CN114599041B - Fusion method for calculation and communication - Google Patents
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- CN114599041B CN114599041B CN202210035660.8A CN202210035660A CN114599041B CN 114599041 B CN114599041 B CN 114599041B CN 202210035660 A CN202210035660 A CN 202210035660A CN 114599041 B CN114599041 B CN 114599041B
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- 238000004364 calculation method Methods 0.000 title claims abstract description 26
- 238000004891 communication Methods 0.000 title claims abstract description 23
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- 238000013461 design Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 5
- 238000013468 resource allocation Methods 0.000 claims description 5
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 claims description 3
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/142—Network analysis or design using statistical or mathematical methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/24—Cell structures
- H04W16/28—Cell structures using beam steering
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
- H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a fusion method of calculation and communication, which comprises the following steps: the cell center deploys a multi-antenna base station equipped with an edge computing server, a large number of mobile devices access a wireless network through the base station and offload their own computing tasks to the base station through a wireless channel for processing. The base station reasonably distributes the calculation resources of the server, optimizes the transmitting power of the mobile equipment, designs the receiving wave beam of the base station based on the acquired channel state information and the calculation task characteristics required to be unloaded, and finally ensures the completion of the wireless transmission and calculation of the unloading task under the minimum time delay condition. The invention provides an effective computing and communication fusion method for the Internet of things service of a large number of mobile devices with limited resources in a computation intensive and time delay sensitive scene.
Description
Technical Field
The invention relates to the field of wireless communication, in particular to a computing and communication fusion method.
Background
In recent years, mobile devices and global internet of things core technologies are rapidly developed, novel digital infrastructures in smart cities are deployed on a large scale, the number and types of devices in networks are increased rapidly, and accordingly data streams generated by internet of things applications are increased explosively. According to the forecast report issued by GSMA, the global Internet of things equipment will continue to grow at a high speed in the next few years, the use quantity of the global Internet of things equipment in 2025 years will reach about 246 hundred million, and the Internet of things will be the third wave of world information industry following the computer and the Internet.
At present, more and more new applications of new services of the computation-intensive and time-delay-sensitive mobile internet of things are grown, such as augmented reality, internet of vehicles, automatic driving, industrial internet of things, smart cities and the like, which have strict requirement standards of ultralow delay, high reliability, user experience continuity and the like, and bring new challenges to traditional communication and cloud computing technologies. For this reason, edge computing is a solution for providing data processing at the network edge near the mobile device and the internet of things device data source, alleviating the problems of communication congestion and resource limitation. Meanwhile, an effective edge computing coordination mechanism is needed to optimize the use of various resources, so that the delay of the system is greatly reduced, the network load is lightened, and the energy consumption is reduced.
Therefore, the computing technology and the communication technology are effectively integrated, the limitation of the traditional cloud computing system is hopeful to be broken through, the application scene standard of more advanced internet of things equipment is met, the mobile edge computing technology is better utilized, and a series of problems when mass mobile equipment is accessed to a wireless network are solved.
Disclosure of Invention
The invention aims to solve the problems of limited communication, low calculation efficiency, excessive time delay, large energy consumption and the like when a large number of mobile devices are accessed in the scheme, and provides a calculation and communication fusion method.
The specific technical scheme adopted by the invention is as follows:
the invention provides a fusion method of calculation and communication, which comprises the following steps:
1) A base station which is provided with an edge calculation server and has N antennas is deployed in the center of a cell, and K mobile devices with single antennas are accessed into a wireless network through the base station; wherein, the cell refers to a range covered by one base station;
2) The base station is communicated withOverestimation or feedback, obtaining kth mobile device u k Channel vector h to the base station k K=1, …, K; respectively obtaining large-scale fading information g of the uplink channel from each device to the base station according to the long-term statistical information k The method comprises the steps of carrying out a first treatment on the surface of the H to be obtained k And g k Collectively referred to as channel state information;
3) Each different mobile device u k Based on different tasks ψ k The calculated amount of each task is c k And data size d k Transmitting to the base station, the edge computing server calculates the maximum computing power f max Transmitting to a base station; the obtained calculated amount is c k And data size d k Collectively referred to as offload tasks features;
4) The base station obtains channel state information (h k And g k ) Maximum computing power (f) of edge computing server max ) And offloading task features (c) k And d k ) Computing an offloading latency minimization algorithm based on edges of joint beamforming and resource allocation, designing a transmit power p for each mobile device k And fed back to the respective devices for each task ψ k Allocating corresponding computing resources f at an edge computing server k At the same time, the receiving wave beam w is designed for the base station k ；
5) Mobile device u k Constructing a transmit signalTask ψ k Is transmitted to the base station through an uplink channel, wherein p k For transmitting power s k Is a data signal obtained after sampling, quantizing, encoding and modulating; the base station then decodes the received signal using the received beam to the edge computing server to allocate computing resources f for each task k Execution task ψ k After the calculation process is completed, the calculation result is returned to the mobile device u k To achieve a convergence of overall system (including mobile devices, base stations, and edge computing servers) computation and communication.
