权利要求 2 所述的方法, 其特征在于, 所述指定参量为所有相邻子带的赋形权 矢量相关系数的平均值、 最大值或最小值,
或者, 所述指定参量为所有相邻子带的赋形权矢量相关系数中, 大于预设门限值的赋 形权矢量相关系数的数目, 占赋形权矢量相关系数总数目的比例。
4、 如权利要求 2 所述的方法, 其特征在于, 统计任意一组相邻子带上各子带釆用的 赋形权矢量之间的赋形权矢量相关系数, 包括:
若系统釆用单流传输方式, 则统计任意一组相邻子带上各子带釆用的一种赋形权矢量 之间的赋形权矢量相关系数;
若系统釆用多流传输方式, 则分别统计任意一组相邻子带上各子带釆用的每一级赋形 权矢量之间的赋形权矢量相关系数。
5、 如权利要求 4 所述的方法, 其特征在于, 所述任意一组相邻子带上各子带釆用的 赋形权矢量之间的赋形权矢量相关系数, 包括:
所述任意一组相邻子带上各子带釆用的赋形权矢量之间的矢量内积的模值; 或者, 所 述任意一组相邻子带上各子带釆用的赋形权矢量的归一化矢量的差值的范数。
6、 如权利要求 2 - 5任一项所述的方法, 其特征在于, 计算任意一子带釆用的赋形权 矢量时, 包括:
将所述任意一子带按照预设的频域宽度划分为多个小子带, 并分别计算每一个小子带 上的赋形权矢量;
对各小子带的赋形权矢量进行归一化处理, 得到各小子带的归一赋形权矢量, 再取其 平均值作为所述任意一子带的赋形权矢量; 或者, 将任意一小子带的赋形权矢量作为所述 任意一子带的赋形权矢量。
7、 如权利要求 2 - 5任一项所述的方法, 其特征在于, 所述将信道相关性与预设条件 进行比较, 根据比较结果对当前赋形颗粒度进行调整, 包括:
将用于表征所述信道相关性的指定参量与预设的门限值进行比较;
若确定所述指定参量大于或等于设定门限值, 则按照预设步长增大所述当前赋形颗粒 度;
若确定所述指定参量小于设定门限值, 则按照预设步长减小所述当前赋形颗粒度。
8、 如权利要求 1 所述的方法, 其特征在于, 所述统计多个子带的信道相关性, 将信 道相关性与预设条件进行比较, 根据比较结果对当前赋形颗粒度进行调整, 包括:
计算间隔指定频域宽度的两个子带上使用的赋形权矢量之间的赋形权矢量相关系数, 将该赋形权矢量相关系数作为表征所述信道相关性的参量;
当所述赋形权矢量相关系数未超过预设门限值时, 将所述指定频域宽度设定为当前赋 形颗粒度。
9、 一种用于调整赋形颗粒度的装置, 其特征在于, 包括:
确定单元, 用于确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前 赋形颗粒度;
统计单元, 用于统计所述多个子带的信道相关性, 该信道相关性用于表征子带间的信 道响应的一致性;
调整单元, 用于将所述信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗 粒度进行调整。
10、 如权利要求 9所述的装置, 其特征在于,
所述统计单元分别统计每组相邻子带上各子带釆用的赋形权矢量之间的赋形权矢量 相关系数; 基于所有相邻子带的赋形权矢量相关系数, 计算用于表征所述信道相关性的指 定参量。
11、如权利要求 10所述的装置, 其特征在于, 所述统计单元获得的指定参量为所有相 邻子带的赋形权矢量相关系数的平均值、 最大值或最小值,
或者所述统计单元获得的指定参量为所有相邻子带的赋形权矢量相关系数中, 大于预 设门限值的赋形权矢量相关系数的数目, 占赋形权矢量相关系数总数目的比例。
12、 如权利要求 10所述的装置, 其特征在于,
若系统釆用单流传输方式, 则所述统计单元统计任意一组相邻子带上各子带釆用的一 种赋形权矢量之间的赋形权矢量相关系数;
若系统釆用多流传输方式, 则所述统计单元分别统计任意一组相邻子带上各子带釆用 的每一级赋形权矢量之间的赋形权矢量相关系数。
13、 如权利要求 12 所述的装置, 其特征在于, 所述统计单元统计的任意一组相邻子 带上各子带釆用赋形权矢量之间的赋形权矢量相关系数, 包括: 所述任意一组相邻子带上各子带釆用的赋形权矢量之间的矢量内积的模值; 或者, 所 述任意一组相邻子带上各子带釆用的赋形权矢量的归一化矢量的的差值的范数。
14、 如权利要求 10 - 13 任一项所述的装置, 其特征在于, 所述统计单元计算任意一 子带釆用的赋形权矢量时, 包括:
所述统计单元将所述任意一子带按照预设的频域宽度划分为多个小子带, 并分别计算 每一个小子带上的赋形权矢量;
所述统计单元对各小子带的赋形权矢量进行归一化处理, 得到各小子带的归一赋形权 矢量, 再取其平均值作为所述任意一子带的赋形权矢量; 或者, 将任意一小子带的赋形权 矢量作为所述任意一子带的赋形权矢量。
15、 如权利要求 10 - 13任一项所述的装置, 其特征在于,
所述调整单元将用于表征所述信道相关性的指定参量与预设的门限值进行比较; 若确定所述指定参量大于或等于设定门限值, 则所述调整单元按照预设步长增大所述 当前赋形颗粒度;
若确定所述指定参量小于设定门限值, 则所述调整单元按照预设步长减小所述当前赋 形颗粒度。
16、 如权利要求 9所述的装置, 其特征在于,
所述统计单元计算间隔指定频域宽度的两个子带上使用的赋形权矢量之间的赋形权 矢量相关系数, 将该赋形权矢量相关系数作为表征所述信道相关性的参量;
所述调整单元当所述赋形权矢量相关系数未超过预设门限值时, 将所述指定频域宽度 设定为当前赋形颗粒度。
17、 一种用于调整赋形颗粒度的系统, 包括若千基站, 其特征在于,
所述基站, 用于确定系统频域资源被划分出的多个子带, 每个子带的频域宽度为当前 赋形颗粒度 , 并统计所述多个子带的信道相关性, 该信道相关性用于表征子带间的信道响 应的一致性, 以及将所述信道相关性与预设条件进行比较, 根据比较结果对当前赋形颗粒 度进行调整。
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