WO2020248443A1 - 一种基于二维相控天线阵列的快速精确波束跟踪方法 - Google Patents
一种基于二维相控天线阵列的快速精确波束跟踪方法 Download PDFInfo
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- 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
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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- the invention belongs to the field of communication technology, relates to millimeter wave mobile communication, and particularly relates to a fast and accurate beam tracking method based on a two-dimensional phased antenna array.
- millimeter wave communication have broad application prospects. Due to the short wavelength, millimeter wave communication systems are often equipped with large-scale antennas to achieve high array gain, which makes the millimeter wave beam very narrow, and a slight misalignment may cause huge energy loss.
- beam alignment can be achieved through pilot training, which will occupy huge pilot resources.
- pilot training In a scene where the channel changes rapidly, the alignment cannot be achieved directly by means of pilot training. Therefore, it is necessary to achieve accurate beam tracking with as little pilot overhead as possible in mobile scenarios.
- IEEE 802.11ad proposes a simple dynamic tracking algorithm, which switches between the current beam and adjacent beams based on the received signal strength.
- Kalman filtering is applied to the beam tracking problem, using the beam direction and channel coefficients as the system state, and applying the extended Kalman filtering method for tracking.
- these methods do not optimize the detection beamforming vector.
- the tracking performance is closely related to the selected detection beamforming vector.
- the purpose of the present invention is to provide a fast and accurate beam tracking method based on a two-dimensional phased antenna array.
- the pilot overhead used should be as small as possible and the detection beamforming vector should be optimized. , In order to achieve the highest possible tracking accuracy and the fastest possible tracking speed.
- a fast and accurate beam tracking method based on a two-dimensional phased antenna array which is characterized in that it periodically works in detection and communication modes alternately.
- the beam is directed to several detection directions in sequence, and the communication
- the phase beam points to the beam direction estimated at the time.
- the beam tracking method includes the following steps:
- Step A According to the time-varying characteristics of the channel, the channel is divided into three types: 1) quasi-static scene; 2) dynamic type I; 3) dynamic type II. Determine which type of channel to be tracked belongs to;
- Step B In the detection period of each detection communication cycle, based on the channel type determined in step A, according to the three types of beam tracking methods, determine the direction of sequential detection, and obtain according to the detection results and historically recorded information Estimation of channel coefficients and beam direction;
- Step C Point the beam to the beam direction estimation obtained in Step B for communication.
- the quasi-static scene refers to a situation where the channel coefficient and the beam direction change very slowly: ⁇ k ⁇ k-1 , x k ⁇ x k-1 .
- ⁇ k refers to the channel coefficient of the k-th probing communication cycle
- x k refers to the direction parameter vector of the k-th probing communication cycle
- x k, 1 , x k, 2 are the values of the two dimensions of the two-dimensional direction parameter vector x k , respectively
- ⁇ k , ⁇ k refer to the elevation angle and azimuth angle of the arrival beam direction in the k-th detection communication cycle.
- M, N are the number of antennas in two directional dimensions of the two-dimensional area array antenna
- d 1 , d 2 are the distances between adjacent antennas in the two directional dimensions of the area array antenna
- ⁇ is the millimeter wave wavelength.
- step A the dynamic type I refers to the situation where the channel coefficient changes rapidly and the beam direction changes very slowly: ⁇ k ⁇ ⁇ k-1 , x k ⁇ x k-1 .
- step A the dynamic type II refers to the situation where both the channel coefficient and the beam direction change rapidly: ⁇ k ⁇ ⁇ k-1 , x k ⁇ x k-1 .
- step B the tracking steps for the quasi-static scene are as follows:
- Step 11 Obtain the initial direction estimation in the real beam main lobe range and the initial estimation of the channel coefficients.
- the initial estimation method used may include, but is not limited to, beam scanning: in one probing communication cycle, M ⁇ N pilots are sent, and these pilots are used to perform M ⁇ N detections in different directions.
- OMP Orthogonal Matching Pursuit
- Step 12 In the detection period of each detection communication cycle, three pilots are sent in sequence to perform three detections in different directions.
- the detection direction is the last estimated direction plus three sets of fixed offsets ⁇ S,1 , ⁇ S,2 , ⁇ S,3 , these three sets of offsets are located on a ring of the two-dimensional plane: 0.4 ⁇
- ⁇ 0.6,i 1, 2, 3.
- the three sets of offsets can be optimized according to the target to be tracked.
