The disclosure relates to wireless communication techniques, and more particularly to radio frequency (RF) chain allocation for massive multiple input and multiple output (MIMO) systems.
For the next generation communication networks, millimeter wave (mmWave) technology is considered one of the promising candidates to address the challenge of bandwidth shortage. Massive multiple-input multiple-output (MIMO) also evolves with mmWave communications and leads to the development of hybrid beamforming (HB), where analog processing of RF signals, referred to as analog beamforming, is combined with digital processing, referred to as digital beamforming, in the baseband to improve the performance with a limited number of RF chains.
Regarding notation in the detailed description, real part and imaginary part of a complex scalar a are denoted by Re{a} and Im{a} respectively. For a matrix A, Tr(A), AT and AH denote the trace, transpose and Hermitian operations respectively. The notation ∥·∥F denotes the Frobenius norm, which is defined as ∥A∥F=√{square root over (Tr(AAH))}. Notation As−1 and ∥A∥ are the inverse and determinant of a square matrix As respectively. Notation In denotes the identity matrix of dimension n. A diagonal matrix is denoted diag{ . . . } whose kth parameter is the kth diagonal term in the matrix. Notation E[·] denotes the expectation operator.
The method for RF chain allocation is utilized in a massive multiple-input multiple-output (MIMO) system. Specifically, a hybrid beamforming (HB) system in which the overall beamformer consists of a low-dimensional digital beamformer followed by an analog beamformer utilized the method to allocate RF chains to data streams. Due to power and complexity consideration, analog beamforming, also referred to as analog precoding, is typically implemented using phase shifters and the elements of a analog precoder have the constraint of constant magnitude. The method of the disclosure may be applied to downlink multiuser MIMO (MU-MIMO) transmission using HB, or point-to-point (P2P) MIMO communication.
With reference to
The processor 101 transmits downlink signals to a user equipment (UE) device and receives uplink signals from the UE device via the transceiver 103. The transceiver 103 receives and transmits data under the control of the processor 101. Embodiments of the processor 101 may include one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), central processing units (CPUs), controllers, microcontrollers, microprocessors, graphics processing units (GPUs), and others.
The method of the disclosure may be implemented by computer program stored in storage media, such mass storage in the base station 100. When the computer program implementing the method is loaded to a memory 102 by a processor 101, the processor 101 in the device 100 executes the disclosed method.
Embodiments of UE device may include a personal digital assistant (PDA), a cellular phone, a personal communication service (PCS) phone, a global system for mobile (GSM) phone, a wideband code division multiple access (WCDMA) phone, an LTE phone, a NR phone, a Mobile broadband system (MBS) phone, a hand-held PC, a laptop PC, a smart phone, a multi mode-multi band (MM-MB) terminal, etc.
The transceiver 103 is a multiple-input and multiple-output (MIMO) antenna array system. In
A user equipment (UE) device 301 has a single antenna. A UE device has multiple antennas may be treated as multiple virtual UE device each having a single antenna and sharing channel information with one another. Allocating the RF chains to UE devices or, more generally, the signal space dimensions of the UE devices, and the related precoder designs are critical to the system performance.
In communication with the UE devices 301, the processor 101 receives UE identity, such as international mobile equipment identity (IMEI), of each of the UE device 301 from a core network such as the core network 151 in the wireless communication network 150. The processor 101 further receives service requirements associated with each of user equipment identities associated with the UE devices 301. The processor 101 may further receive signal requirements associated with each of user equipment identities associated with the UE devices 301. Each of the user equipment identities is associated with a subscriber identity, such as international mobile subscriber identity (IMSI), representing a user of a UE device 301.
A MIMO antenna array system executing the RF chain allocation method is given in the following. Consider a multiuser downlink scenario with K′ UE devices. The base station 100 is equipped with N antennas and NtRF transmit RF chains serving K′ UE devices each equipped with M antennas and NrRF chains. There are a total of K data streams to be transmitted by the base station 100 and each UE device demands d data streams. Thus, the total number of data streams served by the base station 100 is K=K′d. For simplicity, it is assumed that M=NrRF=d=1 and K′=K. Because the number of transmit RF chains is limited, the HB architecture is applied at the base station 100. Following the convention in the HB literature, beamforming at the base station 100 is performed by precoders. A case with NtRF=K is shown in the following.
