CN112272232A - Millimeter wave Internet of vehicles resource scheduling method and device, electronic equipment and storage medium - Google Patents

Millimeter wave Internet of vehicles resource scheduling method and device, electronic equipment and storage medium Download PDF

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CN112272232A
CN112272232A CN202011150165.9A CN202011150165A CN112272232A CN 112272232 A CN112272232 A CN 112272232A CN 202011150165 A CN202011150165 A CN 202011150165A CN 112272232 A CN112272232 A CN 112272232A
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time
base station
data
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CN112272232B (en
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陈亚文
王子凡
路兆铭
温向明
王宸
王阳
王鲁晗
曾琴
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Beijing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/046—Wireless resource allocation based on the type of the allocated resource the resource being in the space domain, e.g. beams

Abstract

The embodiment of the disclosure discloses a millimeter wave internet of vehicles resource scheduling method and device, electronic equipment and a storage medium. The resource scheduling method comprises the following steps: acquiring states of a plurality of data queues; in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues; determining a space-domain beam set in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by a base station; in each space-domain beam of the space-domain beam set, time-domain resources and/or frequency-domain resources are distributed, so that the space-domain beam set facilitates the time-frequency-domain resource collaborative scheduling on a plurality of channel coherent times within the beam coherent time, the space-domain beam resources and the time-domain and frequency-domain transmission resources are distributed more efficiently, the ideal signal receiving direction of the mobile equipment is aligned, the interference is avoided, the link gain is improved, the coverage range is expanded, the utilization efficiency of the space resources and the time-domain and frequency-domain resources is improved, and the overall throughput rate is improved.

Description

Millimeter wave Internet of vehicles resource scheduling method and device, electronic equipment and storage medium
Technical Field
The disclosure relates to the technical field of computers, in particular to a millimeter wave vehicle networking resource scheduling method and device, electronic equipment and a storage medium.
Background
In a wireless internet of things system, in order to ensure efficient transmission of data and improve the overall throughput efficiency of the system, efficient scheduling of spatial beams, time domain and frequency domain resources is required.
Disclosure of Invention
In order to solve the problems in the related art, the embodiments of the present disclosure provide a millimeter wave vehicle networking resource scheduling method and apparatus, an electronic device, and a storage medium.
In a first aspect, an embodiment of the present disclosure provides a resource scheduling method, including:
acquiring states of a plurality of data queues;
in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues;
determining a space-domain beam set in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by a base station;
allocating, in each spatial beam of the set of spatial beams, a time domain resource and/or a frequency domain resource.
With reference to the first aspect, in a first implementation manner of the first aspect, the allocating, in the beam coherence time, the arrival data to the plurality of data queues by using an access control method includes:
and in the beam coherence time, constructing the access control method by adopting a convex optimization mode, and distributing the arrival data to the plurality of data queues.
With reference to the first aspect, in a second implementation manner of the first aspect, the spatial beam set includes:
a set of transmit beams of the base station; and
a set of receive beams for the mobile device,
the determining the spatial-domain beam set in the beam coherence time according to the distribution of the mobile device in the wireless environment covered by the base station comprises:
in the beam coherence time, performing channel correlation analysis based on chordal distance on a wireless channel between the mobile equipment and the base station to obtain a channel chordal distance correlation analysis result;
and clustering by using a K-mean method according to the channel chordal distance correlation analysis result to obtain the centroid of the cluster, and determining the direction of the transmitting beam of the base station according to the centroid of the cluster.
With reference to the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the present disclosure further includes:
calculating the width of the transmission beam of the base station according to the direction of the transmission beam of the base station;
and calculating the width of the receiving beam of the mobile equipment according to the beam width product and the width of the transmitting beam of the base station.
With reference to the first aspect, in a fourth implementation manner of the first aspect, the allocating, in each spatial beam of the spatial beam set, a time domain resource and/or a frequency domain resource includes:
calculating a baseband channel gain in each spatial beam of the set of spatial beams during a channel coherence time;
and calculating the resource allocation of the frequency domain sub-channels according to the baseband channel gain in each space domain beam.
With reference to the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the calculating resource allocation to the frequency domain subchannels according to the baseband channel gain in each spatial beam includes:
and calculating the resource allocation of the frequency domain sub-channels by using an integer programming method according to the baseband channel gain in each space domain beam.
With reference to the first aspect, in a sixth implementation manner of the first aspect, the present disclosure further includes:
transmitting data in the plurality of data queues according to the spatial beam set and the time domain resources and/or frequency domain resources allocated in each spatial beam;
updating the status of the plurality of data queues.
In a second aspect, an embodiment of the present disclosure provides a resource scheduling apparatus, including: a data queue status acquisition module configured to acquire statuses of a plurality of data queues;
an access control module configured to allocate the arrival data to the plurality of data queues by using an access control method in a beam coherence time;
a spatial beam set determination module configured to determine a spatial beam set in a beam coherence time according to a distribution of mobile devices in a space covered by a base station;
a time-frequency domain resource allocation module configured to allocate a time domain resource and/or a frequency domain resource in each spatial beam of the set of spatial beams.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory and a processor; wherein the content of the first and second substances,
the memory is configured to store one or more computer instructions, where the one or more computer instructions are executed by the processor to implement the method according to the first aspect, the first implementation manner to the sixth implementation manner of the first aspect.
