阅读说明：本技术 一种基于mumimo的用户配对方法、装置及基站 (User pairing method, device and base station based on MUMIMO ) 是由 张淼 王玉财 于 2020-04-14 设计创作，主要内容包括：本发明实施例公开了一种基于MUMIMO的用户配对方法、装置及基站,该方法包括：接收媒体介入控制MAC层发送的配对用户候选集,所述配对用户候选集中包括多个候选用户；根据本地存储的MUMIMO相关系数记录和SRS信息,确定各个所述候选用户之间的相关系数；其中,所述MUMIMO相关系数记录用于保存已计算过相关系数的各个用户、以及各个用户之间的相关系数；根据所述相关系数计算各个所述候选用户之间的第一配对关系,并将所述第一配对关系反馈给所述MAC层,以使所述MAC层根据所述第一配对关系进行对应的调度资源分配。因此,本发明实施例减少了PL对相关系数计算的重复操作,提升了用户配对成功率和系统吞吐量。(The embodiment of the invention discloses a user pairing method, a device and a base station based on MUMIMO, wherein the method comprises the following steps: receiving a pairing user candidate set sent by a Media Access Control (MAC) layer, wherein the pairing user candidate set comprises a plurality of candidate users; determining a correlation coefficient between each candidate user according to the locally stored MUMIMO correlation coefficient record and SRS information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users; and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation. Therefore, the embodiment of the invention reduces the repeated operation of PL on the calculation of the correlation coefficient, and improves the success rate of user pairing and the system throughput.)

1. A user pairing method based on MUMIMO is characterized by comprising the following steps:

receiving a pairing user candidate set sent by a Media Access Control (MAC) layer, wherein the pairing user candidate set comprises a plurality of candidate users;

determining a correlation coefficient between each candidate user according to a locally stored multi-user multi-input multi-output (MUMIMO) correlation coefficient record and Sounding Reference Symbol (SRS) information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

2. The method of claim 1, wherein the determining the correlation coefficient between the candidate users according to the locally stored multi-user multiple-input multiple-output (MUMIMO) correlation coefficient record and Sounding Reference Symbol (SRS) information comprises:

inquiring a correlation coefficient between a first candidate user and a second candidate user in the MUMIMO correlation coefficient record; wherein the first candidate user and the second candidate user are used to characterize any two users of the respective candidate users;

if the correlation coefficient between the first candidate user and the second candidate user is inquired, acquiring the correlation coefficient between the first candidate user and the second candidate user from the first correlation coefficient record;

if the correlation coefficient between the first candidate user and the second candidate user is not inquired, calculating the correlation coefficient between the first candidate user and the second candidate user according to the SRS information, and storing the correlation coefficient between the first candidate user and the second candidate user into the MUMIMO correlation coefficient record.

3. The MUMIMO-based user pairing method of claim 1, further comprising:

when an SRS signal sent by a reporting user is received during the calculation of the pairing relationship, eliminating the correlation coefficient related to the reporting user in the MUMIMO correlation coefficient record; a starting point in the pairing relationship calculation period is a pairing user candidate set sent by a received MAC layer, and an ending point in the pairing relationship calculation period is the first pairing relationship fed back to the MAC layer;

in an idle period after the pairing relation calculation period, calculating a correlation coefficient between the reporting user and one or more appointed users according to the SRS signal;

and storing the correlation coefficient between the reported user and each appointed user in the MUMIMO correlation coefficient record.

4. The MUMIMO-based user pairing method of claim 3, wherein the idle period comprises a period other than each of the pairing relationship calculation periods within one SRS period.

5. The method of claim 3, wherein the calculating a correlation coefficient between the reporting user and one or more designated users according to the SRS signals comprises:

determining a first number of the designated users for performing correlation coefficient calculation with the reporting user;

for any one appointed user, inquiring the correlation coefficient between the reported user and the appointed user in the MUMIMO correlation coefficient record;

if the correlation coefficient between the reporting user and the designated user is inquired, the correlation coefficient between the reporting user and the designated user is not recalculated;

and if the correlation coefficient between the reported user and the designated user is not inquired, calculating the correlation coefficient between the reported user and the designated user according to the SRS signal.

6. The MUMIMO-based user pairing method of claim 5, wherein the first number corresponds to a capability of a base station-side processor.

7. The MUMIMO-based user pairing method of claim 5, wherein the designated users comprise users who have performed correlation coefficient calculation within a set time and/or online users.

8. An apparatus for user pairing based on MUMIMO, comprising:

the media intervention control system comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a paired user candidate set sent by a media intervention control MAC layer, and the paired user candidate set comprises a plurality of candidate users;

the determining module is used for determining the correlation coefficient among the candidate users according to the locally stored multi-user multi-input multi-output (MUMIMO) correlation coefficient records and Sounding Reference Symbol (SRS) information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and the pairing module is used for calculating a first pairing relationship among the candidate users according to the correlation coefficient and feeding back the first pairing relationship to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relationship.

9. A base station comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the MUMIMO-based user pairing method of any one of claims 1 to 7.