P=diag{p1,p2, . . . ,pK} (1)
where p1,p2, . . . , pK are the power allocated to the 1st, 2nd, . . . , K-th data streams, respectively. The overall digital precoder can be represented as:
V
D
=
P
1/2 (2)
where is the normalized digital precoder matrix (with the norm of each column being one).
The digitally precoded signals output by the digital precoder stage 110 are up-converted to the carrier frequency by the NtRF RF chains 121 in stage 120. Then the BS 110 applies the N×NtRF analog precoders, represented by matrix VRF, which is implemented by phase shifters 131 in the stage 130. The absolute value of each element of VRF is one. The transmitted signal x output by the analog precoder stage 130 can be represented as:
where VD=[v1(D), v2(D), . . . , vK(D)], s∈K×1 is the vector of data symbols for all UE devices, s=[s1,s2, . . . ,sK]T, and x∈CN×1 is the vector of transmitted signal. In
where the first term denote the desired signal, the second term is the inter-user interference, and nk represents the zero-mean additive Gaussian noise (AWGN) with variance N0. Different metrics may be used to evaluate the performance of a HB system. For example, a sum rate can be expressed as:
where signal-to-interference-plus-noise (SINR) of k-th UE device may be represented
In the following, maximizing sum rate is taken as an example of the signal requirements. Similar procedures can be applied if other performance metrics are considered. The optimal analog and digital precoders to maximize the sum rate under the total power constraint should satisfy:
where P is the total power constraint at the BS 100.
In general, no closed form solution may be obtained for the optimal hybrid precoders. The following steps are to approximate the optimal solution.
Step 1: Design the analog precoders assuming that the digital precoder stage 110 is doing nothing, i.e., digital precoder input equals digital precoder output, with equal power allocation, that is,
Find the optimal analog precoders.
Step 2: Design the digital precoder in the stage 110 for the effective channel formed by combing the effects of the downlink channel and the analog precoders found in Step 1.
Mathematical description of the precoder design problem is described in the following. In analog precoder design (Step 1), provided
in digital precoders in stage 110. Thus the system model can be shown as
where VRF=[v1(RF), v2(RF), . . . , vK(RF)] and the matrix vi(RF) represents the analog precoder for i-th data stream and i-th UE device.
Since difficult may be to find the optimal analog precoder in the original downlink system, uplink-downlink duality is often applied and help to solve transmit beamforming/precoding.
where qi is the power for UE device i and nUL is the effective noise in the virtual uplink.
From equation (9), the SINR of the k-th data stream received by the k-th UE device is:
The following problem formulation (P1) targets at maximizing the SINR of the k-th data stream received by the k-th UE device.
Problem 1 (P1):
Provided NtRF=K and equal power allocation in the analog precoder stage 130, i.e.,
where P is the total power at the BS 100. With the constant-magnitude constraint of the phase shifters, maximizing the SINR in equation (10) of the k-th data stream received by the k-th UE device over all analog precoders vk(RF) can be formulated as:
Unfortunately, the constant-magnitude constraint of the phase shifters makes the problem non-convex. To provide a near-optimal solution to the P1, the original problem is divided into two sub-problems. The strategy is to relax the constraint of constant-magnitude and try to solve the un-constrained optimization problem first. Then a solution which satisfies the constant-magnitude constraint and can approach the optimal solution can be found. The un-constrained optimization problem is referred to as Problem 1 relax in the following.
Problem 1 Relax (P1 r):
Assume NtRF=K and equal power allocation in analog precoder stage 130, i.e.,
where P is the total power at the BS 100. Maximize the SINK in equation (10) for the k-th data stream received by the k-th UE device over all analog precoders vk(RF).
Here vk(Fully) represents the analog precoders without the constant-magnitude constraint which is equivalent to the fully digital precoder.
After the optimal vk(Fully) are found, the solution vk(RF) that satisfies the constant-magnitude constraint and can approach the optimal solution is obtained by Problem 1 approach as follows.
Problem 1 Approach (P1 a):
Assume NtRF=K. Minimize the difference between the optimal solution found in P1 r for all UE devices and the target analog precoder VRF which satisfies the constant-magnitude constraint.
where VRF={vi(RF)}i=1K, VFully={vi(Fully)}i=1K. Here Euclidean distance is utilized as the performance metric, so the Frobenius norm is used in P1 a.
