CN113395684A - Distributed operation unloading method based on variable bandwidth channel - Google Patents

Distributed operation unloading method based on variable bandwidth channel Download PDF

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CN113395684A
CN113395684A CN202110940450.9A CN202110940450A CN113395684A CN 113395684 A CN113395684 A CN 113395684A CN 202110940450 A CN202110940450 A CN 202110940450A CN 113395684 A CN113395684 A CN 113395684A
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user
energy consumption
network
pair
unloading
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CN113395684B (en
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高瞻
沈良
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Nanjing Zhineng Xintong Technology Development Co ltd
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Nanjing Zhineng Xintong Technology Development Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • 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
    • H04W16/14—Spectrum sharing arrangements between different networks
    • 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
    • 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 distributed operation unloading method based on a variable bandwidth channel, wherein in a distributed wireless network, a terminal with larger operation requirement can unload partial data to peripheral terminals for processing, so that a data processing task is completed within a given time limit, the terminal has differentiated unloading requirement, different amounts of spectrum resources can be used according to requirements, in addition, the terminal can overlap and use partial spectrum resources according to the conditions of network topology and the like, and the energy consumption minimization of the whole network is realized by a distributed decision method through a better response learning algorithm. The invention can better adapt the differentiated unloading requirement to the limited frequency spectrum resource, has higher utilization rate of the frequency spectrum resource, can share the frequency spectrum resource by the terminal, has more flexible frequency utilization mode and can improve the communication performance.

Description

Distributed operation unloading method based on variable bandwidth channel
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a distributed operation unloading method based on a variable bandwidth channel.
Background
In a distributed wireless network, terminals usually have differentiated operation requirements and operation capabilities. The terminal with large operation requirement can unload part of operation amount to the terminal with small operation requirement and strong operation capability, thereby completing the data processing task within a given time limit. The terminal with unloading requirement is called user, the terminal providing calculation service is called helper, and the communication link formed by one user and one helper is called D2D pair. Such a technology is called a device-to-device (D2D) assisted mobile edge computing technology, and has been widely applied to the scenes of the touch internet, the internet of things and the like.
Under the constraint of limited spectrum resources, most of the existing related works assume that a pair of D2D works on an isomorphic channel, and a control center centrally decides the behaviors of unloading proportion, unloading channel, unloading power and the like of all users. Such working methods have the following disadvantages: 1) under the conditions of large number of D2D pairs and large decision space, the control center needs to acquire information of all D2D pairs, make a centralized decision and issue a decision result, so that the information interaction cost is high and the implementation complexity is high; 2) homogeneous channel bandwidth and differentiated offloading requirements are difficult to adapt, resulting in low utilization of spectrum resources.
In order to solve the above problems, researchers have proposed a distributed channel access scheme based on a variable bandwidth. However, the existing correlation works to avoid mutual interference, and it is mostly assumed that the variable bandwidth channels accessed by the users cannot overlap. Although the working method considers the adaptation of the differentiated frequency demand and the limited frequency spectrum resource, the communication performance is difficult to be ensured due to the limited accessible channel resource of the terminal. In fact, when the terminal operates on the superimposable channel, although mutual interference is introduced, the communication performance can be improved in certain situations due to the increase of available spectrum resources. At one extreme, the users in the network are distributed sparsely enough, and the mutual interference is very small, so that the highest transmission rate can be obtained by multiplexing the full frequency band by all the users in the whole network.
Disclosure of Invention
The invention aims to provide a distributed operation unloading method based on a variable bandwidth channel, aiming at the problems that the channel cannot be overlapped, the resource is limited and the communication performance is difficult to ensure in a distributed channel access mode of the variable bandwidth.