10. A non-transitory computer readable storage medium, having stored thereon a computer program, which, when being executed by a processor, performs the steps of the MUMIMO based user pairing method according to any one of claims 1 to 7.

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a user pairing method and apparatus based on MUMIMO, and a base station.

Background

The mimo (Multi-User Multiple-Input Multiple-Output) refers to that in a wireless communication system, one base station serves Multiple mobile terminals at the same time, and the base stations fully utilize spatial resources of antennas to communicate with Multiple users at the same time.

In an existing LTE (Long Term Evolution) system, a single TTI (Transmission Time-Interval) is 1ms, a Physical Layer (PL) on a base station side acquires a paired User candidate set within 1ms and calculates two correlation coefficients, a pairing relationship that maximizes total spectral efficiency on each resource block is found by greedy calculation, and the pairing relationship is fed back to a Media Access Control (MAC) Layer, when a User Equipment (User terminal) is scheduled by the MAC at one TTI, available frequency domain resources are selected according to whether the UE has a pairing relationship on frequency domain resources and which users have a pairing relationship, and a Signal to Interference plus Noise Ratio (SINR) and a pairing condition are determined. If there is no pairing relationship, resources are directly allocated according to a Single-User Multiple-Input Multiple-Output (SUMIMO) mode, and if too few paired users are generated in a pairing set at a Single time, the pairing success rate and the system throughput are low.

However, in 5G NR (New Radio, New air interface), the single TTI time is shortened to 500us, the total bandwidth is expanded to 100M, the single-user scheduling data amount can reach more than 1.7G, if the paired user candidate set is continuously acquired 1ms in advance, the selected user has a higher probability of completing scheduling within 1ms, and a difference between the currently scheduled user and the paired user candidate set is more likely to occur. Resulting in the next 1ms scheduled user not being in the paired user candidate set without pairing relationships. If the pairing relationship table is still provided to the PL one TTI in advance, the processing time of the PL is limited, and the number of users scheduled by MAC single TTI is increased, the probability that the users to be scheduled appear in the pairing relationship table is also reduced.

Disclosure of Invention

The invention aims to provide a user pairing method, a user pairing device and a base station based on MUMIMO (multiple input multiple output), so as to reduce the PL processing time in 5G NR (noise figure and noise figure) and improve the system throughput.

In a first aspect, an embodiment of the present invention provides a user pairing method based on MUMIMO, including:

receiving a pairing user candidate set sent by a Media Access Control (MAC) layer, wherein the pairing user candidate set comprises a plurality of candidate users;

determining correlation coefficients among the candidate users according to locally stored multi-user multi-input multi-output (MUMIMO) correlation coefficient records and SRS (sounding reference signal) information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

Optionally, the determining the correlation coefficient between the candidate users according to the locally stored MUMIMO correlation coefficient record and SRS information includes:

inquiring a correlation coefficient between a first candidate user and a second candidate user in the MUMIMO correlation coefficient record; wherein the first candidate user and the second candidate user are used to characterize any two users of the respective candidate users;

if the correlation coefficient between the first candidate user and the second candidate user is inquired, acquiring the correlation coefficient between the first candidate user and the second candidate user from the first correlation coefficient record;

if the correlation coefficient between the first candidate user and the second candidate user is not inquired, calculating the correlation coefficient between the first candidate user and the second candidate user according to the SRS information, and storing the correlation coefficient between the first candidate user and the second candidate user into the MUMIMO correlation coefficient record.

Optionally, the method further comprises:

when an SRS signal sent by a reporting user is received during the calculation of the pairing relationship, eliminating the correlation coefficient related to the reporting user in the MUMIMO correlation coefficient record; a starting point in the pairing relationship calculation period is a pairing user candidate set sent by a received MAC layer, and an ending point in the pairing relationship calculation period is the first pairing relationship fed back to the MAC layer;

in an idle period after the pairing relation calculation period, calculating a correlation coefficient between the reporting user and one or more appointed users according to the SRS signal;

and storing the correlation coefficient between the reported user and each appointed user in the MUMIMO correlation coefficient record.

Optionally, the idle period includes a period in one SRS period other than each pairing relationship calculation period.

Optionally, the calculating a correlation coefficient between the reporting user and one or more designated users according to the SRS signal includes:

determining a first number of the designated users for performing correlation coefficient calculation with the reporting user;

for any one appointed user, inquiring the correlation coefficient between the reported user and the appointed user in the MUMIMO correlation coefficient record;

if the correlation coefficient between the reporting user and the designated user is inquired, the correlation coefficient between the reporting user and the designated user is not recalculated;

and if the correlation coefficient between the reported user and the designated user is not inquired, calculating the correlation coefficient between the reported user and the designated user according to the SRS signal.

Optionally, the first number corresponds to a capability of the base station side processor.

Optionally, the specified users include users who have performed correlation coefficient calculation within a set time, and/or online users.

In a second aspect, an embodiment of the present invention provides an apparatus for user pairing based on MUMIMO, including:

the media intervention control system comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a paired user candidate set sent by a media intervention control MAC layer, and the paired user candidate set comprises a plurality of candidate users;

the determining module is used for determining the correlation coefficient among the candidate users according to the locally stored multi-user multi-input multi-output (MUMIMO) correlation coefficient records and SRS (sounding reference signal) information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and the pairing module is used for calculating a first pairing relationship among the candidate users according to the correlation coefficient and feeding back the first pairing relationship to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relationship.