As to the problem of digital precoder design, due to the constant-magnitude constraint and the finite resolution of phase shifters, the constrained solution found above may not yield the optimal performance. These hardware impairments may be compensated by the baseband digital precoder design. The case of NtRF<K is to be discussed later. ZF approach may fail, and only the approaches that can tolerate interference, such as to maximize the SINR, will work.
Situations of RF chain allocation and related analog precoder design are given in the following. No matter how many data streams there are to be served, the dimension of the signal space of the transmitted signal x is governed by the number of RF chains. Three situations are possible: the number of RF chains is less than the number of data streams, i.e., NtRF<K; the number of RF chains is equal to the number of data streams, i.e., NtRF=K; and the number of RF chains is larger than the number of data streams, i.e., NtRF>K. In the first case, the dimension of the transmitted signal space is not enough to separate the data streams, and there is no way to completely eliminate the interference between the data streams. Therefore, the design target should be to make the analog precoder match the channels between the BS 100 and the UE devices 301 as much as possible, such that the maximum power can be conveyed to the UE devices 301. In the second case, the dimension of the transmitted signal space equals the number of data streams. Ideally, the BS can allocate one RF chain to each data stream and design the precoder such that each UE device can receive its desired data stream with the interference from the other data streams suppressed. However, due to the constant magnitude constraint of phase shifters, the interference suppression cannot be done perfectly. In this case, the analog precoder can be designed to suppress the inter-beam interference and inter-stream interference as much as possible, or maximize the SINR of each data stream as much as possible, depending on the performance metrics used. In the third case, the number of RF chains is larger than the number of data streams. More than one RF chains can be allocated to each data stream to alleviate the effect of the constraint of the phase shifters and approach the optimal performance. Alternatively, more RF chains can be allocated to the dimensions (or directions) of the signal space that experience better channels to enhance the performance. The design issues of these three cases are detailed below.
Analog precoder design when NtRF=K is given in the following.
The GMSINR-FB is used as beamformers and processes the data streams of each UE device as a group. In the particular example, each group has only one data stream. Note that the approach can be easily generalized to the case in which each UE device has multiple data streams. Applying the GMSINR-FB as the analog precoder, the design problem of maximizing the received SINR of each group becomes:
is the covariance matrix of the desired signal in the virtual uplink (as shown in
is the covariance matrix of interference-plus-noise in the virtual uplink for i-th UE device. With the quadratic form in equation (14), the problem is equivalent to the following Lagrange multipliers:
The solution to the Lagrange multipliers is a generalized eigenvalue problem:
R
s,i
UL
v
i
(Fully)
=λv
i
R
n,i
UL
v
i
(Fully), (18)
where eigenvalue λ may be represented as
Consequently, the maximum SINR is the largest eigenvalue obtained from the generalized eigenvalue problem, and the analog precoder for the i-th data stream is the eigenvector corresponding to the largest eigenvalue:
V
i
(Fully)
=eig
1(Rs,iUL,Rn,iUL), (20)
where eig(A,B) is defined as a function that produces the eigenvector x corresponding to the largest eigenvalue λ of the eigenvalue problem Ax=λBx.
An analog precoder with the phase shifter constraint is given in the following. In the above derivation of the analog precoder stage 130 that maximizes the SINR of each data stream, the constant-magnitude constraint of the phase shifters is not considered. In the following, a solution of the analog precoder stage 130 that satisfies the constraint and is “closest” to the un-constrained solution obtained above is described. While “closest” can be defined in many senses, such as with the shortest chordal distance. In the following example, Frobenius norm is used as the metric to define “closest”. That is, “closest” means that the target solution of the analog precoder stage 130 is the one that satisfies the constant-magnitude constraint while its difference from the un-constrained solution obtained above has the smallest Frobenius norm. That is, the target analog precoder VRF must minimize the following:
Since Tr(·) is a linear function, derivation of the equations (21) can be obtained. Observing last line of the equation (21), the first term is constant and the second term depends on the optimal solution. Only the last term depends on the target analog precoder VRF in stage 130. Thus the optimization problem P1 a can be transformed to maximizing the last term in the last line of the equation (21). When VRF has the same phase components as VFully, the last term can be maximized. Thus, the target analog precoder VRF in stage 130 can be obtained as:
V
RF=exp{jarg(VFully)}, (22)
where arg(·) denotes the component-wise argument operator. In the following, the vk(RF) and vk(Fully) is referred to as the analog beamformer and fully digital beamformer, respectively, of the k-th data stream for the k-th UE device.