- the optimization targets include but are not limited to the mean square error of the channel vector and the mean square error of the direction parameter vector.
- Step 13 based on the detection results and historically recorded information, update the estimated value using a random iteration method.
- the random iteration method used may include, but is not limited to, the random Newton method.
- step B for the dynamic type I, only the beam direction is tracked.
- step B the tracking steps for dynamic type I are as follows:
- Step 21 Obtain an initial direction estimate in the real beam main lobe range.
- the initial estimation method used may include but is not limited to beam scanning: in the first L probing communication cycles, each probing communication cycle sends M ⁇ N pilots, using these pilots, each probing communication cycle performs M ⁇ N Detection in different directions.
- the selection of L must ensure that the maximum signal energy of M ⁇ N different detection directions received in the L-th detection communication cycle is greater than a certain threshold. Then use the detection result of the L-th detection communication cycle to obtain an initial estimate of the beam direction.
- Step 22 In the detection period of each detection communication cycle, three pilots are sent in sequence to perform three detections in different directions.
- the detection direction is the last estimated direction plus three sets of fixed offsets ⁇ DI,1 , ⁇ DI,2 , ⁇ DI,3 , these three sets of offsets are located on a ring of the two-dimensional plane 0.5 ⁇
- ⁇ 0.7, i 1, 2, 3.
- the three sets of offsets can be optimized according to the target to be tracked.
- the optimization target includes but is not limited to the mean square error of the direction parameter vector.
- Step 23 based on the detection result and historically recorded information, update the estimated value using a random iteration method.
- the random iteration method used may include, but is not limited to, the random Newton method.
- step B the tracking steps for dynamic type II are as follows:
- Step 31 Obtain an initial direction estimate in the real beam main lobe range and an initial estimate of channel coefficients.
- the initial estimation method adopted may include, but is not limited to, beam scanning: in one probing communication cycle, M ⁇ N pilots are sent in sequence, and these pilots are used to perform M ⁇ N detections in different directions. According to the OMP algorithm, an initial estimate of the channel coefficients and beam direction is obtained.
- Step 32 In the detection period of each detection communication cycle, three pilots are sent in sequence to perform three detections in different directions.
- the detection direction is the last estimated direction plus three sets of fixed offsets ⁇ DII,1 , ⁇ DII,2 , ⁇ DII,3 , these three sets of offsets are located on a ring in the two-dimensional plane: 0.4 ⁇
- ⁇ 0.6,i 1, 2, 3.
- the three sets of offsets can be optimized according to the target to be tracked.
- the optimization targets include but are not limited to the mean square error of the channel vector and the mean square error of the direction parameter vector.
- Step 33 based on the detection result and historically recorded information, update the estimated value using a random iteration method.
- the random iteration method used may include, but is not limited to, the random Newton method.
- the method can reach the Cramer-Road lower bound (CRLB) of the two-dimensional beam tracking error asymptotically.
- CRLB Cramer-Road lower bound
- the tracking method can achieve higher tracking accuracy and faster tracking speed.
- Fig. 1 is a schematic diagram of a two-dimensional phased antenna array structure according to an embodiment of the present invention.
- Fig. 2 is a frame structure of a beam tracking method in a quasi-static scene according to an embodiment of the present invention.
- Fig. 3 is a diagram showing an example of the optimal offset of the beam tracking detection direction in a quasi-static scene according to an embodiment of the present invention.
- Fig. 4 is a performance simulation diagram of a beam tracking method in a quasi-static scene according to an embodiment of the present invention.
- Fig. 5 is a frame structure of a dynamic I-beam tracking method according to an embodiment of the present invention.
- Fig. 6 is a diagram showing an example of the optimal offset of the dynamic I-beam tracking detection direction according to an embodiment of the present invention.
- Fig. 7 is a performance simulation diagram of a dynamic I-beam tracking method according to an embodiment of the present invention.
- Fig. 8 is a performance simulation diagram of a dynamic type II beam tracking method according to an embodiment of the present invention.
- This method studies the tracking problem at the receiving end, and the tracking at the transmitting end can be achieved through channel reciprocity.
- the planar antenna array is composed of M ⁇ N elements distributed in a rectangular area, and the distance between adjacent elements in the x(y) axis is d 1 ( d 2 ).
- the receiver uses an analog beamforming architecture, and each element is connected to the same RF link through a separate phase shifter. In this embodiment, the channel remains unchanged during the probing communication period.
- the transmitter transmits the q same known pilot s p, for estimating the channel coefficients and the beam direction of arrival.