In a third aspect, an embodiment of the present invention provides a base station, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the MUMIMO-based user pairing method in the first aspect when executing the program.

In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the MUMIMO-based user pairing method according to the first aspect.

In the user pairing method, device and base station based on the MUMIMO provided by the embodiment of the invention, after the PL receives the pairing user candidate set sent by the MAC layer, the correlation coefficient between each of the candidate users may be determined based on the locally stored MUMIMO correlation coefficient records and SRS information, and calculating a first pairing relationship between the candidate users according to the correlation coefficient, and feeding back the first pairing relationship to the MAC layer, so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relationship, therefore, the repeated operation of the PL on the calculation of the correlation coefficient is reduced, the calculation complexity in the limited time of the pairing relationship calculation is reduced, the pairing relationship calculation processing capacity in the fixed time is improved, the MAC layer can obtain the pairing relationship table covering more users before scheduling, and the user pairing success rate and the system throughput are improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

FIG. 1 is a diagram illustrating a timing sequence of a pairing relationship calculation in the prior art;

FIG. 2 is a flowchart of a MUMIMO-based user pairing method according to an embodiment of the present invention;

FIG. 3 is a diagram illustrating a timing sequence of pairing relationship calculation according to an embodiment of the present invention;

fig. 4 is a flowchart illustrating an optimization process of a MUMIMO-based user pairing method according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a user pairing apparatus based on MUMIMO according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a base station according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

MUMIMO refers to a wireless communication system in which a base station serves a plurality of mobile terminals at the same time, and the base stations communicate with a plurality of users at the same time by fully utilizing the spatial resources of antennas.

The embodiment of the invention discloses an MUMIMO pairing algorithm optimization scheme for reducing PL processing time and improving system throughput in a 5G system. Compared with the traditional SUMIMO, in the MUMIMO downlink, the base station can serve a plurality of users on a plurality of same time-frequency resources through space division multiple access, and the purposes of improving the total throughput of a cell and the number of the service users are achieved. Considering that certain interference exists among different users, in order to ensure that the system throughput can be maximized in one-time scheduling, the best pairing relation of the users to be scheduled at the current time needs to be obtained through greedy calculation before scheduling. However, the number of terminals supported by a single cell can reach thousands of terminals, correlation calculation between every two users is complex, pairing relation calculation can only be performed on part of users in consideration of hardware processing capacity and single TTI duration, and MAC performs scheduling resource allocation based on the calculation result.

In the existing LTE system, a single TTI is 1ms, a PL (quality indicator) at a base station side acquires a paired user candidate set within 1ms and calculates two correlation coefficients, a pairing relation for maximizing total spectral efficiency on each resource block is found out through greedy calculation, the pairing relation is fed back to an MAC (media access control) layer, and when the MAC schedules UE in one TTI, available frequency domain resources are selected according to whether the UE has the pairing relation on frequency domain resources and which users have the pairing relation, and the spectral efficiency of the users is determined according to user CQI/SINR (channel quality indicator/signal to interference and noise ratio) and pairing conditions. If no pairing relationship directly allocates resources according to the SUMIMO mode, if too few paired users in the pairing set generated in a single time are available, the pairing success rate and the system throughput are both low.

However, in the 5G NR system, the single TTI time is shortened to 500us, the total bandwidth is expanded to 100M, the single-user single-scheduling data volume can reach more than 1.7G, and if the paired user candidate set is continuously acquired 1ms in advance, the selected user has a higher probability of completing scheduling within 1ms, and a difference between the currently scheduled user and the paired user candidate set is more likely to occur. Resulting in the next 1ms scheduled user not being in the paired user candidate set without pairing relationships. If the pairing relationship table is still provided to the PL one TTI in advance, the processing time of the PL is limited, and the number of users scheduled by MAC single TTI is increased, the probability that the users to be scheduled appear in the pairing relationship table is also reduced.

The embodiment of the invention optimizes the situation, still maintains an algorithm for generating the paired user candidate set by 1 TTI in advance in a 5G NR system, reduces the calculation complexity of the paired relationship by optimizing the time point of the PL calculation correlation coefficient, improves the total number of users of the PL calculation paired relationship in a limited time period in a single TTI, ensures that the PL can feed back the paired relationship table covering more users to an MAC layer, and improves the pairing success rate and the system throughput.

For an LTE system, for each TTI, the MAC layer selects N users with higher priority to enter a paired user candidate set according to the processing capacity of the PL, and sends the N users to the PL. The PL acquires the spectrum efficiency of each user on each resource block after acquiring the pairing user candidate set, and selects the user with the highest spectrum efficiency on the resource block as a baseline user, namely, the user is considered to be fixedly capable of participating in pairing on the resource, and the non-baseline user needs to calculate a correlation coefficient with the baseline user to judge whether the user can be paired on the resource block. The determination method comprises the following steps:

and traversing each user flow of the candidate users under each resource block, and computing the correlation coefficient by using the user flow and the user flow on the current resource block pairwise, wherein the computing process is shown as a formula (1).