In a fourth aspect, an embodiment of the present disclosure provides a readable storage medium, on which computer instructions are stored, and the computer instructions, when executed by a processor, implement the method according to the first aspect, or any one of the first to sixth implementation manners of the first aspect.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the technical scheme provided by the embodiment of the disclosure, the states of a plurality of data queues are acquired; in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues; determining a space-domain beam set in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by a base station; in each space-domain beam of the space-domain beam set, time-domain resources and/or frequency-domain resources are allocated, so that the space-domain beam set provides reference basis for time-frequency domain resource cooperative scheduling based on a set space-domain beam scheduling result on a plurality of channel coherent times within the beam coherent time, the space-domain beam resources and time-domain and frequency-domain transmission resources are allocated more efficiently, an ideal signal receiving direction of mobile equipment is aligned, interference is avoided, link gain is improved, a coverage range is expanded, utilization efficiency of the space resources and the time-domain and frequency-domain resources is improved, and overall throughput rate is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
fig. 1a illustrates an exemplary flowchart of an implementation scenario of a resource scheduling method according to an embodiment of the present disclosure;
fig. 1b shows an exemplary schematic diagram of an implementation scenario of a resource scheduling method according to an embodiment of the present disclosure;
FIG. 2 shows a flow diagram of a resource scheduling method according to an embodiment of the present disclosure;
FIG. 3 shows a flow chart according to step S203 in the embodiment shown in FIG. 2;
fig. 4 shows a flowchart according to step S203 in another embodiment shown in fig. 2;
FIG. 5 shows a flow chart according to step S204 in the embodiment shown in FIG. 2;
FIG. 6 shows a flow diagram of a resource scheduling method according to another embodiment of the present disclosure;
fig. 7 is a block diagram illustrating a structure of a resource scheduling apparatus according to an embodiment of the present disclosure;
FIG. 8 shows a block diagram of an electronic device according to an embodiment of the present disclosure;
FIG. 9 is a schematic structural diagram of a computer system suitable for implementing a resource scheduling method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of labels, numbers, steps, actions, components, parts, or combinations thereof disclosed in the present specification, and are not intended to preclude the possibility that one or more other labels, numbers, steps, actions, components, parts, or combinations thereof are present or added.
It should be further noted that the embodiments and labels in the embodiments of the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Wireless internet vehicles are usually equipped with a large number of sensors, such as cameras, laser radars, infrared sensing, millimeter wave radars, etc., to accurately perceive environmental information such as road conditions, vehicles, etc. However, many sensors generate a large amount of data, up to 1TB per hour. Such huge sharing of environment-aware data poses a severe challenge to wireless network access rates. As the spectrum efficiency of the microwave wireless link gradually approaches to a theoretical extreme value, the design of a millimeter wave vehicle networking system is imperative. In the 5G millimeter wave internet of vehicles, wireless resources need to be scheduled in a space-time-frequency coordinated scheduling mode, so that the internet-connected vehicles can be accessed in a multiplexing mode through three space-time-frequency domains, and interference-free parallel transmission is realized.
As can be understood by those skilled in the art, in addition to the wireless internet vehicles, for example, mobile devices such as robots for power system inspection and plant protection unmanned aerial vehicles flying at low altitudes also face complex wireless environments, and space-time-frequency domain coordinated scheduling of wireless resources needs to be performed.
In order to solve the above problem, the present disclosure provides a resource scheduling method, device, electronic device, and readable storage medium.
Fig. 1a shows an exemplary flowchart of an implementation scenario of a resource scheduling method according to an embodiment of the present disclosure.
As shown in fig. 1a, the transmission of the car networking data takes "beam coherence time" as a time unit of beamforming. In the Beam Coherence Time (BCT), the Beam direction and Beam width of the base station transmission Beam and the networked vehicle reception Beam are not changed. In the initial part of the beam coherence time, an "available beam set decision phase" is included. In the available beam set decision phase, in step S101, an available beam set for a plurality of networked vehicles is determined according to a wireless environment, and beam directions and beam widths of a base station transmission beam and a networked vehicle reception beam are calculated. In the beam coherence time, the "available beam set decision phase" is followed by a plurality of "channel estimation phases" and "data transmission phases". The period of one "Channel estimation phase" and one "data transmission phase" corresponds to one "Channel correlation Time" (CCT).
In the channel estimation phase, in step S102, effective channel gain estimation is performed by using the available beam set; in the data transmission phase, in step S103, space-time-frequency resource scheduling is performed according to the effective channel gain estimation, and data transmission is performed on the scheduled resources.
Fig. 1b is an exemplary diagram illustrating an implementation scenario of a resource scheduling method according to an embodiment of the present disclosure.
As shown in fig. 1b, during the Beam Coherence Time (BCT), the access control 111 receives data blocks of a size a to be transmitted to K networked vehicles1[t]、a2[t]、......、aK[t]. The access control 111 puts the data into K queues 102, the K queues 112 correspond to K networked vehicles respectively, and the length of each queue is q1[t]、q2[t]、......、qK[t]. In the space-time-frequency resource cooperative scheduling 113, the scheduling of the transmission beam of the base station, the receiving beam of the networked vehicles, the time domain sub-frame and the frequency domain sub-channel resource of each networked vehicle is determined, and the TRP is transmitted to the transmitting antenna 114TRP of the base station1、TRP2、TRP3、......、TRPMA plurality of transmission beams 115 are formed to cover a plurality of networked vehicles. Internet vehicle 107UE1、UE2、......、UEKThe receive beam 116 is formed accordingly. The base station transmits the data in the K queues 102 to the networked vehicle 117UE through the transmitting beam 105 and the receiving beam 116 of the networked vehicle1、UE2、......、UEKThereby forming the received data of the networked vehicles. The receiving data rates of the K networked vehicles are r respectively1[t]、r2[t]、......、rK[t]. Speed of networked vehicle r1[t]、r2[t]、......、rK[t]After the data is correctly received, the queue 112 is updated.