- the millimeter wave scattering effect is weak, and there is only a direct path and a small amount of reflection path in the channel. Because the angle extension is small, the mutual interference between multipaths is quite weak. Therefore, each path in the multipath can be tracked independently. This embodiment focuses on the tracking method of one path, and other multipaths can be tracked independently by the same method.
- the direction of the beam arrival beam to be studied is ( ⁇ k , ⁇ k ), where ⁇ k is the elevation angle of the arrival beam direction, and ⁇ k is the azimuth angle of the arrival beam direction.
- the channel vector of this path can be expressed as
- a(x k ) [a 11 (x k )...a 1N (x k )a 21 (x k )...a MN (x k )] T , (2)
- ⁇ is the millimeter wave wavelength.
- ⁇ k,i represents the detection direction vector corresponding to w k,i
- the detection direction of the receiver can be adjusted by changing ⁇ k,i .
- constraints (8) Ensure Is the channel vector The unbiased estimation of, the constraint (9) ensures that the detection direction of each detection communication cycle is the last estimated direction plus three sets of fixed offsets.
- JBCT Joint Beam and Channel Tracking
- the beam direction obeys uniform distribution:
- the channel coefficient obeys the Rice distribution, and the Rice factor is 15dB.
- the average result obtained after 1000 system simulations is shown in Figure 4. It can be seen that the proposed tracking method can asymptotically reach the minimum CRLB of the channel vector mean square error, and the tracking accuracy is much higher than the existing algorithm.
- ⁇ k obeys the Rayleigh distribution, and At this time, the conditional probability density function of the observation vector y k is
- ⁇ y (x) is the covariance matrix of the observation vector y k :
- J 3 is the unit matrix of order 3, and the determinant of ⁇ y (x) is
- the present invention considers a specific set of causal tracking strategies ⁇ DI : the detection beamforming matrix W k and system estimation of the k-th detection communication cycle All are determined by the previously used detection beamforming matrices W 1 , W 2 ,...W k-1 and historical observations y 1 , y 2 ,...y k . Therefore, in the k-th detection communication cycle, the tracking problem of the beam direction can be formulated as:
- constraints (19) ensure It is an unbiased estimation of the direction parameter vector x, the constraint (20) ensures that the detection direction of each detection communication cycle is the last estimated direction plus three sets of fixed offsets
- RBT Recursive Beam Tracking
- the total number of detection communication cycles L at this stage is determined by the following formula
- the present invention considers a specific set of causal tracking strategies ⁇ DII : the probe beamforming matrix W k and system estimation for the k-th probe communication cycle All are determined by the previously used detection beamforming matrices W 1 , W 2 ,...W k-1 and historical observations y 1 , y 2 ,...y k . Therefore, in the k-th probing communication cycle, the tracking problem of channel coefficient and beam direction can be formulated as:
- constraints (29) ensure Is the channel vector
- the constraint (30) ensures that the detection direction of each detection communication cycle is the last estimated direction plus three sets of fixed offsets.
- JBCT Joint Beam and Channel Tracking
- the initial channel coefficient ⁇ 0 obeys the Rice distribution, and the Rice factor is 15dB.