The technical scheme of the invention is as follows:
the invention provides a distributed operation unloading method based on a variable bandwidth channel, which comprises the following steps:
step 1, the total bandwidth of the frequency spectrum in the network is
Figure 544503DEST_PATH_IMAGE001
Is divided into
Figure 905077DEST_PATH_IMAGE002
A plurality of non-overlapping sub-channels in series
Figure 495458DEST_PATH_IMAGE003
Each subchannel having a bandwidth of
Figure 458735DEST_PATH_IMAGE004
(ii) a Then
Figure 349331DEST_PATH_IMAGE005
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure 739861DEST_PATH_IMAGE006
A D2D pair, the set of which is
Figure 83118DEST_PATH_IMAGE007
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure 459872DEST_PATH_IMAGE008
The user and the helper in (1) are respectively recorded as the user
Figure 64029DEST_PATH_IMAGE009
And helpers
Figure 861346DEST_PATH_IMAGE009
User of
Figure 754216DEST_PATH_IMAGE009
The amount of data to be processed is
Figure 934661DEST_PATH_IMAGE010
The amount of data processed is
Figure 658904DEST_PATH_IMAGE010
The number of processor cycles required is
Figure 532182DEST_PATH_IMAGE011
All users in the network need to be in
Figure 931589DEST_PATH_IMAGE012
The data processing task is completed within a time period during which the user is
Figure 72982DEST_PATH_IMAGE009
Offloading portions of data to a helper
Figure 527097DEST_PATH_IMAGE009
Then help the person
Figure 695911DEST_PATH_IMAGE009
Performing remote operations while the user is simultaneously
Figure 235476DEST_PATH_IMAGE009
Performing local operation on the residual data in the whole process;
step 2, the user
Figure 757725DEST_PATH_IMAGE009
Has a discharge ratio of
Figure 190980DEST_PATH_IMAGE013
Then its local operation frequency is
Figure 701333DEST_PATH_IMAGE014
With local computational power consumption of
Figure 243042DEST_PATH_IMAGE015
Wherein
Figure 568981DEST_PATH_IMAGE016
for the user
Figure 997688DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 3, the user
Figure 744190DEST_PATH_IMAGE009
Selecting a plurality of continuous sub-channels for operation unloading, wherein the total unloading power is
Figure 258348DEST_PATH_IMAGE017
Selected set of sub-channels as
Figure 247032DEST_PATH_IMAGE018
With an offloaded throughput of
Figure 530246DEST_PATH_IMAGE019
Wherein
Figure 87129DEST_PATH_IMAGE020
the number of sub-channels to select for it,
Figure 947638DEST_PATH_IMAGE021
for the user
Figure 880959DEST_PATH_IMAGE009
And helpers
Figure 143313DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 871098DEST_PATH_IMAGE022
in the case of background noise, the noise level,
Figure 94269DEST_PATH_IMAGE023
for its sub-channel
Figure 206448DEST_PATH_IMAGE024
Is subject to interference, wherein the user
Figure 464254DEST_PATH_IMAGE025
Is composed of
Figure 221995DEST_PATH_IMAGE006
D2D centering user
Figure 198041DEST_PATH_IMAGE009
Other than
Figure 66640DEST_PATH_IMAGE026
Any one of the users may be selected from the group of users,
Figure 913373DEST_PATH_IMAGE027
for the user
Figure 107594DEST_PATH_IMAGE025
The total power of the offload of (1),
Figure 39778DEST_PATH_IMAGE028
for the user
Figure 479112DEST_PATH_IMAGE025
The number of sub-channels to be selected,
Figure 445931DEST_PATH_IMAGE029
for the user
Figure 951999DEST_PATH_IMAGE025
And helpers
Figure 496112DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 847459DEST_PATH_IMAGE030
if D2D pairs
Figure 793419DEST_PATH_IMAGE025
Also operating on subchannels
Figure 470388DEST_PATH_IMAGE024
Upper, then it is paired with D2D
Figure 377164DEST_PATH_IMAGE009
Generate interference, users
Figure 922415DEST_PATH_IMAGE009
Is unloaded for a time of
Figure 598247DEST_PATH_IMAGE031
With a discharge energy consumption of
Figure 446117DEST_PATH_IMAGE032
；
Step 4, the helper
Figure 463358DEST_PATH_IMAGE009
The remote operation time is
Figure 422087DEST_PATH_IMAGE033
The remote operation frequency is
Figure 483584DEST_PATH_IMAGE034
The remote computing energy consumption is
Figure 361410DEST_PATH_IMAGE035
Wherein
Figure 242778DEST_PATH_IMAGE036
for the help of
Figure 5198DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 5, pair D2D
Figure 45835DEST_PATH_IMAGE009
Total energy consumed is
Figure 235508DEST_PATH_IMAGE037
Total energy consumption of the whole network D2D pair is
Figure 338593DEST_PATH_IMAGE038
；
And 6, realizing the minimization of the energy consumption of the whole network by a distributed operation unloading method through a better response learning algorithm.