Wherein, thereinA forming factor of the paired user stream i on the resource block u,is a forming factor, rho, of user flow j on a resource block u in a candidate set_i,jThe correlation coefficients are the user stream i and the user stream j.

According to the correlation coefficient, the total spectrum efficiency of the paired users on the resource block u and the user stream j can be estimated. Where the spectral efficiency of user stream jAs shown in equation (2).

Wherein the content of the first and second substances,the spectrum efficiency of the stream after CQI correction is carried out on the MAC layer, L is the sum of the current paired streams, K is a correction factor, and delta eta_MU,LLIs inter-stream interference.

If the user stream j participates in pairing, the total spectrum efficiency of the current resource block is shown as formula (3).

Wherein J is the total number of paired streams on the current resource block. After traversing all the user streams, selecting a candidate user with the total spectrum efficiency after the user is added greater than the spectrum efficiency when the user is not added and the total spectrum efficiency is the highest, adding the pairing relation, and recording the current total spectrum efficiency. The above processes are cycled for a plurality of times until no unpaired user stream capable of improving the total spectrum efficiency exists in the candidate set or the pairing threshold on a single resource block is reached.

According to the algorithm, each user needs to calculate the correlation coefficient pairwise on each resource block, calculate the spectrum efficiency and the total throughput under the condition of interference, and select the maximum throughput improvement result through comparison. Taking the example that the total bandwidth is divided into N resource blocks, and M candidate users are total, at least one resource block needs to be allocated in a single TTIThe calculation of the secondary correlation coefficient is carried out,calculating and comparing the secondary spectrum efficiency relationship, and considering that the time consumption of single-time correlation coefficient calculation is k₁us, the mean of single spectral efficiency calculation is k₂us, the time of 3/5 for a single TTI can be used for PL calculation of the pairing relationship, then the number of user streams that the PL can handle is shown in equation (4).

For the current system, the more users that the PL can calculate the pairing relationship within a single TTI, the higher the pairing success rate in the subsequent scheduling, and the greater the cell throughput. In the aspect of improving the computation capability of the pairing relationship in the PL single TTI, the current algorithm mainly has the following two defects:

first, PL calculates a shaping factor through SRS (Sounding Reference Symbol), and calculates a correlation coefficient based on the shaping factors of two users. And the SRS is reported periodically, taking a 40ms period as an example, which means that if two users calculate the pairing relationship for many times within 40ms, the same shaping factor is used to calculate the correlation coefficient each time, PL does meaningless repeated operation, and processing capacity is wasted.

Secondly, considering that the MAC layer should notify the PL pairing candidate set in 1 TTI as much as possible and obtain the pairing relationship table, so as to reduce the quantization of data to be scheduled and the change of scheduling priority of the user to be scheduled, the calculation time of the single pairing relationship is limited, and the PL alternates a large amount of correlation coefficient calculation in the calculation process of the pairing relationship, so that the number of users covered by the single calculation pairing relationship is small, and the pairing success rate of MAC scheduling and the system throughput are affected.

As shown in fig. 1, in time slot 0, the MAC layer sends a paired user candidate set a/B to the PL, and the PL calculates the pairing relationship from the reception of the paired user candidate set, and feeds back the pairing relationship to the MAC layer at time P1, and then performs similar operations in each slot (slot). In the time slot 0, when the PL receives the SRS, only the forming factor of the user receiving the SRS is calculated, and the correlation coefficient is not calculated, so that idle time occurs for a period of time; and the correlation calculation is performed on the users needing the pairing only after the moment P2.

The embodiment of the invention mainly considers the characteristics of low time delay and high throughput of a 5G system, and continuously uses the original algorithm, on one hand, the data volume to be scheduled of a user in single scheduling is improved, and the candidate set user cannot keep up with the change of the data volume to be scheduled actually, so that the invalid pairing relationship is increased, and the processing time of PL is wasted; on the other hand, the number of users scheduled at a time is increased, but the effective pairing relationship cannot be improved, so that the improvement of the system throughput is limited. It is therefore desirable to optimize the efficient pairing of UEs for computation within a PL single TTI in both ways.

Compared with the original LTE system, the 5G system has the following two characteristics:

(1) TTI (transmission time interval) of single scheduling is reduced, and the number of users processed in fixed time is increased;

(2) the 5G bandwidth is increased, the total data amount of single TTI scheduling is increased, the BO change of the user is faster,

aiming at the two points, in order to ensure that the pairing relationship calculated at a single time can cover more users, the embodiment of the invention optimizes the pairing relationship calculation algorithm as follows:

and when the PL receives the SRS report of the UE, clearing the correlation coefficient updating record identifications of the reported UE and all users, and calculating two correlation coefficients of the reported user and K users which have recently performed correlation coefficient calculation. If the number of users who have recently performed correlation coefficient calculation is less than K, calculating correlation coefficients of the reported user and current (K-M) online users in addition to the M user correlation coefficients which have recently performed pairing relation calculation, and updating calculation record identifiers of the reported UE and the K users with recalculated correlation coefficients after the calculation is finished. Wherein the value of K can be set to different sizes according to the processing capacity of the processor.

