Patent ID: 12191948

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The same or similar reference numbers throughout denote the same or similar elements or elements having the same or similar function. The embodiments described below by reference to the accompanying drawings are exemplary, are intended only for the objective of explaining the present invention and are not to be construed as a limitation of the present invention.

Those skilled in the art may understand that the singular forms “a,” “an,” “the” and “the” used herein may also include the plural forms unless specifically stated. It is further understood that a term “comprising” as used in the specification of the present invention refers to the presence of such features, integers, steps, operations, elements and/or assemblies, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof. It should be understood that when an element is “connected” or “coupled” to another element, the element may be directly connected or coupled to other elements, or an intermediate element can be provided. In addition, “connecting” or “coupling” as used herein may include wireless connection or coupling. A term “and/or” as used herein includes any unit and all combinations of one or more associated listings.

Those skilled in the art may understand that unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by the person skilled in the art to which the present invention belongs. It should also be understood that terms such as those defined in the general dictionary are to be understood as having a meaning consistent with that in the context of the prior art and are not to be interpreted in an idealized or overly formal sense unless defined in a manner as is the case here.

In order to facilitate the understanding of the embodiments of the present invention, the following will be combined with the accompanying drawings to take a plurality of specific embodiments by way of examples to make further explanations, and each embodiment does not constitute a limitation of the embodiments of the present invention.

Embodiment 1

An implementation schematic diagram of a method for realizing rate-splitting multi-access in a mobile cell-free massive MIMO system provided by an embodiment of the present invention is shown inFIG.1. A specific processing flowchart is shown inFIG.2, and includes the following processing steps:

Step S1: splitting, by an access point, the data of each user into two parts with a common message and a private message, coding all the common message into one super common message stream, coding each piece of the private message into a private message stream, and superimposing and sending out the super common message stream on the private message stream.

Step S2: determining, by each of the access points, a power splitting ratio between the common message and the private message based on a large-scale channel state information.

Step S3: using, by the private message stream, an arbitrary linear pre-coding method, and solving a problem of maximizing the minimum common message rate of the user using bisection-based iterative optimization to obtain an optimal pre-coding method for a super common message stream.

Step S4: sending, by the access point, the final coded super common message stream to user terminals after superimposing the final coded super common message stream on the private message stream.

Step S5: first decoding, by each of the user terminals, the super common message stream, removing the super common message stream using successive interference cancellation technology, and then decoding the private message stream.

Specifically, the forgoing step S1includes: taking as an example one cell-free massive MIMO system including L access points and K users, using, by the system, coherent transmission, and moving, by different users, at different speeds. The message sent by each of the access points to the user is Wk, k=1, . . . , K. Each of the access points then splits user message Wkinto the common message Wc,kand the private message Wp,k.

All the common message is coded into one super common message stream. Each piece of the private message is coded into the private message stream. All the common message Wc,1, . . . , Wc,kof all the users are combined into one super common message Wc, and then the super common message Wcis coded into the super common message stream scusing a common codebook. The private message Wp,1, . . . , Wp,Kof each of the users are coded into the private message streams s1, . . . sK, respectively.

Specifically, the forgoing step S2includes: determining, by each of the access points, a power splitting ratio of the common message and the private message based on the large-scale channel state information, mainly including, by the large-scale channel state information, path loss and shadow fading, and describing the change of a channel over a long period of time and being easily accessible.

The service capability of each of the access points is measured based on a large-scale channel fading message of the system. The access point with strong service capability distributes more power to the common message. Conversely, the access point with weak service capability distributes less power to the common message.

The power splitting ratio of the common message of each of the access points is calculated using the following equation:
tl=t+Δl

Δl=ω⁢βl-(∑l=1L⁢βl)/Lmax⁢{❘"\[LeftBracketingBar]"βl-(∑l=1L⁢βl)/L❘"\[RightBracketingBar]"}βl=((∑k=1K⁢βk⁢l)/K)α
ω=min{t−0,1−t}/εwhere t is an initial power splitting ratio of each of the access points, Δlis a power splitting ratio adjustment factor of each of the access points, βklis a large-scale fading coefficient between a k-th user and a l-th access point, βlis an average channel quality coefficient from the l-th access point to all the users, α is a scaling factor of average channel quality, ω is an adjustment range of a power splitting ratio, ε is a scaling factor of the adjustment range, and tlis a final power splitting ratio of the common message and the private message of the access point.