The access control 111 controls the input of the size a of a block of data into the queue 112 within each BCT1[t]、a2[t]、......、aK[t]The space-time-frequency resource cooperative scheduling 113 takes out data from the queue 112 to the internet vehicle 117 by forming a transmitting and receiving beam and scheduling the time-frequency domain resource, so that the receiving data rate r is as high as possible1[t]、r2[t]、......、rK[t]Maximized so that queue 112 remains dynamically balanced without overflowing, i.e.
Figure BDA0002740929490000061
Wherein | q [ t | ]]||1Represents q [ t ]]The first-order norm of the time-frequency resource is obtained, so that the overall utilization efficiency of the space-time-frequency resource is improved as much as possible, and the overall throughput rate of the system is improved.
In the embodiments of the present disclosure, the present disclosure may generally propose a triple-iteration cooperative scheduling framework including access control-space-time-frequency resource cooperative scheduling-dynamic queue updating based on Lyapunov drift optimization theory.
The Lyapunov function of the tth BCT is defined as
Figure BDA0002740929490000062
Wherein
Figure BDA0002740929490000063
Represents a vector q [ t ]]Squared second order norm of (d). The corresponding Lyapunov drift function satisfies
Figure BDA0002740929490000064
Considering that the queue service rate and the arrival data of all vehicles in a BCT also have upper bounds, the upper bound of the Lyapunov drift function is set as
Figure BDA0002740929490000065
Wherein the constant epsilon is more than or equal to 0.
Let V denote a specific constant and U (a [ t ]) denote the system utility function of the millimeter wave Internet of vehicles with respect to a [ t ]. According to the Lyapunov drift optimization theory, the joint optimization problem of a plurality of BCT time slots can be converted into the iterative optimization problem of each BCT, namely the minimization is carried out in the tth BCT
Figure BDA0002740929490000071
Therefore, stable operation of the network is maintained in the dynamic queue updating process, and the system utility is maximized.
In the embodiment of the disclosure, a triple iteration cooperative scheduling framework including access control, space-time-frequency resource cooperative scheduling and dynamic queue updating based on the Lyapunov drift optimization theory is established in the above manner.
In embodiments of the present disclosure, in access control 111, the problem is solved within each BCT
Figure BDA0002740929490000072
Wherein the system utility function U (a [ t ]) may be a second order continuously derivable strongly convex increasing function of the data block size a (t) reached within the BCT. Therefore, the access control problem can be a convex optimization problem, the convex optimization problem is effectively solved in polynomial time, and partial system utility functions can directly obtain a closed expression of an optimal solution. The optimal solution for access control can be expressed as, for example, when a proportional fair scheduling utility function is employed
Figure BDA0002740929490000073
In the embodiments of the present disclosure, in the space-time-frequency resource co-scheduling 113, for any given queue length q [ t ]]And the size of the arriving data block a [ t ]]And optimizing the cooperative scheduling of the space-time-frequency resources slot by slot to maximize the service rate of the weighted system. Order to
Figure BDA0002740929490000074
Representing the feasible domain of the overall service rate of the system, the problem is modeled as the following maximum problem solving
Figure BDA0002740929490000075
In an embodiment of the present disclosure, in the "available beam set decision phase" of fig. 1a, a "vehicle clustering decision based on channel correlation" may be performed first.
In the embodiment of the present disclosure, a set of networked vehicles accessing one base station beam is defined as one vehicle cluster. And the parallel interference-free transmission of data can be carried out by utilizing spatial multiplexing gain among different vehicle clusters accessing different beams. For a plurality of networked vehicles in the same vehicle cluster accessed with the same wave beam, the wireless channel characteristics between the base station and the networked vehicles are fully utilized, and the transmission resource multiplexing among the networked vehicles is carried out through the digital wave beam forming, the frequency domain sub-channel and the time domain CCT scheduling of the vehicles, so that the space-time-frequency domain collaborative scheduling gain is fully exerted, and the utilization rate of space-time-frequency triple degree of freedom is maximized.
In the embodiments of the present disclosure, the millimeter wave internet of vehicles may be designed to cope with a dense high-speed access scenario, and there are cases where the distribution of millimeter wave base stations and vehicles is dense. Based on the similarity of the positions of the adjacent vehicles and the environmental scattering, the channels between the adjacent vehicles have strong correlation, so that the vehicles with similar positions and environmental scattering tend to form clusters and access the same beam in the analog beam domain. The channel correlation between the base station and the networked vehicle depends on factors such as the antenna spacing, the arrangement mode of the antenna array, the angular domain expansion and the departure/arrival angle of signals, the geographical position spacing and the like.
In the embodiment of the present disclosure, in the "vehicle clustering decision based on channel correlation", the "channel correlation analysis based on chordal distance" is performed first.