Preferably, the step 4) is specifically as follows:
a) Initializing the transmit power p k ＝P max,k Computing resources allocated to each taskReception beam w k ＝[1,0,…,0] T Wherein P is max,k Maximum transmit power, f, for the kth mobile device max Calculating a maximum computing power of the server for the edge;
b) The design goal is to minimize the maximum offload latency in all mobile devicesWherein the unloading delayg k ＝1，|·| 2 Representing the square of the absolute value,/>Representing the variance of gaussian white noise;
c) Introducing auxiliary variables t, t 1,k 、t 2,k 、R k And Γ k The design goal is transformed to minimize t, letR k ≤log 2 (1+Γ k )，/>
d) Definition of intermediate variablesDefine constant->Order thetr (·) is the trace of the matrix;
e) Let p be based on maximum transmit power limit of mobile device k ≤P max,k ；
f) According to the maximum computing capacity limit of the edge computing server, let
g) Order the
Wherein->And->For the feasible point in the previous iteration, solving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX tool kit to obtain W k And f k ；
h) Order theSolving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX toolkit to obtain p k And f k ；
i) Alternately and iteratively solving the step g) and the step h) until t converges, and solving a solution which minimizes the maximum value t of the unloading delay to obtain p k 、f k And W is k For W k Decomposing the characteristic value to obtain w k 。
Compared with the prior art, the invention has the following beneficial effects:
the method for integrating calculation and communication solves a series of problems caused by limited communication, lack of calculation resources and overhigh calculation time delay due to task unloading of mass mobile equipment. The joint design of the received wave beam and the resource allocation algorithm provided by the invention has the advantages of low complexity, small system time delay, reasonable energy consumption and calculation resource allocation and the like.
Drawings
FIG. 1 is a system block diagram of a fusion method of computing and communication;
fig. 2 is a performance comparison of the proposed method (number of antennas 16, 32 and 64, respectively) in case of different numbers of antennas of the base station and different maximum transmit powers of the mobile device;
fig. 3 is a comparison of task offloading latency performance under different calculation and communication fusion methods.
Detailed Description
The invention is further illustrated and described below with reference to the drawings and detailed description. The technical features of the embodiments of the invention can be combined correspondingly on the premise of no mutual conflict.
Examples
In this embodiment, as shown in fig. 1, a system block diagram of a method for integrating computation and communication is shown, a base station has N antennas and is deployed with an edge computation server, and each mobile device configures a single antenna. The base station obtains the channel state information of all the mobile devices to the base station, the characteristics of each calculation task and the maximum calculation capacity of the edge calculation server, and designs the transmitting power of the mobile devices, the calculation resources allocated to each task and the receiving wave beam of the base station. Each mobile device in the cell transmits signals to the base station, and the base station receiver receives and decodes the data to the edge computing server to finish the unloading of the computing task.
The specific technical scheme adopted in the embodiment is as follows:
a method of fusion of computation and communication comprising the steps of:
1) Deploying a base station which is provided with an edge computing server and has N antennas, and accessing K mobile devices with single antennas into a wireless network through the base station;
2) The base station obtains the kth mobile device u through estimation or feedback k Channel vector h to the base station k K=1, …, K, and then obtaining the large-scale fading information g of the uplink channel from each device to the base station according to the long-term statistical information k The method comprises the steps of carrying out a first treatment on the surface of the Will obtainH of (2) k And g k Collectively referred to as channel state information;
3) Mobile device u k Based on task ψ k The calculated amount of each task is c k And data size d k Transmitting to the base station, the edge computing server calculates the maximum computing power f max Transmitting to a base station; the obtained calculated amount is c k And data size d k Collectively referred to as offload tasks features;
4) The base station designs the transmitting power p for each mobile device based on the obtained channel state information, the maximum computing capability of the edge computing server and the unloading task characteristics and the edge computing unloading time delay minimization algorithm based on the combined beam forming and the resource allocation k And feed back to the devices for each task ψ k Allocating a corresponding computing resource f at an edge computing server k At the same time, the receiving wave beam w is designed for the base station k . The transmission power p is based on the proposed algorithm in this step k Computing resource f k And a reception beam w k The design method of the method specifically adopts the steps a) to i) which are sequentially executed:
a) Initializing the transmit power p k ＝P max,k Computing resources allocated to each taskReception beam w k ＝[1,0,…,0] T Wherein P is max,k Maximum transmit power for kth mobile terminal, f max The maximum computing power of the server is calculated for the edge.
b) The design goal is to minimize the maximum offload latency in all mobile devicesWherein the unloading delay->g k ＝1,|·| 2 Representing the square of the absolute value of the sum,representing the variance of gaussian white noise.
c) Introducing auxiliary variables t, t 1,k 、t 2,k 、R k And Γ k Target conversion to minimize t, letR k ≤log 2 (1+Γ k )，/>
d) Definition of intermediate variablesDefine constant->Order thetr (·) is the trace of the matrix.