An analog precoder design when NtRF<K is given in the following.
If no priority ranking of the data streams is determined, the RF chains 121 should be used to serve the signals for all UE devices 301 in the area 300 as much as possible. That is, the BS 100 is to support as much as possible the signal space spanned by the data streams of the UE devices 301. Note that in this case, the interference between the data streams may be suppressed by the baseband digital precoder. The un-constrained analog precoder VFully, which has NtRF columns, should satisfy:
is the covariance matrix of the vector space spanned by the data streams of the UE devices 301. The solution of the equation (23) consists of the eigenvectors corresponding to the largest NtRF eigenvalues of RULs that is,
V
Fully=[v1f(Fully),v2(Fully), . . . ,vN
where eign(A) is defined as a function that produces the eigenvectors x corresponding to the largest n eigenvalues λ of the eigenvalue problem Ax=λx. The analog precoder satisfying the constant-magnitude constraint may be found using equation (22).
An analog precoder design when NtRF>K is given in the following. When NtRF>K, a subset of the RF chains 121 includes NtRF−K RF chains. The processor 101 may initially not yet allocate NtRF−K RF chains to serve data streams. Each of the NtRF−K RF chains is referred to as an extra RF chain. An RF chain allocation method using extra RF chains, i.e., analog beams, is provided to enhance the system performance of the BS 100. In the following, two design approaches are proposed.
Beam decomposition is detailed in the following.
In the following, a 1st data stream for the 1st UE device 301 is assumed to have the highest priority. Analog precoders serving other data streams that satisfy the constant-magnitude constraint are obtained by equations (20) and (22). Two RF chains are allocated to the 1st data stream, with the corresponding constant-magnitude analog precoders obtained by the following decomposition. The analog beams formed by these two analog precoders allocated to the 1st data stream is to be combined by the digital precoder in stage 110 to enhance the performance of data stream 1.
A beam decomposition approach for the RF chain allocation and beamforming is detailed in the following. A complex number can be decomposed into the sum of two numbers with constant magnitude. For example, a complex number c=rejα with 0≤r≤2 can be expressed as c=ejθ+ejφ, where:
This rejα=ejφ can be verified as follows:
In other words, with proper normalization, it is possible to use two phase shifters to represent any complex coefficient in a fully digital beam. Thus, a fully digital beamformer obtained by equation (20) can be decomposed into a sum of two analog beamformers satisfying the constant-magnitude constraint to avoid the performance loss due to the constraint. For example, the fully digital beamformer for i—the UE device can be decomposed as follows:
that is,
v
i
(Fully)
=v
i1
(RF)
+v
i2
(RF) (29)
where vi(Fully) is the fully digital beamformer for i-th UE device obtained by equation (20) and vi1(RF) and Vi2(RF) are the two analog beams decomposed from the fully digital beam. Variables i1 and i2 are the indices of the RF chains which support these two analog beams.
Based on the concept of decomposition, when NtRF>K, the extra RF chains may be allocated to the data streams according to priority ranking. For example, if the goal is to maximize the sum rate of the BS 100, the SINRk(RF) for the k-the data stream, where k=1, . . . , K, are calculated after the K analog precoders satisfying the constant-magnitude constraint are found according to equation (22). Then the SINRk(RF) are ranked from high to low. The extra RF chains are allocated to the data streams according to the ranked SINRk(RF). That is, after allocating one RF chain to each data stream, if still one or more extra RF chains have not been allocated, one of the extra RF chains is allocated to the data stream with the highest SINRk(RF) among the data streams that are allocated only one RF chain. Similarly, another extra RF chain is allocated to the data stream with the second highest SINRk(RF). This procedure is continued until all RF chains are allocated.
An orthogonal space approach for the RF chain allocation and beamforming is detailed in the following.
Then, depending on the priority ranking, the extra RF chains can be allocated to form beams 201 pointing to the directions of vk(Oth)'s (subject to the constant magnitude constraint by using equation (22)).