When the PL receives the pairing candidate set notified by the MAC, the correlation coefficient calculation operation is interrupted, and the notification message is used as a trigger point to trigger the pairing relationship calculation. During the period, when two correlation coefficients are calculated, the correlation coefficient updating marks of two users are inquired, the correlation coefficient is calculated and the marks are recorded for the non-updated correlation coefficients, and the updated correlation coefficients are directly taken for the updated correlation coefficients.

The following description will be made by way of specific examples.

Fig. 2 is a flowchart of a MUMIMO-based user pairing method in an embodiment of the present invention, which may be used at a base station side, for example: PL on the base station side; as shown in fig. 2, the method may include the steps of:

s210: receiving a pairing user candidate set sent by a MAC layer, wherein the pairing user candidate set comprises a plurality of candidate users.

Specifically, the PL on the base station side may receive the paired user candidate set sent by the MAC layer, and calculate the pairing relationship.

S220: determining a correlation coefficient between each candidate user according to the locally stored MUMIMO correlation coefficient record and SRS information; wherein, the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient between each user.

Specifically, the MUMIMO correlation coefficient record is used to hold the respective users for which the correlation coefficients have been calculated, and the correlation coefficients between the respective users.

Such as: the paired user candidate set includes candidate users a/B/C. The MUMIMO correlation coefficient record comprises the user A/B/C with the calculated correlation coefficient. At this time, in determining the correlation coefficient between the candidate users a/B/C, it can be determined from the users a/B/C in the MUMIMO correlation coefficient record without recalculation.

For another example: the paired user candidate set includes candidate users a/B/C. The MUMIMO correlation coefficient record comprises the user A/B/F with the calculated correlation coefficient. At this time, in determining the correlation coefficient between the candidate users a/B/C, the correlation coefficient of the candidate user a/B may be determined according to the users a/B/F in the MUMIMO correlation coefficient record, and the correlation coefficient between the candidate user a/C and the candidate user B/C may be calculated by using the above formula (1).

S230: and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

As can be seen from the above embodiments, after receiving a candidate set of paired users sent by an MAC layer, a PL may determine a correlation coefficient between each candidate user according to a locally stored MUMIMO correlation coefficient record and SRS information, calculate a first pairing relationship between each candidate user according to the correlation coefficient, and feed back the first pairing relationship to the MAC layer, so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relationship, thereby reducing the repetitive operations of the PL on correlation coefficient calculation, reducing the computational complexity in a limited time of pairing relationship calculation, improving the processing capability of pairing relationship calculation in a fixed time, ensuring that the MAC layer can obtain a pairing relationship table covering more users before scheduling, and further improving the user pairing success rate and system throughput.

Further, based on the above method, determining the correlation coefficient between the candidate users according to the locally stored MUMIMO correlation coefficient record and SRS information in the step S220 may include:

(1-1) inquiring a correlation coefficient between a first candidate user and a second candidate user in the MUMIMO correlation coefficient record; wherein the first candidate user and the second candidate user are used to characterize any two users of the respective candidate users; if the query is received, executing (1-2), otherwise, executing (1-3).

Specifically, the MUMIMO correlation coefficient record is used to hold the respective users for which the correlation coefficients have been calculated, and the correlation coefficients between the respective users. In order to avoid repeated calculation of correlation coefficients, when the correlation coefficients among the candidate users are determined, the correlation coefficients can be preferentially inquired from the MUMIMO correlation coefficient record, and if the correlation coefficients are inquired, the correlation coefficients are directly acquired and are not recalculated; if the matching relation is not inquired, calculation is needed, and the calculation result is stored in the MUMIMO related coefficient record, so that repeated calculation in the next matching relation calculation period can be avoided.

Such as: the paired user candidate set includes candidate users a/B/C. The MUMIMO correlation coefficient record comprises the user A/B/F with the calculated correlation coefficient. At this time, when determining the correlation coefficient between the candidate users a/B/C, the correlation coefficient of the candidate user a/B may be determined according to the users a/B/F in the MUMIMO correlation coefficient record, and the correlation coefficient between the candidate user a/C and the candidate user B/C may be calculated by using the above formula (1), and the calculation result is stored in the MUMIMO correlation coefficient record, where the MUMIMO correlation coefficient record includes the users a/B/F/a/B/C with the calculated correlation coefficients.

(1-2) if the correlation coefficient between the first candidate user and the second candidate user is inquired, acquiring the correlation coefficient between the first candidate user and the second candidate user from the first correlation coefficient record.

(1-3) if the correlation coefficient between the first candidate user and the second candidate user is not queried, calculating the correlation coefficient between the first candidate user and the second candidate user according to the SRS information, and storing the correlation coefficient between the first candidate user and the second candidate user in the MUMIMO correlation coefficient record.