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Abstract
本发明提出了一种基于二维相控天线阵列的快速精确波束跟踪方法，本方法适用于毫米波移动通信。通过将时变信道划分为准静态场景、动态I型和动态II型三种情形，该方法采用优化后的探测方向，根据随机牛顿法跟踪每种情形下的信道参量。该方法的优点在于：能实现二维波束方向和信道系数联合跟踪的最小导频开销；针对准静态场景和动态I型，该方法的性能可以逼近跟踪误差的克拉美罗下界；针对动态II型，该方法能实现更高的跟踪精度和更快的跟踪速度。
Description
本发明属于通信技术领域，涉及毫米波移动通信，特别涉及一种基于二维相控天线阵列的快速精确波束跟踪方法。
巨大的带宽优势使得毫米波通信具有广阔的应用前景。由于波长较短，毫米波通信***常常配备大规模的天线以实现高阵列增益，这使得毫米波波束很窄，轻微的对不准就可能造成巨大的能量损失。在信道变化很慢的静态场景或准静态场景下，波束对准可以通过导频训练的方式来实现，这会占用巨大的导频资源。然而，在信道快速变化的场景下，无法直接通过导频训练的方式实现对准。因此，移动场景下用尽可能少的导频开销实现精确的波束跟踪是必要的。
同时，随着天线数目的增多和载频的提高，毫米波通信中采用全数字波束成形架构的硬件开销和能量损耗都巨大无比。一种经济可行的解决方式是采用模拟波束成形架构。当采用模拟波束成形架构时，接收机每次只能获得一个特定方向的观测，所选取的探测波束成形矢量会对***性能产生很大的影响。因此，如何选取探测波束成形矢量，从而实现对波束的精确跟踪，是快速移动场景下毫米波通信的重要问题。
针对移动场景下的毫米波波束跟踪问题，已存在一系列的研究算法。通过利用毫米波信道的稀疏特性，一种基于压缩感知的算法被提出。然而，这种算法主要针对静态或准静态场景设计，在快速移动的场景中算法性能较差。IEEE 802.11ad中提出了一种简单的动态跟踪算法，它基于接收到的信号强度，在当前波束和相邻波束间切换。有人把卡尔曼滤波的思想应用到了波束跟踪问题中，以波束方向和信道系数作为***状态，应用扩展卡尔曼滤波的方法进行跟踪。然而，这些方法都没有对探测波束成形矢量进行优化，在模拟波束成形架构中， 跟踪的性能跟选取的探测波束成形矢量密切相关，没有优化探测波束成形矢量使得这些算法的跟踪精度都不够高。基于一维天线阵列，一种信道系数和波束方向联合跟踪的算法被提出，并且对探测波束成形矢量进行了优化。然而，该算法只能支持一维波束方向的跟踪，在诸如无人机通信的很多场景下，波束方向可能从不同的水平和垂直方向到达，因此，需要对二维的波束方向同时进行跟踪。
发明内容
为了克服上述现有技术的缺点，本发明的目的在于提供一种基于二维相控天线阵列的快速精确波束跟踪方法，其采用的导频开销要尽可能小，要对探测波束成形矢量进行优化，以实现尽可能高的跟踪精度和尽可能快的跟踪速度。
为了实现上述目的，本发明采用的技术方案是：
一种基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，周期式交替地工作在探测和通信模式，在一个探测通信周期内的探测时段，波束依次指向若干个探测方向，通信阶段波束指向当时估计出的波束方向。
波束跟踪方法包括如下步骤：
步骤A,根据信道的时变特性，将信道划分为三种类型：1)准静态场景；2)动态I型；3)动态II型。确定待跟踪的信道属于哪种类型；
步骤B,在每个探测通信周期的探测时段，基于步骤A中确定的信道类型，依照对应于三种类型的波束跟踪方法，确定依次探测的方向，根据探测结果及历史上记录的信息，获得信道系数和波束方向的估值；
步骤C,将波束指向步骤B中获得的波束方向估值进行通信。
步骤A中，准静态场景是指信道系数和波束方向都变化很慢的情况：β
k≈β
k-1,x
k≈x
k-1。其中β
k指第k个探测通信周期的信道系数，x
k指第k个探测通信周期的方向参数矢量：
x
k,1,x
k,2分别为 二维方向参数矢量x
k两个维度的值，θ
k,φ
k分别指第k个探测通信周期到达波束方向的俯仰角和方位角。M,N为二维面阵天线的两个方向维度的天线数目，d
1,d
2为面阵天线两个方向维度上的相邻天线间距，λ为毫米波波长。
步骤A中，动态I型是指信道系数快速变化，波束方向变化很慢的情况：β
k≠β
k-1,x
k≈x
k-1。
步骤A中，动态II型是指信道系数和波束方向都快速变化的情况：β
k≠β
k-1,x
k≠x
k-1。
步骤B中，针对准静态场景的跟踪步骤如下：