In the embodiment of the disclosure, the correlation analysis is performed by using the second-order statistical characteristics of the multi-transmitting and multi-receiving channel matrix of the base station and the networked vehicle, namely, the channel covariance matrix characteristic space. To base station and k networking vehicle UEkThe inter-channel covariance matrix is subjected to singular value decomposition, and a unitary matrix U formed by expanding eigenvectors corresponding to the eigenvalueskModeling as a feature space, and further modeling the feature space as an observation space, the feature space of each networked vehicle corresponding to one of the BCTsAnd (6) observing. And measuring the correlation of the channels between the base station and different networked vehicles by adopting the chord distance between the feature spaces. For any two networked vehicles UEq、UElCharacteristic space U ofq，UlThe chord distance between them is shown as
Figure BDA0002740929490000081
In an embodiment of the present disclosure, in the "vehicle clustering decision based on channel correlation", after the "channel correlation analysis based on chordal distance", the "vehicle clustering based on K-Means clustering" may be performed.
Within one BCT, due to the number of base station radio frequency chains, it is assumed that a mm-wave vehicle networking base station can emit N beams at most. In order to realize the full utilization of space-domain beam resources, all vehicles are divided into N clusters according to the channel correlation, namely, each beam serves one cluster of vehicles. Under the condition of a given cluster number, dividing the networked vehicle clusters by adopting K-means clustering, and enabling the channel correlation of all networked vehicles in one cluster to be stronger as much as possible, so that the characteristic space of the covariance matrix covers a specific subspace. For a particular vehicle cluster, the center node of the cluster can be defined as the centroid, and the channel covariance matrix eigenspace of the centroid is modeled as the mean of the nodes of the whole cluster
Figure BDA0002740929490000082
Wherein eigenp(X) denotes a unitary matrix composed of eigenvectors corresponding to p main eigenvalues of the matrix X.
In embodiments of the present disclosure, a decision problem for a cluster of vehicles may be formulated as
Figure BDA0002740929490000091
Wherein C represents a clustering scheme comprising N clusters, i.e.
Figure BDA0002740929490000092
Figure BDA0002740929490000093
Indicates the ith vehicle cluster, contains CiAnd (4) a vehicle.
In the embodiment of the disclosure, the solution of the vehicle cluster decision problem can be performed by adopting a K-means clustering algorithm. Firstly, randomly generating N centroids in an area wirelessly covered by a base station, calculating the centroid closest to each observed networked vehicle, and adding a cluster where the centroid closest to each observed networked vehicle is located. And then, the mass center of each cluster is recalculated, the cluster to which the networked vehicle belongs is adjusted, and the process is continuously repeated until convergence is reached, so that a stable clustering scheme is obtained.
In an embodiment of the present disclosure, in the "available beam set decision phase" of fig. 1a, a "spatial beam scheduling decision" may be made after a "channel correlation-based vehicle clustering decision". In the millimeter wave internet of vehicles, vehicles correspond to N wave beams of a base station in a one-to-one mode in the form of N clusters.
In an embodiment of the present disclosure, in the "spatial beam scheduling decision", a "beam direction decision" may be made first. And taking the azimuth angles of the centroids of the N clusters relative to the base station as N beam orientations, namely the central direction of the vehicle cluster channel covariance matrix feature space.
In embodiments of the present disclosure, in the "spatial beam scheduling decision", a "beam width decision" may be made after the "beam direction decision".
In the embodiment of the disclosure, the beam width of each base station is optimized for the transmitting beam of each base station and the receiving beam of the networked vehicle, so that a communication link with high signal-to-noise ratio can be established for the vehicles in the cluster. Let thetat,θuRespectively, a transmission beam and a reception beam width vector. Order to
Figure BDA0002740929490000097
Transmission beam forming gain (transmission) representing generation of base station transmission beamSend array gain), order
Figure BDA0002740929490000098
Indicating networked vehicles UEkThe resulting receive beamforming gain (receive array gain) is then the link signal strength and transmission rate are determined by the product of the two, i.e., the overall link gain
Figure BDA0002740929490000099
The signals in the main lobe of the beam can obtain the same and higher beam forming gain, and the signal beam forming gain in the range of the side lobe is also the same but is far smaller than the main lobe gain.
In the embodiment of the disclosure, according to the aforementioned space-time-frequency resource cooperative scheduling framework based on the Lyapunov drift theory, the optimal beam width can be realized
Figure BDA0002740929490000094
Is maximized.
Firstly, optimizing the beam width integral product: integral product of beam widths
Figure BDA0002740929490000095
Determines the overall link gain
Figure BDA0002740929490000096
Is specifically as follows
Figure BDA0002740929490000101
Figure BDA0002740929490000102
Wherein
Figure BDA0002740929490000103
In order for the base station to transmit the beamwidth,
Figure BDA0002740929490000104
and receiving the beam width for the networked vehicle.
In the embodiment of the present disclosure, the
Figure BDA0002740929490000105
The maximization problem translates into an overall product on the beamwidth
Figure BDA0002740929490000106
The single variable optimization problem can use an ellipsoid method to solve an optimal value
Figure BDA0002740929490000107
Secondly, making a bilateral beam width decision: at the base station side, a beam guard interval delta is introduced, and for any transmission beam i, the transmission beams at the two sides of the space direction are respectively assumed to be m and n, and the beam directions are respectively assumed to be thetai,θm,θnThen the maximum beamwidth of the transmission beam i is defined as
Figure BDA0002740929490000108
The optimized base station transmitting beam width corresponds to the user cluster C according to the beam iiNumber and centroid to base station distance DiDetermine, in particular set to
Figure BDA0002740929490000109
Wherein, k is a weight factor, and can be flexibly set according to the preference of performance parameters.