Based on the forgoing power distribution principle, the power splitting ratio factor of each of the access points is adjusted based on an equal power splitting ratio solution tl= . . . =tL=t.

Therefore, during subsequent processing, the power splitting ratios of the common message and the private message are different for each of the access points. A final power splitting ratio tlused is effective in suppressing interference and fully utilizes the usage effectiveness of an access point power.

Specifically, the forgoing step S3includes: using, by the private message stream, the arbitrary linear pre-coding method. A normalized pre-coding vector vc,klnormof the private message stream can directly use various linear pre-coding solutions obtained in conventional cell-free massive MIMO, which include maximum ratio transmission pre-coding, local minimum mean-square error pre-coding, and centralized minimum mean-square error pre-coding.

The normalized pre-coding vector vil,nnormof the private message stream can directly use various linear pre-coding solutions obtained in the conventional cell-free massive MIMO.

Normalized maximum ratio transmission pre-coding is calculated as:

vkl,nnorm=hˆkl,n/E⁢{hˆkl,n2}where ĥkl,nis an estimated channel state information from the k-th user to the l-th access point at a n-th time slot.

Normalized local minimum mean-square error pre-coding is calculated as:

vk⁢l,nnorm=vk⁢l,n/E⁢{vkl,n2}where vkl,nis minimum mean-square error pre-coding designed for the k-th user by the l-th access point at the n-th time slot based on local channel state information, and calculated as:

vkl,n=pd(1-tl)K⁢(∑i=1Kpd(1-tl)K⁢(hˆil,n⁢hˆil,nH,+Cil,n)+σ2⁢IN)-1⁢hˆkl,nwhere pdis a maximum downlink transmission power per the access point, Cil,nis a variance of the channel estimated error from the i-th user to the l-th access point at the n-th time slot, and σ2is a noise power of a receiver.

Normalized centralized minimum mean-square error pre-coding is calculated as:

vkl,nnorm=vkl,n/maxl=1,…,L{E⁢{vkl,n2}}where vkl,nis minimum mean-square error pre-coding designed for the k-th user by the l-th access point at the n-th time slot based on global channel state information, and calculated as:

vkl,n=11-tl⁢v¯kl,n[v¯k⁢1⁢nT,…,v¯kL,nT]T=v¯k,n=pdK⁢(∑i=1KpdK⁢(hˆi,n⁢hˆi,nH+Ci,n)+σ2⁢IL⁢N)-1⁢hˆk,nwhere ĥi,nis an estimated channel state information vector consisting of the i-th user to all the access points at the n-th time slot, Ci,nis a variance of an estimated error of the channel vector, andvk,nis a minimum mean-square error pre-coding vector designed for the k-th user by a central processing unit at the n-th time slot based on the global channel state information.

The difference between local pre-coding and centralized pre-coding is that the local pre-coding can only use a local estimated channel state information, whereas the centralized pre-coding can use an estimated channel state information for the entire system.

A problem of maximizing the minimum common message rate of the user is solved using bisection-based iterative optimization to obtain an optimal pre-coding method for a super common message stream. The following problem of maximizing the minimum common message rate is constructed based on power consumption limitation of each of the access points:

max{vc,l,nnorm}mink=1,…,KRk,nc⁢(vc,l,nnorm)s.t.vc,l,nnorm2≤1,∀lwhere Rk,ncis a rate at which the k-th user decodes the received common message at the n-th time slot, and is a function of normalized common message pre-coding vc,l,nnorm.

The forgoing equation is equivalent to:

max{v_c,n}mink=1,…,Kpd⁢❘"\[LeftBracketingBar]"h^k,nH⁢v_c,n❘"\[RightBracketingBar]"2pd(v_c,n)H⁢Ck,n⁢v_c,n+κk,ns.t.vc,l,nnorm2,,1,∀l

Wherevc,nis the common message pre-coding vector consisting of all the access points at the n-th time slot.