步骤11，获得在真实波束主瓣范围的初始方向估计以及信道系数的初始估计。采用的初始估测方法可包括但不限于波束扫描：在1个探测通信周期内，发送M×N个导频，利用这些导频，进行M×N个不同方向的探测。根据正交匹配跟踪(Orthogonal Matching Pursuit，OMP)算法，获得信道系数和波束方向的初始估计；
步骤12，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测。探测的方向为上一次估测的方向加上三组固定偏移量Δ
S,1,Δ
S,2,Δ
S,3，这三组偏移量位于二维平面的一个环上：0.4≤|Δ
S,i|≤0.6,i＝1,2,3。三组偏移量可依据要跟踪的目标进行优化，优化目标包括但不限于信道矢量的均方误差，方向参数矢量的均方误差。
步骤13，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值。采用的随机迭代法可包括但不限于随机牛顿法。
步骤B中，针对动态I型，只跟踪波束方向。
步骤B中，针对动态I型的跟踪步骤如下：
步骤21，获得在真实波束主瓣范围的初始方向估计。采用的初始估测方法可包括但不限于波束扫描:在前L个探测通信周期内，每个探测通信周期发送M×N个导频，利用这些导频，每个探测通信周期进行M×N个不同方 向的探测。L的选取要保证在第L个探测通信周期接收到的M×N个不同探测方向的最大信号能量大于某个阈值。然后利用第L个探测通信周期的探测结果，获得波束方向的初始估计。
步骤22，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测。探测的方向为上一次估测的方向加上三组固定偏移量Δ
DI,1,Δ
DI,2,Δ
DI,3，这三组偏移量位于二维平面的一个环上0.5≤|Δ
DI,i|≤0.7,i＝1,2,3。三组偏移量可依据要跟踪的目标进行优化，优化目标包括但不限于方向参数矢量的均方误差。
步骤23，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值。采用的随机迭代法可包括但不限于随机牛顿法。
步骤B中，针对动态II型的跟踪步骤如下：
步骤31，获得在真实波束主瓣范围的初始方向估计以及信道系数的初始估计。采用的初始估测方法可包括但不限于波束扫描：在1个探测通信周期内，依次发送M×N个导频，利用这些导频，进行M×N个不同方向的探测。根据OMP算法，获得信道系数和波束方向的初始估计。
步骤32，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测。探测的方向为上一次估测的方向加上三组固定偏移量Δ
DII,1,Δ
DII,2,Δ
DII,3，这三组偏移量位于二维平面的一个环上：0.4≤|Δ
DII,i|≤0.6,i＝1,2,3。三组偏移量可依据要跟踪的目标进行优化，优化目标包括但不限于信道矢量的均方误差，方向参数矢量的均方误差。
步骤33，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值。采用的随机迭代法可包括但不限于随机牛顿法。
与现有技术相比，本发明的有益效果是：
(1)实现了二维信道系数和波束方向联合跟踪的最小导频开销。
(2)在静态场景和动态I型中，该方法能渐近达到二维波束跟踪误差的克拉 美罗下界(CRLB)。
(3)在动态II型中，相比已有技术，该跟踪方法能实现更高的跟踪精度和更快的跟踪速度。
图1为根据本发明一个实施例的二维相控天线阵列结构示意图。
图2为根据本发明一个实施例的准静态场景下波束跟踪方法的帧结构。
图3为根据本发明一个实施例的准静态场景下波束跟踪探测方向的最优偏移示例图。
图4为根据本发明一个实施例的准静态场景下波束跟踪方法性能仿真图。
图5为根据本发明一个实施例的动态I型波束跟踪方法的帧结构。
图6为根据本发明一个实施例的动态I型波束跟踪探测方向的最优偏移示例图。
图7为根据本发明一个实施例的动态I型波束跟踪方法性能仿真图。
图8为根据本发明一个实施例的动态II型波束跟踪方法性能仿真图。
下面详细描述本发明的实施例，实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，仅用于解释本发明，而不能理解为对本发明的限制。
本方法研究接收端的跟踪问题，发射端的跟踪可以通过信道互易性实现。
考虑如图1所示的二维相控阵列天线接收机：平面天线阵列由M×N个分布在矩形区域内的阵子构成，x(y)轴方向相邻阵子之间的距离为d
1(d
2)。接收机采用模拟波束成形架构，每一个阵子通过单独的移相器连接到同一个射频链路上。本实施例中，信道在探测通信周期内保持不变。在每个探测通信周期的探测时段，发射机发射q个相同的已知导频s
p，用以估测信道系数和到达的波束方向。