For networked vehicles, the receive beamwidth may be set accordingly
Figure BDA00027409294900001010
In the embodiment of the present disclosure, in the "data transmission phase" of fig. 1a, "time-frequency cooperative scheduling decision" may be made.
In the embodiment of the disclosure, after the airspace wave beam scheduling decision on the BCT time scale is completed, the time-frequency domain resource scheduling on the CCT time scale can be further performed according to the scheduling result, so that the space-time-frequency domain multiplexing gain is fully excavated through cooperative scheduling optimization, and the overall throughput rate of the system is improved.
In the embodiment of the disclosure, a time-frequency domain collaborative scheduling algorithm based on a greedy algorithm can be adopted to convert a multi-CCT non-causal joint scheduling problem into a CCT-by-CCT optimized frequency domain sub-channel allocation problem. In each CCT, firstly, estimating the effective channel gain of a baseband according to the previously determined spatial-domain wave beams; then, establishing a frequency domain sub-channel distribution optimization problem, wherein the optimization target of the frequency domain sub-channel distribution optimization problem is
Figure BDA0002740929490000111
And the optimization variable is used for allocating the indication to the frequency domain sub-channels of all the networked vehicles. When a specific frequency domain subchannel is not allocated to a specific networked vehicle, the allocation indication of the frequency domain subchannel is 0; when a specific frequency domain subchannel is allocated for a specific networked vehicle, the allocation indication of the frequency domain subchannel is 1. The optimization problem may be an integer programming problem, solved by a branch and bound algorithm.
In the embodiment of the present disclosure, in the BCT, the above-mentioned "time-frequency cooperative scheduling decision" may be executed per CCT until the end of the BCT.
One of ordinary skill in the art may understand that the resource scheduling method of the present disclosure may be used for, in addition to the millimeter wave internet vehicles, mobile devices such as power system inspection robots, plant protection unmanned aerial vehicles flying at low altitude, or other application scenarios, and the present disclosure does not limit this.
Fig. 2 shows a flowchart of a resource scheduling method according to an embodiment of the present disclosure. As shown in fig. 2, the resource scheduling method includes steps S201, S202, S203, and S204.
In step S201, the states of a plurality of data queues are acquired.
In step S202, in the beam coherence time, the access control method is adopted to allocate the arrival data to the plurality of data queues.
In step S203, a spatial beam set is determined in a beam coherence time according to the distribution of mobile devices in the wireless environment covered by the base station.
In step S204, a time domain resource and/or a frequency domain resource is allocated to each spatial beam of the spatial beam set.
In the embodiment of the disclosure, the millimeter wave internet of vehicles base station may acquire the states of N data queues corresponding to N internet vehicles in the coverage area of the base station, and may include the length q of the N data queues at time t1[t]、q2[t]、......、qK[t]. The beam direction and the beam width of the base station transmitting beam and the networked vehicle receiving beam may not change within the beam coherence time BCT. Within the BCT, arriving data may be assigned to N data queues ready for delivery to N networked vehicles. According to the distribution of the networked vehicles in the wireless environment covered by the base station, the spatial-domain beam set sent out by the base station can be determined in the beam coherence time. The spatial beam set includes: the transmission beam set of the base station and the receiving beam set of the networked vehicle. The beam coherence time BCT may comprise a plurality of channel coherence times CCT. According to the spatial-domain beam set, time domain resources and/or frequency domain resources can be distributed in each spatial-domain beam of the spatial-domain beam set in the channel coherent time, so that spatial, time domain and frequency domain multiplexing gains are fully utilized, and the system throughput rate is improved.
According to the technical scheme provided by the embodiment of the disclosure, the states of a plurality of data queues are acquired; in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues; determining a spatial domain beam set sent by a base station in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by the base station; in each space-domain beam of the space-domain beam set, time-domain resources and/or frequency-domain resources are allocated, so that the space-domain beam set provides reference basis for time-frequency domain resource cooperative scheduling based on a set space-domain beam scheduling result on a plurality of channel coherent times within the beam coherent time, the space-domain beam resources and time-domain and frequency-domain transmission resources are allocated more efficiently, an ideal signal receiving direction of mobile equipment is aligned, interference is avoided, link gain is improved, a coverage range is expanded, utilization efficiency of the space resources and the time-domain and frequency-domain resources is improved, and overall throughput rate is improved.
In embodiments of the present disclosure, for the access control portion, the problem may be solved within each BCT
Figure BDA0002740929490000121
Wherein the system utility function U (a [ t ]) may be a second order continuously derivable strongly convex increasing function of the data block size a (t) reached within the BCT. Therefore, the access control problem can be a convex optimization problem, the convex optimization problem is effectively solved in polynomial time, and partial system utility functions can directly obtain a closed expression of an optimal solution. The optimal solution for access control can be expressed as, for example, when a proportional fair scheduling utility function is employed
Figure BDA0002740929490000122
By means of convex optimization, queue overflow is avoided, i.e. guarantee
Figure BDA0002740929490000131
The system reliability and the overall throughput rate are improved.