Alternatively, the NtRF−K extra RF chains can be used to form beams 201 pointing to the NtRF−K most significant dimensions (directions) of the orthogonal space of VRF which may be represented as:
V
Oth=[v′1(Oth)v′2(Oth)L v′K(Oth)] (31)
where
v′
k
(Oth)
=v
k
(Fully)
−V
RF(VRFHVRF)−1VRFHvk(Fully), . . . ,∀k. (25)
The NtRF−K most significant dimensions of VOth may be found by:
[vK+1vK+2L vN
The corresponding constant-magnitude analog beams are then given by:
v
K+j
(RF)=exp{j arg(vK+j)}, for j=1,2,L,NtRF−K (34)
The processor 100 utilizes the constant-magnitude analog beams to drive the transceiver 103 for beamforming.
With reference to
The MIMO antenna array system of the BS 100 receives input signals and performs beamforming processing on the input signals. The processor 101 obtains a total number of RF chains 121 in the MIMO antenna array system of transceiver 103. The processor 101 obtains a total number of the data streams S1, S2, . . . SK in the input signals for the UE identities. The processor 101 may receive system requirements, such as service requirements and signal requirements, associated with data streams S1, S2, . . . SK for a plurality of user equipment identities (block 700). The processor 101 obtains channel information H associated with the BS 100 (block 702). The processor 101 calculates fully digital beams in stage 110 for the data streams S1, S2, . . . SK such as using ZF or GMSINR (block 704), and calculates expected SINR for each beam output by the transceiver 103 (block 706). The processor 101 determines whether the BS 100 receives signal requirements associated with data streams S1, S2, . . . SK for a plurality of user equipment identities (block 708). When the BS 100 does not receive the signal requirements, the processor 101 may prioritize the data streams S1, S2, . . . SK and select a sub-group of the data streams from the data streams S1, S2, . . . SK according to the service requirements (block 710). When the BS 100 receives the signal requirements, the processor 101 may prioritize the data streams S1, S2, . . . SK and select a sub-group of the data streams from the data streams S1, S2, . . . SK according to the service requirements and the signal requirements (block 712). The processor 101 performs the RF chain allocation method (block 714).
In the block 714, the processor 101 allocates each of the RF chains 121 to a selected sub-group of the data streams S1, S2, . . . SK for beamforming processing to achieve a first injective and surjective allocation relationship between the RF chains 121 and the data streams S1, S2, . . . SK when the number of the RF chains 121 is less than or equal to the total number of the data streams S1, S2, . . . SK. The selected sub-group of the data streams includes a subset of the data streams S1, S2, . . . SK which is selected from the data streams S1, S2, . . . SK according to priority between the data streams S1, S2, . . . SK. The processor 101 determines the priority between the data streams Si, S2, . . . SK is based on at least one requirement of the service requirements and the signal requirements. The signal requirements are measured based on group signal to interference plus noise ratio (SINR) associated with the data streams. The RF chain allocation method has two cases depending on whether the decomposition design or the orthogonal space design is used.
With reference to
When the transceiver 103 has one or more extra RF chains not yet allocated after the processing of the block 714, the processor 101 allocates each of the extra RF chains to one data stream according to the priority obtained until no more extra RF chain remained.
The processor 101 determines whether to use a decomposition approach or an orthogonal approach (block 804). When using the orthogonal approach, the processor 1 determines whether the RF allocation in the BS 100 satisfies the service requirements (block 806)? If the RF allocation in the BS 100 satisfies the service requirements, the processor 101 obtains beam parameters of analog precoders (beamformers) for the allocated RF chains by taking the phases of the fully digital beams output by the digital precoder stage 110 (block 810). The processor 101 drives the phase shifters 131 in the stage 130 to perform analog precoding based on the obtained beam parameters (block 830).
If the RF allocation in the BS 100 does not satisfies the service requirements, the processor 101 obtains signal space formed by channels of all data streams (block 812) and calculates orthogonal space of the obtained signal space (block 814). The processor obtains and sorts eigenvectors of the orthogonal space according to corresponding eigenvalues associated with the eigenvectors, from the largest to the smallest (block 816).