毫米波散射效应较弱，信道中仅仅存在一条直射径和少量的反射径。由于角度扩展很小，多径之间的相互干扰相当微弱。因此，可以独立地跟踪多径中的每一径。本实施例重点研究一径的跟踪方法，其它多径可以通过相同的方法独立跟踪。在第k个探测通信周期，要研究的该径到达波束方向为(θ
k,φ
k)，其中θ
k为到达波束方向的俯仰角，φ
k为到达波束方向的方位角。这一径的信道矢量可以表示为
h
k＝β
ka(x
k), (1)
其中
为复信道系数，
为由(θ
k,φ
k)决定的方向参数矢量，a(x
k)为导向矢量
a(x
k)＝[a
11(x
k)…a
1N(x
k)a
21(x
k)…a
MN(x
k)]
T, (2)
其中
λ为毫米波波长。
在第k个探测通信周期的探测时段，用w
k,i(i＝1,…q)表示接收第i个导频符号所用的探测波束成形矢量，考虑w
k,i也具有导向矢量的形式，
其中γ
k,i表示对应于w
k,i的探测方向矢量，通过改变γ
k,i可以调整接收机的探测方向。在移相和合并后，接收机最终获得的基带输出信号为
其中
为复循环高斯随机变量。定义
为第k个探测通信周期的信道参数矢量，
为探测波束成形矩阵，
为噪声矢量，则可将(4)中接收机获得的基带输出信号重写为
在准静态场景、动态I型和动态II型场景下，要保证利用每个探测通信周期的探测结果获得信道参数矢量的唯一估计，所需的最小导频开销均为每探测通信周期3个导频，因此q＝3。
接下来给出不同信道变化场景下的波束跟踪方法。
1)准静态场景
该场景下，信道系数和波束方向都变化很慢，可近似为β
k＝β,x
k＝x，因此
此时观测矢量y
k的条件概率密度函数为
用
表示一种信道系数和波束方向的跟踪策略，考虑特定的因果跟踪策略集合Ξ
S：第k个探测通信周期的探测波束成形矩阵W
k和***估计
均由以前使用的探测波束成形矩阵W
1,W
2,…W
k-1和历史观测y
1,y
2,…y
k决定。因此，在第k个探测通信周期，信道系数和波束方向的跟踪问题可以公式化为：
其中约束(8)
(8)确保
是信道矢量
的无偏估计，约束(9)确保每个探测通信周期的探测方向为上一次估测的方向加上三组固定偏移量。
在准静态场景下，本实施例设计一种两阶段的跟踪方案：波束和信道联合跟踪(Joint Beam and Channel Tracking,JBCT)，具体如下：
(i)粗波束扫描。如图2所示，在一个探测通信周期内，接收机依次接收M×N个导频，对应于观测
的探测波束成形矢量为
信道系数和波束方向的初始估计如下所示：
其中
采用的码本尺寸为M
0×N
0(M
0≥M,N
0≥N),
X
+＝(X
HX)
-1X
H.
(ii)信道系数和波束方向联合跟踪。在第k个探测通信周期的探测时段，接收机依次接收3个导频，所采用的3个探测波束成形矢量如下所示：
其中
是准静态场景下天线数目趋于无穷时渐近最优的探测方向偏移，由图3和表1给出：
表1 准静态场景下渐近最优的探测偏移
信道参数矢量估测
由随机牛顿法更新：
其中
是跟踪步长。Fisher信息矩阵
定义如下
设置***参数为：天线数目M＝N＝8，天线间距
粗波束扫描的码本尺寸M
0＝2M,N
0＝2N,导频符号s
p＝1，发射信噪比
波束方向服从均匀分布：
信道系数服从莱斯分布，莱斯因子为15dB。进行1000次***仿真后取平均得到的结果如图4所示，可以看出，所提出的跟踪方法能够渐近到达信道矢量均方误差的最小CRLB,跟踪精度远高于已有算法。
2)动态I型
该场景下，信道系数快速变化，但波束方向都变化很慢，可近似为x
k＝x。本实施例中β
k服从Rayleigh分布，且
此时观测矢量y
k的条件概率密度函数为
其中∑
y(x)为观测矢量y
k的协方差矩阵：
J
3为3阶的单位阵，∑
y(x)的行列式为
用
表示一种波束方向的跟踪策略，本发明考虑特定的因果跟踪策略集合Ξ
DI：第k个探测通信周期的探测波束成形矩阵W
k和***估计
均由以前使用的探测波束成形矩阵W
1,W
2,…W
k-1和历史观测y
1,y
2,…y
k决定。因此，在第k个探测通信周期，波束方向的跟踪问题可以公式化为：
其中约束(19)确保
是方向参数矢量x的无偏估计，约束(20)确保每个探测通信周期的探测方向为上一次估测的方向加上三组固定偏移量
针对动态I型，本实施例设计一种两阶段的跟踪方案：递归的波束跟踪(Recursive Beam Tracking，RBT)，具体如下：
(i)粗波束扫描。如图5所示，在前L个探测通信周期内，接收机每个探测通信周期接收M×N个导频，对应于观测
的探测波束成形矢量为
该阶段的总探测通信周期数L由下式决定
信道系数和波束方向的初始估计如下所示：
其中
采用的码本尺寸为M
0×N
0(M
0≥M,N
0≥N),
X
+＝(X
HX)
-1X
H.