According to the technical solution provided by the embodiment of the present disclosure, allocating arrival data to the plurality of data queues by using the access control method in the beam coherence time includes: and in the beam coherence time, the access control method is constructed in a convex optimization mode, and the arrival data are distributed to the plurality of data queues, so that queue overflow is avoided, and the system reliability and the overall throughput rate are improved.
Fig. 3 shows a flow chart according to step S203 in the embodiment shown in fig. 2. As shown in fig. 3, step S203 in fig. 2 includes: steps S301 and S302.
In step S301, in the beam coherence time, a channel correlation analysis based on a chordal distance is performed on a wireless channel between the mobile device and the base station, so as to obtain a channel chordal distance correlation analysis result.
In step S302, according to the result of the channel chordal distance correlation analysis, clustering is performed by using a K-means method, a centroid of the cluster is obtained, and a direction of a transmission beam of the base station is determined according to the centroid of the cluster.
In an embodiment of the present disclosure, the spatial beam set comprises: a set of transmit beams for the base station and a set of receive beams for the networked vehicles. The channel correlation analysis based on the chord distance can be carried out on the wireless channel between the mobile equipment and the base station, the clustering is carried out by using a K-mean method, the mass centers of N clusters are obtained, and the directions of N sending beams of the base station are determined according to the mass centers of the N clusters. Each cluster can serve a plurality of networking vehicles, the base station can cover as many networking vehicles as possible through limited N transmitting beams in a clustering mode, and the spatial gain among different transmitting beams is utilized to transmit data by adopting the same time and frequency domain resources, so that the overall throughput of the system is improved.
According to the technical scheme provided by the embodiment of the disclosure, the spatial domain beam set comprises: a set of transmit beams of the base station; and a set of receive beams for the mobile device, the determining the set of spatial beams in the beam coherence time according to a distribution of the mobile device in a wireless environment covered by the base station comprising: in the beam coherence time, performing channel correlation analysis based on chordal distance on a wireless channel between the mobile equipment and the base station to obtain a channel chordal distance correlation analysis result; and clustering by using a K-mean method according to the channel chordal distance correlation analysis result to obtain the centroid of the cluster, and determining the direction of the transmitting beam of the base station according to the centroid of the cluster, so that space beam resources and time domain and frequency domain transmission resources are more efficiently distributed, the ideal signal receiving direction of the mobile equipment is aligned, interference is avoided, link gain is improved, the coverage range is expanded, the utilization efficiency of the space resources and the time domain and frequency domain resources is improved, and the overall throughput rate is improved.
Fig. 4 shows a flowchart according to step S203 in another embodiment shown in fig. 2. Fig. 4 includes steps S401 and S402, in addition to steps S301 and S302, which are the same as those in fig. 3.
In step S401, the width of the transmission beam of the base station is calculated according to the direction of the transmission beam of the base station.
In step S402, the width of the reception beam of the mobile device is calculated from the beam width product and the width of the transmission beam of the base station.
In the embodiment of the present disclosure, the width of the transmission beam of the base station may be calculated first.
Introducing a beam guard interval delta at the base station side, and for any beam i, assuming that the beams at two sides of the space direction are m and n respectively, and the beam directions are theta respectivelyi,θm,θnThen the maximum beam width of the beam i is defined as
Figure BDA0002740929490000141
The optimized wave beam width of the base station corresponds to a user cluster C according to the wave beam iiNumber and centroid to base station distance DiDetermine, in particular set to
Figure BDA0002740929490000142
Wherein, k is a weight factor, and can be flexibly set according to the preference of performance parameters.
Then, the width of the receiving beam of the networked vehicle is calculated according to the beam width product and the width of the transmitting beam of the base station
Figure BDA0002740929490000143
Wherein
Figure BDA0002740929490000144
Is the integral product of beam width
Figure BDA0002740929490000145
The optimum value of (c).
According to the technical scheme provided by the embodiment of the disclosure, the method further comprises the following steps: calculating the width of the transmission beam of the base station according to the direction of the transmission beam of the base station; and calculating the width of the receiving beam of the mobile equipment according to the beam width product and the width of the transmitting beam of the base station, thereby optimizing the gain of a spatial link, expanding the coverage range, improving the utilization efficiency of spatial resources and time domain and frequency domain resources and improving the overall throughput rate.
Fig. 5 shows a flow chart according to step S204 in the embodiment shown in fig. 2. As shown in fig. 5, step S204 in fig. 2 includes: steps S501 and S502.
In step S501, a baseband channel gain in each spatial beam of the spatial beam set is calculated in each spatial beam during a channel coherence time.
In step S502, resource allocation to the frequency domain sub-channels is calculated according to the baseband channel gain in each spatial domain beam.
In an embodiment of the present disclosure, one beam coherence time BCT may include a plurality of channel coherence times CCT. And calculating the gain of the baseband channel in each space-domain beam in CCT, and calculating the resource allocation of the frequency-domain sub-channels according to the gain of the baseband channel, so that the time-domain and frequency-domain channel resources can be fully utilized, and the overall throughput rate of the system is improved.
According to the technical scheme provided by the embodiment of the present disclosure, allocating time domain resources and/or frequency domain resources in each spatial beam of the spatial beam set comprises: calculating a baseband channel gain in each spatial beam of the set of spatial beams during a channel coherence time; and calculating resource allocation to the frequency domain sub-channels according to the baseband channel gain in each space domain beam, thereby improving the utilization efficiency of space resources and time domain and frequency domain resources and improving the overall throughput rate.