As can be seen from the above embodiments, in the MUMIMO correlation coefficient record, the correlation coefficient between the first candidate user and the second candidate user is queried; if the correlation coefficient is found, the correlation coefficient is directly obtained, otherwise, the correlation coefficient is calculated according to the SRS information and is stored in the MUMIMO correlation coefficient record, so that the correlation coefficient can be directly obtained from the MUMIMO correlation coefficient record when the pairing relation calculation is subsequently executed, and the efficiency of the pairing relation calculation is improved.

Further, based on the above method, the method may further include the following steps:

(2-1) when a Sounding Reference Symbol (SRS) signal sent by a reporting user is received during the calculation of the pairing relationship, removing a correlation coefficient related to the reporting user in the MUMIMO correlation coefficient record; a starting point in the pairing relationship calculation period is a pairing user candidate set sent by a received MAC layer, and an ending point in the pairing relationship calculation period is the first pairing relationship fed back to the MAC layer;

and (2-2) in an idle period after the pairing relation calculation period, calculating a correlation coefficient between the reported user and one or more appointed users according to the SRS signal.

And (2-3) storing the correlation coefficient between the reporting user and each appointed user in the MUMIMO correlation coefficient record.

As can be seen from the above embodiments, after receiving an SRS signal, the PL clears the correlation coefficient related to the reported user, calculates the correlation coefficient between the reported user and one or more specified users in an idle period after the pairing relationship calculation period, and stores the correlation coefficient in the MUMIMO correlation coefficient record, so that the correlation coefficient can be directly obtained from the MUMIMO correlation coefficient record without repeatedly calculating the user correlation coefficient when subsequently performing the pairing relationship calculation, thereby reducing the repeated operation of the PL on the correlation coefficient calculation, reducing the calculation complexity in the limited time of the pairing relationship calculation, and increasing the rate of the pairing relationship calculation.

Further, based on the above method, the idle period in (2-2) includes a period in an SRS period other than the pairing relationship calculation period.

Specifically, as shown in fig. 3, P1, P2, and P3 are pairing relation calculation periods, C1 is an idle period after P1, and C2 is an idle period after P2, and both of these idle periods can be used for correlation coefficient calculation, that is, both of C1 and C2 are correlation coefficient calculation periods.

It can be seen from the above embodiments that the idle period except for each pairing relationship calculation period can be used as a correlation coefficient calculation period, so that even if the number of processing users in a 5G system per TTI decreases, and the total data amount of single TTI scheduling increases due to an increase in 5G bandwidth, which user data to be scheduled changes faster, PL can actively calculate the correlation coefficient of part of users after receiving SRS, thereby reducing the repetition calculation of correlation coefficient in the pairing relationship calculation period, increasing the number of UEs in which pairing relationships are calculated in the same time, ensuring that the duration of 5G single TTI decreases and the number of users in single slot scheduling increases, the MAC layer can obtain a sufficient pairing relationship table covering users before scheduling, and further improving the pairing success rate and the system throughput.

Further, based on the above method, when the calculating of the correlation coefficient between the reporting user and one or more designated users according to the SRS signal in (2-2) above is performed, the method may include:

(3-1) determining a first number of the appointed users for carrying out correlation coefficient calculation with the reporting user.

Specifically, the first number may be a value set in advance by the base station side, such as: 10 pieces.

(3-2) for any one of the designated users, inquiring the correlation coefficient between the reported user and the designated user in the MUMIMO correlation coefficient record; if the query is received, executing (3-3), otherwise executing (3-4).

Specifically, before the correlation coefficient is calculated, it is also required to search in the MUMIMO correlation coefficient record, for the purpose of avoiding repeated calculation of the correlation coefficient.

Such as: as shown in fig. 3, after receiving an SRS signal within a period P1 and clearing the correlation coefficient related to the reporting user, the PL does not immediately calculate the correlation coefficient related to the reporting user, but starts to calculate the correlation coefficient related to the reporting user only during a period C1, but when the reporting user is a candidate user during a period P1, since the correlation coefficient between the reporting user and another candidate user is calculated during a period P1 and stored in the MUMIMO correlation coefficient record, although the correlation coefficient related to the reporting user is calculated only during a period C1 later, at this time, a part of the correlation coefficient of the reporting user is stored in the MUMIMO correlation coefficient record, and in order to avoid repeatedly calculating the correlation coefficient, the correlation coefficient existing in the MUMIMO correlation coefficient record is not recalculated during a period C1.

In addition, when the correlation coefficient of the reported user is calculated during C1, the correlation coefficient calculation cannot be completed during C1 because there are more users that need to be calculated, and thus, the incomplete correlation coefficient calculation may be continued during the subsequent C2 until the SRS signal is received next time.

(3-3) if the correlation coefficient between the reporting user and the designated user is inquired, not recalculating the correlation coefficient between the reporting user and the designated user;

and (3-4) if the correlation coefficient between the reported user and the designated user is not inquired, calculating the correlation coefficient between the reported user and the designated user according to the SRS signal.

As can be seen from the above embodiments, when calculating the correlation coefficient between the reporting user and one or more designated users according to the SRS signal, the correlation coefficient between the reporting user and the designated users may be queried in the MUMIMO correlation coefficient record; if the correlation coefficient is found, the calculation is not repeated, otherwise, the correlation coefficient is calculated, and the calculated correlation coefficient is stored in the MUMIMO correlation coefficient record, so that the repeated operation of PL on correlation coefficient calculation is further reduced, and the user pairing efficiency based on MUMIMO is improved.