(ii)波束方向跟踪。在第k个探测通信周期的探测时段，接收机接收3个导频，所采用的3个探测波束成形矢量如下所示：
其中
是动态I型时天线数目趋于无穷时渐近最优的探测方向偏移，由图6和表2给出:
表2 动态I型渐近最优的探测方向偏移
方向参数矢量估测
由随机牛顿法更新：
其中
是跟踪步长。Fisher信息矩阵
的第p行，第s列(p＝1,2；s＝1,2)的元素由下式给出
其中
设置***参数为：天线数目M＝N＝8，天线间距
粗波束扫描的码本尺寸M
0＝2M,N
0＝2N,导频符号s
p＝1，发射信噪比
波束方向服从均匀分布：
φ∈(-π,π]。进行1000次***仿真后取平均得到的结果如图7所示，可以看出，所提出的跟踪方法能够渐近到达方向参数矢量均方误差的最小CRLB,跟踪精度远高于已有算法。
3)动态II型
该场景下，信道系数和波束方向都变化很快，此时观测矢量y
k的条件概率密度函数为
用
表示一种信道系数和波束方向的跟踪策略，本发明考虑特定的因果跟踪策略集合Ξ
DII：第k个探测通信周期的探测波束成形矩阵W
k和***估计
均由以前使用的探测波束成形矩阵W
1,W
2,…W
k-1和历史观测y
1,y
2,…y
k决定。因此，在第k个探测通信周期，信道系数和波束方向的跟踪问题可以公式化为：
其中约束(29)确保
是信道矢量
的无偏估计，约束(30)确保每个探测通信周期的探测方向为上一次估测的方向加上三组固定偏移量。
针对动态II型，本实施例设计一种两阶段的跟踪方案：波束和信道联合跟踪(Joint Beam and Channel Tracking，JBCT)，具体如下：
(i)粗波束扫描。如图2所示，接收机在1个探测通信周期内接收M×N个导频，对应于观测
的探测波束成形矢量为
信道系数和波束方向的初始估计如下所示：
其中
采用的码本尺寸为M
0×N
0(M
0≥M,N
0≥N),
X
+＝(X
HX)
-1X
H.
(ii)信道系数和波束方向联合跟踪。在第k个探测通信周期的探测阶段，接收机接收3个导频，所采用的3个探测波束成形矢量如下所示：
其中
由图3和表1给出。信道参数矢量估测
由随机牛顿法更新：
其中
b
DII,k＝0.7是跟踪步长。Fisher信息矩阵
定义如下
设置***参数为：天线数目M＝N＝8，天线间距
粗波束扫描的码本尺寸M
0＝2M,N
0＝2N,导频符号s
p＝1，发射信噪比
到达的波束方向服从随机游走：θ
k＝θ
k-1+Δ
θ,φ
k＝φ
k-1+Δ
φ；Δ
θ,
初始波束方向服从均匀分布：
φ
0∈(-π,π]，信道系数服从高斯-马尔可夫分布：β
k＝ρβ
k-1+μ
k；ρ＝0.995,
初始信道系数β
0服从莱斯分布，莱斯因子为15dB。进行1000次***仿真后取平均得到的结果如图8所示，可以看出，所提出的跟踪方法能够实现更高的跟踪精度。如果设置一个可容忍的跟踪误差，如e
t＝0.15，则所提出的方法能实现更快的跟踪速度。
Claims (10)
- 一种基于二维相控天线阵列的快速精确波束跟踪方法，适用于毫米波移动通信，其特征在于，周期式交替地工作在探测和通信模式，在一个探测通信周期内的探测时段，波束依次指向若干个探测方向，通信时段波束指向当时估计出的波束方向。
- 根据权利要求1所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，包括如下步骤：步骤A,根据信道的时变特性，将信道划分为三种类型：1)准静态场景；2)动态I型；3)动态II型，首先确定待跟踪的信道属于哪种类型；步骤B,在每个探测通信周期的探测时段，基于步骤A中确定的信道类型，依照对应类型的波束跟踪方法，确定依次探测的方向，根据探测结果及历史上记录的信息，获得信道系数和波束方向的估值；步骤C,将波束指向步骤B中获得的波束方向估值进行通信。
- 根据权利要求2所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述步骤A中，准静态场景是指信道系数和波束方向都变化很慢的情况：β k≈β k-1,x k≈x k-1，其中β k指第k个探测通信周期的信道系数，x k指第k个探测通信周期的方向参数矢量：x k,1,x k,2分别为二维方向参数矢量x k两个维度的值，θ k，φ k分别指第k个探测通信周期到达波束方向的俯仰角和方位角，M,N分别为二维面阵天线两个方向维度上的天线数目，d 1,d 2分别为面阵天线两个方向维度上的相邻天线间距，λ为毫米波波长；