In the embodiment of the disclosure, a time-frequency domain collaborative scheduling algorithm based on a greedy algorithm can be adopted to convert a multi-CCT non-causal joint scheduling problem into a CCT-by-CCT optimized frequency domain sub-channel allocation problem. In each CCT, firstly, estimating the effective channel gain of a baseband according to the previously determined spatial-domain wave beams; then, establishing a frequency domain sub-channel distribution optimization problem, wherein the optimization target of the frequency domain sub-channel distribution optimization problem is
Figure BDA0002740929490000151
And the optimization variable is used for allocating the indication to the frequency domain sub-channels of all the networked vehicles. When a specific frequency domain subchannel is not allocated to a specific networked vehicle, the allocation indication of the frequency domain subchannel is 0; when a specific frequency domain subchannel is allocated for a specific networked vehicle, the allocation indication of the frequency domain subchannel is 1. The optimization problem may be an integer programming problem that can be solved by a branch and bound algorithm.
According to the technical scheme provided by the embodiment of the present disclosure, calculating resource allocation to the frequency domain sub-channel according to the baseband channel gain in each spatial beam includes: and calculating the resource allocation of the frequency domain sub-channels by using an integer programming method according to the baseband channel gain in each space domain beam, thereby improving the utilization efficiency of space resources and time domain and frequency domain resources and improving the overall throughput rate.
Fig. 6 shows a flowchart of a resource scheduling method according to another embodiment of the present disclosure. Fig. 6 includes steps S601 and S602, in addition to steps S201, S202, S203 and S204 similar to those of fig. 2.
In step S601, the data in the plurality of data queues are transmitted according to the spatial beam set and the time domain resource and/or the frequency domain resource allocated in each spatial beam.
In step S602, the states of the plurality of data queues are updated.
In the embodiment of the present disclosure, after the data of the data queue is transmitted, the state of the data queue, for example, the length of the data queue, may be updated, so as to reliably track the state of the data queue and make the next scheduling decision.
According to the technical scheme provided by the embodiment of the disclosure, the data in the plurality of data queues are transmitted according to the spatial beam set and the time domain resources and/or the frequency domain resources distributed in each spatial beam; and updating the states of the plurality of data queues, so that the data in the queues are transmitted to the networked vehicles, the stability of the data queues is ensured, the utilization efficiency of space resources and time domain and frequency domain resources is improved, and the overall throughput rate is improved.
Fig. 7 shows a block diagram of a resource scheduling apparatus according to an embodiment of the present disclosure. As shown in fig. 7, the resource scheduling apparatus 700 includes: a data queue state obtaining module 701, an access control module 702, a spatial-domain beam set determining module 703, and a time-frequency domain resource allocating module 704.
The data queue status acquisition module 701 is configured to acquire the status of a plurality of data queues.
The access control module 702 is configured to allocate the arriving data to the plurality of data queues using an access control method during the beam coherence time.
The spatial beam set determination module 703 is configured to determine a spatial beam set in a beam coherence time according to the distribution of mobile devices in the space covered by the base station.
The time-frequency domain resource allocation module 704 is configured to allocate time domain resources and/or frequency domain resources in each spatial beam of the set of spatial beams.
According to the technical scheme provided by the embodiment of the disclosure, the data queue state acquisition module is configured to acquire the states of a plurality of data queues; an access control module configured to allocate the arrival data to the plurality of data queues by using an access control method in a beam coherence time; a spatial beam set determination module configured to determine a spatial beam set in a beam coherence time according to a distribution of mobile devices in a space covered by a base station; the time-frequency domain resource allocation module is configured to allocate time domain resources and/or frequency domain resources in each space domain beam of the space domain beam set, so that the space beam resources and time domain and frequency domain transmission resources are allocated more efficiently, an ideal signal receiving direction of the mobile device is aligned, interference is avoided, link gain is improved, a coverage range is expanded, utilization efficiency of the space resources and the time domain and frequency domain resources is improved, and overall throughput rate is improved.
Fig. 8 shows a block diagram of an electronic device according to an embodiment of the present disclosure.
The embodiment of the present disclosure also provides an electronic device, as shown in fig. 8, the electronic device 800 includes a processor 801 and a memory 802; wherein the memory 802 stores instructions executable by the at least one processor 801, the instructions being executable by the at least one processor 801 to implement the steps of:
acquiring states of a plurality of data queues;
in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues;
determining a space-domain beam set in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by a base station;
allocating, in each spatial beam of the set of spatial beams, a time domain resource and/or a frequency domain resource.
In an embodiment of the present disclosure, said allocating, in the beam coherence time, the arrival data to the plurality of data queues by using an access control method includes:
and in the beam coherence time, constructing the access control method by adopting a convex optimization mode, and distributing the arrival data to the plurality of data queues.
In an embodiment of the present disclosure, the spatial beam set comprises:
a set of transmit beams of the base station; and
a set of receive beams for the mobile device,
the determining the spatial-domain beam set in the beam coherence time according to the distribution of the mobile device in the wireless environment covered by the base station comprises:
in the beam coherence time, performing channel correlation analysis based on chordal distance on a wireless channel between the mobile equipment and the base station to obtain a channel chordal distance correlation analysis result;
and clustering by using a K-mean method according to the channel chordal distance correlation analysis result to obtain the centroid of the cluster, and determining the direction of the transmitting beam of the base station according to the centroid of the cluster.