Further, based on the above method, the first number in (3-1) above is corresponding to the capability of the base station side processor.

Specifically, since the first number is corresponding to the capability of the base station side processor, the base station side advances by a value that can be matched with its own processing capability, such as: 10 pieces.

It can be seen from the above embodiments that when the PL reports the correlation coefficient between the user and the designated user, the PL can determine the number of the designated users according to its own processing capability, which not only ensures that the computation complexity of the pairing relationship computation within a limited time is reduced as much as possible, but also improves the reliability of the correlation coefficient computation.

Further, based on the method, the specified users in (3-1) above include users who have performed pairing relationship calculation within a set time, and/or online users.

Specifically, when the designated user is determined, users who have performed the correlation coefficient calculation within a set time (i.e., users who have performed the correlation coefficient calculation recently) may be preferred, and if the users who have performed the correlation coefficient calculation within the set time cannot satisfy the first number, online users are selected until the first number of users who have performed the correlation coefficient calculation with the reporting user is finally reached.

As can be seen from the above embodiments, the designated users may include users who have performed pairing relationship calculation within a set time and/or online users, so that the requirement of processing that PL actively calculates correlation coefficients of some users after receiving SRS is met, and the practicability of user pairing based on MUMIMO is also improved.

The following takes 6 users (i.e., users a/B/C/D/E/F) as an example to describe in detail the specific implementation process of the user pairing method based on MUMIMO in the embodiment of the present invention:

assuming that there are currently 6 users, i.e. users a/B/C/D/E/F, and a correlation coefficient and a pairing relationship have been calculated by a/B/F before, at the beginning of P1 in slot 0 in fig. 3, the PL receives a pairing user candidate set notified by the MAC, i.e. candidate users a/B/C, and the PL calculates its pairing relationship on each resource block according to the currently stored correlation coefficient of user a/B/C and feeds back to the MAC layer within P1. P1 is generally limited to 250 us. PL also updates the A/B/F/A/B/C of the user who has calculated the correlation coefficient in the record of calculating the MUMIMO correlation coefficient.

In the period of P1, after receiving the SRS reported by UE, namely reporting user A/B/D, PL calculates the shaping factor according to the SRS, and clears the correlation coefficient between user A/B/D and A/B/F/A/B/C. Then, after the PL feeds back the pairing relationship table to the MAC layer, the PL will calculate the correlation coefficient of the user a/B/D and a/B/F/a/B/C during C1 before the candidate set message of the next MAC (i.e. during correlation coefficient calculation), and add to the MUMIMO correlation coefficient record. Of course, if the next paired user candidate set of the MAC layer arrives earlier, it is not enough to update all the correlation coefficients of a/B, A/F, A/C, B/F, B/D, B/C, D/A, D/F, D/C during the period of C1, and only the correlation coefficient of a/B, A/F, A/C, B/F may be updated.

When the pairing relationship is calculated, in the MUMIMO correlation coefficient record, the update identifier of B/D (or a/D) is inquired to find that one UE has received SRS recently but has no updated correlation coefficient, the correlation coefficient of B/D (or a/D) is calculated when the pairing relationship is calculated, and when the B/a is inquired, the correlation coefficient is found to have been updated, no repeated calculation is needed, and the correlation coefficient in the locally stored MUMIMO correlation coefficient record is directly used.

After the P2 finishes reporting the pairing relationship to the MAC layer at the time PL, the correlation coefficient calculation of B/C is continued during the subsequent C2 period (i.e., the correlation coefficient calculation period).

The tentative SRS period is 40ms, that is, 80 TTIs, assuming that the pairing candidate set provided by the MAC at a time is M1, each time the correlation coefficient calculation considers the users appearing in the candidate set of the previous 5 times, half of the users exist in a single SRS period and are repeatedly transmitted to the PL as the candidate user set. The MAC layer allows the PL to calculate the pairing relationship for a duration of 3/5 TTIs per TTI. Assuming that time points of reporting the SRS by different users uniformly fall in each uplink slot in a period, the probability that the users join the candidate set is consistent in each TTI polling scheduling, and the probability is uniformly distributed in 80 TTIs, so that the probability that whether each user is updated by the PL verification is consistent can be simply considered, and the probability is linearly related to the SRS period and the calculation time length of the non-pairing relation.

The maximum number of times of the pair correlation coefficient calculated by the user in 80 TTIs isThe probability of calculating at the non-pairing relationship calculation time point in 1 slot is shown in formula (5).

As shown in fig. 4, before PL calculates the pairing relationship, the MUMIMO correlation coefficient record is queried to determine whether the user correlation coefficient needs to be recalculated, and then the pairing relationship is calculated.

Through the above, the PL can actively calculate the correlation coefficient after receiving the SRS and acquiring the user forming factor, so that the times of repeatedly calculating the correlation coefficient by the PL can be reduced, the processing capacity of the PL is improved, the times of calculating the internal correlation coefficient during the pairing relation time are reduced, the processing complexity is reduced, the pairing relation of more users can be calculated within the effective time, the success rate of user pairing is improved, and the system throughput is increased.