动态I型是指信道系数快速变化，波束方向变化很慢的情况：β k≠β k-1,x k≈x k-1；动态II型是指信道系数和波束方向都快速变化的情况：β k≠β k-1,x k≠x k-1。 - 根据权利要求2所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述步骤B中，针对准静态场景的跟踪步骤如下：步骤11，获得在真实波束主瓣范围的初始方向估计以及信道系数的初始估计；步骤12，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测，探测的方向为上一次估测的方向加上三组固定偏移量Δ S,1,Δ S,2,Δ S,3；步骤13，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值；针对动态I型，只跟踪波束方向，跟踪步骤如下：步骤21，获得在真实波束主瓣范围的初始方向估计；步骤22，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测，探测的方向为上一次估测的方向加上三组固定偏移量Δ DI,1,Δ DI,2,Δ DI,3；步骤23，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值；针对动态II型的跟踪步骤如下：步骤31，获得在真实波束主瓣范围的初始方向估计以及信道系数的初始估计；步骤32，在每个探测通信周期的探测时段，依次发送3个导频，进行3次不同方向的探测，探测的方向为上一次估测的方向加上三组固定偏移量Δ DII,1,Δ DII,2,Δ DII,3；步骤33，基于探测结果及历史上记录的信息，利用随机迭代法更新估测值。
- 根据权利要求4所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述步骤11中，采用的初始估测方法为波束扫描：在1个探测通信周期内，发送M×N个导频，利用这些导频，进行M×N个不同方向的探测，根据正交匹配跟踪(Orthogonal Matching Pursuit，OMP)算法，获得信道系数和波束方向的初始估计；所述步骤12中，三组固定的探测偏移量位于二维平面的一个环上0.4≤|Δ S,i|≤0.6,i＝1,2,3；所述步骤13中，采用的随机迭代法为随机牛顿法。
- 根据权利要求5所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述位于环上的三组固定探测偏移量依据要跟踪的目标进行优化，优化目标为信道矢量的均方误差、方向参数矢量的均方误差。
- 根据权利要求4所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述步骤21中，采用的初始估测方法为波束扫描:在前L个探测通信周期内，每个探测通信周期发送M×N个导频，利用这些导频，每个探测通信周期进行M×N个不同方向的探测，L的选取要保证在第L个探测通信周期接收到的M×N个不同探测方向的最大信号能量大于某个阈值，然后利用第L个探测通信周期的探测结果，根据OMP算法获得波束方向的初始估计；所述步骤22中，三组固定的探测偏移量位于二维平面的一个环上0.5≤|Δ DI,i|≤0.7,i＝1,2,3，所述步骤23中，采用的随机迭代法为随机牛顿法。
- 根据权利要求7所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述位于环上的三组固定探测偏移量依据要跟踪的目标进行优化，优化目标为方向参数矢量的均方误差。
- 根据权利要求4所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在 于，所述步骤31中，采用的初始估测方法为波束扫描：在1个探测通信周期内，发送M×N个导频，利用这些导频，进行M×N个不同方向的探测。根据OMP算法，获得信道系数和波束方向的初始估计；所述步骤32中，三组固定的探测偏移量位于二维平面的一个环上：0.4≤|Δ DII,i|≤0.6,i＝1,2,3；所述步骤33中，采用的随机迭代法为随机牛顿法。
- 根据权利要求9所述基于二维相控天线阵列的快速精确波束跟踪方法，其特征在于，所述位于环上的三组固定探测偏移量依据要跟踪的目标进行优化，优化目标为信道矢量的均方误差、方向参数矢量的均方误差。
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| CN112738764B (zh) * | 2020-12-28 | 2021-12-24 | 北京邮电大学 | 一种基于车辆运动轨迹认知的宽带毫米波波束追踪方法 |
| CN113794658A (zh) * | 2021-08-06 | 2021-12-14 | 清华大学 | 一种联合时变信道跟踪与移相器网络实时校准方法及装置 |
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