In addition, κk,nis a function of the private message pre-coding vector, independent of an optimization variablevc,n, and calculated as:

κk,n=pdK⁢∑i=1K❘"\[LeftBracketingBar]"h^k,nH⁢v_i,n❘"\[RightBracketingBar]"2+pdK⁢∑i=1Kv_i,nH⁢Ck,n⁢v_i,n+σ2where {circumflex over (v)}i,nis the private message pre-coding vector designed for all the access points by the i-th user at the n-th time slot.

The forgoing problem is solved using the bisection-based iterative optimization. This method obtains the optimal common message pre-coding solution by solving a series of convex feasibility problems in each iteration. A specific algorithm flowchart is shown in a table below:

Pre-Coding Algorithm of the Common Message Based on the Bisection-Based Iterative Optimization

1. Initializing Y min and Y max to define a range of values for an objective function and selecting one threshold ε>0 to define a stopping criterion for loop iteration.2. The normalized pre-coding vector of the common message is

vc,l,nnorm=1tl⁢v_c,l,n.3. Performing While γmax−γmin>ε.4. Setting γ=(γmax+γmin)/2 and solving the following convex feasibility problem:

{pd⁢hˆk,nH⁢v¯c,n⁢…⁢γ⁢uk,nv¯c,l,n2≤tl,∀l5. Where uk,nis defined as:

uk,n=[(pd⁢Ck,n12⁢v¯c,n)T,κk,n]T6. Setting γmin□γ if the forgoing problem is feasible, otherwise setting γmax□γ.7. End while

Specifically, the forgoing step S4includes: superimposing and sending out the super common message stream on the private message stream. The access point/uses a normalized vector ∥vc,lnorm∥2≤1 to linearly pre-code the super common message stream and uses the normalized vector ∥vc,klnorm∥2≤1 to linearly pre-code the private message stream. The linearly pre-coded common and private message streams are superimposed together to combine a transmission signal of the l-th access point as:

xl=pd⁢tl⁢vc,lnorm⁢sc+pd(1-tl)K⁢∑i=1Kviln⁢o⁢r⁢m⁢siwhere pdis a maximum downlink transmission power of each of the access points, tlis a transmission power splitting ratio of the super common message stream of the l-th access point, the transmission power splitting ratio of the super common message stream is tl.

Specifically, the forgoing step S5includes: decoding, by the user end, the super common message stream, removing the super common message stream using the successive interference cancellation technology, and then decoding the private message stream, and includes: after receiving a mixed message stream, firstly considering, by the user end, the private message stream as noise, decoding the super common message stream using the common codebook, and removing the signal of the super common message stream by successive interference cancellation technology. Subsequently, the user considers the private message stream of other users as noise and decodes the private message streams directly.

N antennas are deployed at each of the access points, and a single antenna is deployed at each of the users. One resource block containing τ+1 time slots is used, where a channel state information of the 0-th time slot is known. The latter τ time slots are used for data transmission. At the n-th time slot, a channel from the access point l to a mobile user k is modeled as the following Rayleigh fading:
hkl,n˜CN(0,Rkl),n=0,1, . . . ,τwhere Rkl∈CN×Nis a spatial correlation matrix, and βkl=tr(Rkl)/N is the large-scale fading coefficient.

Due to the relative movement between the user and the access point, the estimated channel state information becomes progressively outdated over time. Based on a channel aging model, the channel state information for the data transmission can be modeled by an initial channel state information as follows:
hkl,n=ρk,nhkl,0+ρk,ngkl,n,n=1, . . . ,τ

Where gkl,n˜CN (0, Rkl) is an independent innovation component at the n-th time slot, 0, ρk,n, 1 is a temporal correlation coefficient between the user k's channels at the O-th time slot and the n-th time slot, and

ρ¯k,n=1-ρk,n2
is an error coefficient due to channel aging. Based on Jakes' model, the forgoing can be calculated as:
ρk,n=J0(2πfD,kTsn),∀k,∀nwhere J0(.) is a zeroth-order Bessel function of the first kind. Tsis a sampling interval, and fD,k=(vkfc)/c is Doppler frequency shift. Where vkis the user k's movement speed, fcis a carrier frequency, and c is the speed of light.