Fig. 5 is a flowchart illustrating an apparatus for user pairing based on MUMIMO according to this embodiment, where the apparatus may be used on a base station side, for example: PL on the base station side; as shown in fig. 5, the apparatus may include:

a receiving module 51, configured to receive a paired user candidate set sent by a media access control MAC layer, where the paired user candidate set includes multiple candidate users;

a determining module 52, configured to determine correlation coefficients between the candidate users according to locally stored multi-user multiple-input multiple-output (MUMIMO) correlation coefficient records and SRS information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

the pairing module 53 is configured to calculate a first pairing relationship between the candidate users according to the correlation coefficient, and feed back the first pairing relationship to the MAC layer, so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relationship.

Further, on the basis of the above apparatus embodiment, the determining module 52 may include:

the first inquiry submodule is used for inquiring the correlation coefficient between a first candidate user and a second candidate user in the MUMIMO correlation coefficient record; wherein the first candidate user and the second candidate user are used to characterize any two users of the respective candidate users;

an obtaining sub-module, configured to obtain a correlation coefficient between the first candidate user and the second candidate user from the first correlation coefficient record if the correlation coefficient between the first candidate user and the second candidate user is queried;

and the calculating sub-module is used for calculating the correlation coefficient between the first candidate user and the second candidate user according to the SRS information if the correlation coefficient between the first candidate user and the second candidate user is not inquired, and storing the correlation coefficient between the first candidate user and the second candidate user into the MUMIMO correlation coefficient record.

Further, on the basis of the above embodiment of the apparatus, the apparatus may further include:

a clearing module, configured to clear correlation coefficients related to a reporting user from the MUMIMO correlation coefficient records when receiving an SRS signal sent by the reporting user during a pairing relationship calculation; a starting point in the pairing relationship calculation period is a pairing user candidate set sent by a received MAC layer, and an ending point in the pairing relationship calculation period is the first pairing relationship fed back to the MAC layer;

a calculating module, configured to calculate, during an idle period after the pairing relationship calculation period, a correlation coefficient between the reporting user and one or more designated users according to the SRS signal;

and the storage module is used for storing the correlation coefficient between the reporting user and each designated user in the MUMIMO correlation coefficient record.

Further, on the basis of the above device embodiment, the idle period includes a period other than each pairing relationship calculation period in one SRS period.

Further, on the basis of the above apparatus embodiment, the calculation module may include:

a determining submodule, configured to determine a first number of the designated users for performing correlation coefficient calculation with the reporting user;

a second query submodule, configured to query, in the MUMIMO correlation coefficient record, a correlation coefficient between the reporting user and the designated user for any one of the designated users;

a first processing sub-module, configured to, if the correlation coefficient between the reporting user and the designated user is queried, not recalculate the correlation coefficient between the reporting user and the designated user;

and the second processing sub-module is used for calculating the correlation coefficient between the reporting user and the designated user according to the SRS signal if the correlation coefficient between the reporting user and the designated user is not inquired.

Further, on the basis of the above-described apparatus embodiment, said first number corresponds to the capabilities of the base station side processor.

Further, on the basis of the above device embodiment, the specified users include users who have performed correlation coefficient calculation within a set time, and/or online users.

The resource allocation apparatus described in this embodiment may be used to implement the method embodiments, and the principle and technical effect are similar, which are not described herein again.

Fig. 6 shows a schematic physical structure diagram of a base station, and as shown in fig. 6, the base station may include: a processor (processor)601, a communication Interface (Communications Interface)602, a memory (memory)603 and a communication bus 604, wherein the processor 601, the communication Interface 602 and the memory 603 complete communication with each other through the communication bus 604. The processor 601 may call logic instructions in the memory 603 to perform the following method:

receiving a pairing user candidate set sent by a MAC layer, wherein the pairing user candidate set comprises a plurality of candidate users;

determining a correlation coefficient between each candidate user according to the locally stored MUMIMO correlation coefficient record and SRS information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

In addition, the logic instructions in the memory 603 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Further, embodiments of the present invention disclose a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which when executed by a computer, the computer is capable of performing the methods provided by the above-mentioned method embodiments, for example, comprising:

receiving a pairing user candidate set sent by a MAC layer, wherein the pairing user candidate set comprises a plurality of candidate users;

determining a correlation coefficient between each candidate user according to the locally stored MUMIMO correlation coefficient record and SRS information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, and for example, the method includes:

receiving a pairing user candidate set sent by a MAC layer, wherein the pairing user candidate set comprises a plurality of candidate users;

determining a correlation coefficient between each candidate user according to the locally stored MUMIMO correlation coefficient record and SRS information; the MUMIMO correlation coefficient record is used for storing each user with the calculated correlation coefficient and the correlation coefficient among the users;

and calculating a first pairing relation among the candidate users according to the correlation coefficient, and feeding back the first pairing relation to the MAC layer so that the MAC layer performs corresponding scheduling resource allocation according to the first pairing relation.

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.