The SINRs of all data streams are computed. The processor 101 obtains a joint performance measurement from weighted SINRs and the service requirements of the data streams. The processor 101 repeats the same procedure each time using one of the eigenvectors not yet assigned with an RF chain. The processor 101 selects an eigenvector which results in the largest increase of the joint performance measurement to be assigned with an extra RF chain. The processor 101 extracts the phase of the selected eigenvector as beam parameters of analog precoder in stage 130 for the assigned extra RF chain, with the amplitudes of the analog precoders kept constant, and updates the analog precoder in stage 130 for the assigned extra RF chain (block 818). With reference to
It is also possible to decompose the selected eigenvector into two constant-amplitude analog precoders using the decomposition method. The processor 101 may allocate the decomposed constant-amplitude analog precoders to two extra RF chains, and utilize beam parameters of the decomposed constant-amplitude analog precoders to update the decomposed constant-amplitude analog precoders.
The processor 101 determines whether any extra RF chain remains (block 820). If no not yet allocated extra RF chain remains, the processor executes block 830. If at least one extra RF chain remains, the processor executes block 806 and computes a orthogonal signal space which is orthogonal to the signal space spanned by the beams of the RF chains already assigned. Bocks 806-820 are executed repeatedly until no extra RF chain remains not yet allocated.
When using the decomposition approach, the processor 1 determines whether the RF allocation in the BS 100 satisfies the service requirements (block 808)? If the RF allocation in the BS 100 satisfies the service requirements, the processor 101 obtains beam parameters of analog precoders (beamformers) for the allocated RF chains by taking the phases of the fully digital beams output by the digital precoder stage 110 (block 810).
In block 714, the processor 101 may allocate a first subset of the RF chains 121 to the data streams S1, S2, . . . SK for beamforming processing to achieve a second injective and surjective allocation relationship between the RF chains 121 and the data streams S1, S2, . . . SK when the number of the RF chains 121 is greater than the total number K of the data streams S1, S2, . . . SK. After each data stream has been allocated one RF chain, if still one or more RF chains remain not yet allocated, the processor 101 may allocate one of the extra RF chain to one data stream according to the priority obtained. The processor 101 selects and allocates an RF chain in the first subset of the RF chains 121 and an extra RF chain in a second subset of the RF chains 121 to one selected data stream in the data streams 51, S2, SK (block 822).
The processor 101 utilizes a first analog precoder associated with the selected RF chain in the first subset and a second analog precoder associated with the extra RF chain in the second subset to perform beam decomposition.
With reference to
For a data stream allocated with two RF chains, the processor 101 obtains beam parameters of the analog precoders for the two RF chains by first computing the fully digital beamformer for the data stream, then decompose the fully digital beamformer into two constant amplitude beams (block 824). For a data stream allocated with only one RF chain, the processor 101 obtains the analog precoder of the data stream by taking the phases of the fully digital beamformer for the data stream, with the amplitudes kept constant (block 826).
With reference to
The processor 101 allocates the K-th analog precoder associated with the selected RF chain in the first subset 123 and the (K+1)-th analog precoder associated with the extra RF chain in the second subset 124 to form beams.
The processor 101 determines whether any extra RF chain remains (block 828). If no unassigned extra RF chain remains, the processor executes block 830. If at least one extra RF chain remains, the processor repeats Bocks 808-828 until no extra RF chain remains unassigned.
The RF allocation method is utilized in a massive multiple-input multiple-output (MIMO) system. Specifically, a hybrid beamforming (HB) system in which the overall beamformer consists of a low-dimensional digital beamformer followed by an analog beamformer utilized the method to allocate RF chains to data streams and perform beamforming processing. The total number of RF chains is not necessarily equal to the number of data streams to users. An extra RF chain may be allocated to a data stream using an orthogonal space approach or a beam decomposition approach.
It is to be understood, however, that even though numerous characteristics and advantages of the disclosure have been set forth in the foregoing description, together with details of the structure and function of the present disclosure, the disclosure is illustrative only, and changes may be made in detail, especially in matters of shape, size, and arrangement of parts within the principles of the present disclosure to the full extent indicated by the broad general meaning of the terms in which the appended claims are expressed.
This application claims the benefit of U.S. Provisional Application No. 62/630,467 filed on Feb. 14, 2018, and entitled “RF Chain Allocation and Related Processing for Massive MIMO Systems”, which is incorporated herein by reference in its entirety.
Number | Date | Country | |
---|---|---|---|
62630467 | Feb 2018 | US |