In an embodiment of the present disclosure, the instructions are further executable by the at least one processor 801 to implement the steps of:
calculating the width of the transmission beam of the base station according to the direction of the transmission beam of the base station;
and calculating the width of the receiving beam of the mobile equipment according to the beam width product and the width of the transmitting beam of the base station.
In an embodiment of the present disclosure, said allocating, in each spatial beam of the set of spatial beams, a time domain resource and/or a frequency domain resource comprises:
calculating a baseband channel gain in each spatial beam of the set of spatial beams during a channel coherence time;
and calculating the resource allocation of the frequency domain sub-channels according to the baseband channel gain in each space domain beam.
In an embodiment of the present disclosure, the calculating resource allocation for the frequency domain sub-channels according to the baseband channel gain in each spatial beam includes:
and calculating the resource allocation of the frequency domain sub-channels by using an integer programming method according to the baseband channel gain in each space domain beam.
In an embodiment of the present disclosure, the instructions are further executable by the at least one processor 801 to implement the steps of:
transmitting data in the plurality of data queues according to the spatial beam set and the time domain resources and/or frequency domain resources allocated in each spatial beam;
updating the status of the plurality of data queues.
FIG. 9 is a schematic structural diagram of a computer system suitable for implementing a resource scheduling method according to an embodiment of the present disclosure.
As shown in fig. 9, the computer system 900 includes a processing unit 901 which can execute various processes in the embodiments shown in the above-described figures according to a program stored in a Read Only Memory (ROM)902 or a program loaded from a storage section 908 into a Random Access Memory (RAM) 903. In the RAM903, various programs and data necessary for the operation of the system 900 are also stored. The processing unit 901, the ROM902, and the RAM903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
The following components are connected to the I/O interface 905: an input portion 906 including a keyboard, a mouse, and the like; an output section 907 including components such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 908 including a hard disk and the like; and a communication section 909 including a network interface card such as a LAN card, a modem, or the like. The communication section 909 performs communication processing via a network such as the internet. The drive 910 is also connected to the I/O interface 905 as necessary. A removable medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 910 as necessary, so that a computer program read out therefrom is mounted into the storage section 908 as necessary. The processing unit 901 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.
In particular, according to embodiments of the present disclosure, the methods described above with reference to the figures may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the methods of the figures. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section 909, and/or installed from the removable medium 911.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the node in the above embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims (10)

1. A resource scheduling method comprises the following steps:
acquiring states of a plurality of data queues;
in the beam coherence time, an access control method is adopted to distribute the arriving data to the plurality of data queues;
determining a space-domain beam set in a beam coherence time according to the distribution of mobile equipment in a wireless environment covered by a base station;
allocating, in each spatial beam of the set of spatial beams, a time domain resource and/or a frequency domain resource.
2. The method of claim 1, wherein the allocating the arriving data to the plurality of data queues using an access control method during the beam coherence time comprises:
and in the beam coherence time, constructing the access control method by adopting a convex optimization mode, and distributing the arrival data to the plurality of data queues.
3. The method of claim 1, wherein the set of spatial beams comprises:
a set of transmit beams of the base station; and
a set of receive beams for the mobile device,
the determining the spatial-domain beam set in the beam coherence time according to the distribution of the mobile device in the wireless environment covered by the base station comprises:
in the beam coherence time, performing channel correlation analysis based on chordal distance on a wireless channel between the mobile equipment and the base station to obtain a channel chordal distance correlation analysis result;
and clustering by using a K-mean method according to the channel chordal distance correlation analysis result to obtain the centroid of the cluster, and determining the direction of the transmitting beam of the base station according to the centroid of the cluster.
4. The method of claim 3, further comprising:
calculating the width of the transmission beam of the base station according to the direction of the transmission beam of the base station;
and calculating the width of the receiving beam of the mobile equipment according to the beam width product and the width of the transmitting beam of the base station.
5. The method of claim 1,
the allocating, in each spatial beam of the set of spatial beams, a time domain resource and/or a frequency domain resource comprises:
calculating a baseband channel gain in each spatial beam of the set of spatial beams during a channel coherence time;
and calculating the resource allocation of the frequency domain sub-channels according to the baseband channel gain in each space domain beam.
6. The method of claim 5, wherein calculating the resource allocation for the frequency domain subchannels based on the baseband channel gain in each spatial beam comprises:
and calculating the resource allocation of the frequency domain sub-channels by using an integer programming method according to the baseband channel gain in each space domain beam.
7. The method of claim 1, further comprising:
transmitting data in the plurality of data queues according to the spatial beam set and the time domain resources and/or frequency domain resources allocated in each spatial beam;
updating the status of the plurality of data queues.
8. A resource scheduling apparatus, comprising:
a data queue status acquisition module configured to acquire statuses of a plurality of data queues;
an access control module configured to allocate the arrival data to the plurality of data queues by using an access control method in a beam coherence time;
a spatial beam set determination module configured to determine a spatial beam set in a beam coherence time according to a distribution of mobile devices in a space covered by a base station;
a time-frequency domain resource allocation module configured to allocate a time domain resource and/or a frequency domain resource in each spatial beam of the set of spatial beams.
9. An electronic device comprising a memory and a processor; wherein the content of the first and second substances,
the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the processor to implement the method of any one of claims 1-7.
10. A readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the method of any one of claims 1-7.
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