Due to the channel aging effect described above, an estimated channel state information and an estimated error of a data transmission part are as follows, respectively:
ĥkl,n=ρk,nhkl,0,n=1, . . . ,τ
{tilde over (h)}kl,n=hkl,n−ĥkl,n=ρk,ngkl,nwhere the distribution of ĥkl,nis CN (0, ρk,n2Rkl), the distribution of {tilde over (h)}kl,nis CN (0, Ckl,n), and a variance of the estimated error is Ckl,n=(1−ρk,n2)Rkl.

The signal rk,nreceived by the k-th user in the n-th time slot is as follows:

rk,n=∑l=1Lhkl,nH⁢xl,n+wk,n=pd⁢∑l=1Lhkl,nH⁢tl⁢vc,l,nnorm⁢sc,n+pdK⁢∑l=1Lhkl,nH⁢1-tl⁢vkl,nnorm⁢sk,n+pdK⁢∑i≠kK∑l=1Lhkl,nH⁢1-tl⁢vil,nnorm⁢si,n+wk,n

The private message stream is considered as noise. The super common message stream in the signal rk,nis decoded using the common codebook. The signal of the super common message stream is removed by the successive interference cancellation technology. Subsequently, the user considers the private message stream of other users as noise and decodes the private message streams directly. The signal interference noise ratios for the common message and the private message at the n-th time slot are calculated as follows, respectively:

SIN⁢Rk,nc=pd⁢❘"\[LeftBracketingBar]"h^k,nH⁢v_c,n❘"\[RightBracketingBar]"2pdK⁢∑i=1K❘"\[LeftBracketingBar]"hˆk,nH⁢v¯i,n❘"\[RightBracketingBar]"2+pd⁢v_c,nH⁢Ck,n⁢v_c,n+pdK⁢∑i=1Kv¯i,nH⁢Ck,n⁢v¯i,n+σ2SIN⁢Rk,np=pdK⁢❘"\[LeftBracketingBar]"hˆk,nH⁢v¯k,n❘"\[RightBracketingBar]"2pdK⁢∑i≠kK❘"\[LeftBracketingBar]"hˆk,nH⁢v¯i,n❘"\[RightBracketingBar]"2+pdK⁢∑i=1Kv¯i,nH⁢Ck,n⁢v¯i,n+σ2
where,
ĥk,n[=ĥkl,nT, . . . ,hkl,nT]T
vc,n=[vc,l,nT, . . . ,vc,L,nT]T,vc,l,n=√{square root over (tl)}vc,l,nnorm
vi,n=[vil,nT, . . . ,vil,nT]T,vil,n=√{square root over (1−tl)}vil,nnorm
Ck,n=diag(Ckl,n, . . . ,Ckl,n)

Thus, the total rate of the system at the n-th time slot can be calculated as:

Sum⁢Rn=E⁢{mink{Rk,nc}}+∑k=1KE⁢{Rk,np}=E⁢{log2(1+mink{SIN⁢Rk,nc})}+∑k=1KE⁢{log2(1+SIN⁢Rk,np)}

Embodiment 2

Regarding Embodiment 2, a method of the present invention is configured to realize rate-splitting multi-access under a mobile cell-free massive MIMO system, and includes the following steps specifically:

Scene parameterization: a square area of 250 m×250 m is provided with 20 access points and 4 users, taking as an example a case of a n=10-th time slot of a channel resource block. Here, a following three-slope propagation model is used:

βk⁢l[dB]={-81.2,dkl<10⁢m-61.2-20⁢log10(dkl1⁢m),10⁢m≤dkl<50⁢m-35.7-35⁢log10(dkl1⁢m)+Fkl,dkl≥50⁢m