e) Let p be based on maximum transmit power limit of mobile device k ≤P max,k 。
f) According to the maximum computing capacity limit of the edge computing server, let
g) Order the
Wherein->And->For the feasible point in the previous iteration, solving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX tool box to obtain W k And f k 。
h) Order theSolving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX tool box to obtain p k And f k 。
i) Alternately and iteratively solving the step g) and the step h) until t converges, and solving a solution which minimizes the maximum value t of the unloading delay to obtain p k 、f k And W is k For W k Decomposing the characteristic value to obtain w k 。
5) Mobile device u k Constructing a transmit signalTask ψ k Is transmitted to the base station through an uplink channel, wherein p k For transmitting power s k Is a data signal obtained after sampling, quantizing, encoding and modulating; the base station then decodes the received signal using the received beam to the edge computing server to allocate computing resources f for each task k Execution task ψ k After the calculation process is completed, the calculation result is returned to the mobile device u k To achieve a convergence of mobile device computing and communication.
Computer simulation shows that as shown in fig. 2, the larger the maximum transmitting power of the mobile equipment is, the lower the unloading time delay is. Moreover, as the number of base station antennas increases, performance may be significantly improved. In addition, fig. 3 shows that the method of the present invention has obvious performance advantages compared with the mode of fixed transmission power maximum and average calculation resource. In particular, as the maximum transmit power of the mobile device increases, the performance gain achieved will gradually increase. Therefore, the invention provides an effective computing and communication fusion method for the Internet of things service of a large number of mobile devices with limited resources in a computation intensive and time delay sensitive scene.
The above embodiment is only a preferred embodiment of the present invention, but it is not intended to limit the present invention. Various changes and modifications may be made by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present invention. Therefore, all the technical schemes obtained by adopting the equivalent substitution or equivalent transformation are within the protection scope of the invention.
Claims (1)
1. A method of merging computation and communication, comprising the steps of:
1) Deploying a base station which is provided with an edge computing server and has N antennas, and accessing K mobile devices with single antennas into a wireless network through the base station;
2) The base station acquires a kth mobile device u through estimation or feedback k Channel vector h to the base station k K=1, …, K; respectively obtaining large-scale fading information g of the uplink channel from each device to the base station according to the long-term statistical information k The method comprises the steps of carrying out a first treatment on the surface of the H to be obtained k And g k Collectively referred to as channel state information;
3) Mobile device u k Based on task ψ k The calculated amount of each task is c k And data size d k Transmitting to the base station, the edge computing server calculates the maximum computing power f max Transmitting to a base station; the obtained calculated amount is c k And data size d k Collectively referred to as offload tasks features;
4) The base station designs the transmitting power p for each mobile device based on the obtained channel state information, the maximum computing capability of the edge computing server and the unloading task characteristics and the edge computing unloading time delay minimization algorithm based on the combined beam forming and the resource allocation k And feed back to the devices for each task ψ k Allocating a corresponding computing resource f at an edge computing server k At the same time, the receiving wave beam w is designed for the base station k ；
5) Mobile device u k Constructing a transmit signalTask ψ k Is transmitted to the base station through an uplink channel, wherein p k For transmitting power s k Is a task data signal obtained after sampling, quantizing, encoding and modulating; the base station then decodes the received signal using the received beam to the edge computing server to allocate computing resources f for each task k Execution task ψ k After the calculation process is completed, the calculation result is returned to the mobile device u k To achieve a fusion of computation and communication;
the step 4) is specifically as follows:
a) Initializing the transmit power p k ＝P max,k Computing resources allocated to each taskReception beam w k ＝[1,0,…,0] T Wherein P is max,k Maximum transmit power, f, for the kth mobile device max Calculating a maximum computing power of the server for the edge;
b) The design goal is to minimize the maximum offload latency in all mobile devicesWherein the unloading delayg k ＝1，|·| 2 Representing the square of the absolute value, sigma n 2 Representing the variance of gaussian white noise;
c) Introducing auxiliary variables t, t 1,k 、t 2,k 、R k And Γ k The design goal is transformed to minimize t, letR k ≤log 2 (1+Γ k )，/>t 1,k +t 2,k ≤t,/>…,K；
d) Definition of intermediate variablesDefine constant->Order thetr (·) is the trace of the matrix;
e) Let p be based on maximum transmit power limit of mobile device k ≤P max,k ；
f) According to the maximum computing capacity limit of the edge computing server, let
g) Order theWherein->And->For the feasible point in the previous iteration, solving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX tool kit to obtain W k And f k ；
h) Order theSolving the solution for minimizing the maximum value t of the unloading delay by using an interior point method or calling a CVX toolkit to obtain p k And f k ；
i) Alternately and iteratively solving the step g) and the step h) until t converges, and solving a solution which minimizes the maximum value t of the unloading delay to obtain p k 、f k And W is k For W k Decomposing the characteristic value to obtain w k 。
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