Where dklis a horizontal distance from a l-th access point to a k-th user. Shadow fading Fkl□N (0, 82) occurs only when a spacing is greater than 50 m, and the correlation thereof is:

E⁢{Fkl⁢Fi⁢j}=822⁢(2-δki/100⁢m+2-υlj/100⁢m)

Where δkiis a distance from the k-th user to the i-th user, and vljis a distance from the l-th access point to the J-th access point. It is assumed that a communication carrier frequency is fc=2 GHZ. A communication bandwidth is B=20 MHz. A downlink transmission power is pd=23 dBm. A noise power is σ2=−96 dBm. A sampling frequency is 15 kHz, and a sampling interval is Ts=67 μs.

In a simulation test, Monte Carlo method is used to randomly generate 200 independent user distributions. Simulation is performed based on the forgoing parameters and the process in Embodiment 1.

FIG.3is an effect picture of a power splitting ratio based on a large-scale channel state information. Referring toFIG.3, a vertical coordinate indicates the total rate of the system, and a horizontal coordinate indicates a power splitting ratio distributed to a common message. Compared to an equal power splitting ratio for each of the access points in a rate-splitting multi-access assisted cell-free massive MIMO system, in an example of the present invention, the total rate of the system is significantly improved after the power splitting ratio is adjusted using large-scale channel state information.

FIG.4is an effect picture of pre-coding the common message based on bisection-based iterative optimization. Referring toFIG.4, a vertical coordinate represents the total rate of the system, and a horizontal coordinate represents two different movement conditions of a user. The users with different speeds make the effects of interference within the system more dramatic and complex compared to the users with the same speed. Under different mobile environment configurations, compared to random common message pre-coding and superimposed common message pre-coding, a pre-coding method using a bisection-based iterative optimization method consistently has the best total rate performance in an example of the present invention. The performance of low-complexity superimposed common message pre-coding is close to common message pre-coding of the bisection-based iterative optimization for the users with the same speed, but the performance is much worse than common message pre-coding of the bisection-based iterative optimization for the users with different speeds. In the present invention, the robustness of the cell-free massive MIMO system in a complex mobile environment is enhanced.

In summary, an embodiment of the present invention proposes a method for realizing rate-splitting multi-access in a mobile cell-free massive MIMO system. Considering outdated channel state information due to mobility, rate-splitting multi-access technology can effectively enhance the interference management capability of the cell-free massive MIMO system, and can significantly improve the transmission rate performance of the system and the robustness of the system in the complex mobile environment.

A power splitting ratio solution based on large-scale channel state information proposed in the present invention has low computational complexity, high efficiency, and better practical value. Private message pre-coding in the present invention can directly use various linear pre-coding solutions in a conventional cell-free massive MIMO system. The common message pre-coding is designed separately for faster solution.

It will be understood by the person skilled in the art that the accompanying drawings are merely the schematic diagram of one embodiment, and that a module or a process in the accompanying drawings are not necessary to carry out the present invention.

As can be seen from the forgoing description of the embodiments, it is clear to the person skilled in the art that the present invention can be realized with the aid of software plus a necessary common hardware platform. Based on this understanding, the technical solution of the present invention, in essence or as a contribution to the prior art, can be embodied in the form of a software product. The software product of a computer may be stored in a storage medium, such as a ROM/RAM, a disk, a CD-ROM, or the like, and includes a number of instructions to cause one computer apparatus (which can be a personal computer, a server, or a network apparatus, or the like) to carry out the method described in the various embodiments, or in some portions of embodiments, of the present invention.

The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, since a device or system embodiment is basically similar to a method embodiment, the description is relatively simple. For related parts, please refer to the part of the description of the method embodiment. The device and system embodiments described above are merely schematic. In addition, a unit described as a separate component can or can not be physically separated. The component displayed as the unit can or can not be a physical unit, that is, the unit or the component can be located in one place, or can be distributed on a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the objective of the solution of the embodiment. It can be understood and implemented by the person skilled in the art without creative labor.

The forgoing are only preferable specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The person skilled in the art can easily think of. changes or substitutions within the technical scope disclosed by the present invention, which should be covered within the protection scope of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.