Further, the preferred response learning algorithm in step 6 specifically includes the following steps:
step 6.1, user in initialization state
Figure 763758DEST_PATH_IMAGE039
Randomly selecting a number of consecutive sub-channels
Figure 534268DEST_PATH_IMAGE040
And unloading ratio
Figure 894842DEST_PATH_IMAGE041
The combined strategy is recorded as
Figure 376901DEST_PATH_IMAGE042
；
Step 6.2 in
Figure 481124DEST_PATH_IMAGE043
In the second iteration, a D2D pair is randomly selected
Figure 106140DEST_PATH_IMAGE009
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 762249DEST_PATH_IMAGE043
the number of iterations is indicated and,
Figure 105506DEST_PATH_IMAGE044
，
Figure 482261DEST_PATH_IMAGE045
is the maximum iteration number; divide D2D pairs in the network
Figure 351997DEST_PATH_IMAGE009
The set of policies for all but D2D pairs is
Figure 54373DEST_PATH_IMAGE046
；
Step 6.3, update D2D pairs
Figure 884926DEST_PATH_IMAGE009
Updating the policy according to equation (1):
Figure 190006DEST_PATH_IMAGE047
Figure 789614DEST_PATH_IMAGE048
wherein,
Figure 662892DEST_PATH_IMAGE049
for one of the federation policies that it tries at random,
Figure 344190DEST_PATH_IMAGE050
is based on
Figure 593906DEST_PATH_IMAGE051
The full network D2D of (2) for total energy consumption,
Figure 48021DEST_PATH_IMAGE052
is based on
Figure 951255DEST_PATH_IMAGE053
The whole network D2D pair total energy consumption.
Further, the whole network D2D has the corresponding joint strategy for the total energy consumption
Figure 756400DEST_PATH_IMAGE054
To the whole net
Figure 544227DEST_PATH_IMAGE006
D2D pairs respectively calculate the consumed energy according to the steps 2-5 and accumulate the obtained energy consumption
The invention has the beneficial effects that:
compared with the prior art, the invention has the remarkable advantages that: (1) compared with a method for unloading data on an isomorphic channel, the method can better adapt differentiated unloading requirements to limited spectrum resources, and the utilization rate of the spectrum resources is higher; (2) compared with a method for unloading data on a non-overlapping channel, a user can share spectrum resources according to conditions such as network topology and the like, the frequency utilization mode is more flexible, and other characteristics and advantages of the invention, of which the communication performance can be improved, are described in detail in a following detailed description.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
Fig. 1 is a schematic diagram of a network scenario in which the present invention is applicable.
Fig. 2 is a frequency utilization scheme for the scenario of fig. 1.
Fig. 3 is a schematic diagram of a network structure in an embodiment of the present invention.
Fig. 4 is a graph comparing the energy consumption based on the proposed method and the existing method in the embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein.
The invention is described in further detail below with reference to the figures and the embodiments.
Referring to fig. 1, there are three pairs of D2D in the diagram, D2D pair 1 is closer to D2D pair 2, and D2D pair 3 is further from the other two D2D pairs. The user in each pair D2D offloads some of the data to the helper for remote operations and the remainder performs local operations.
With reference to fig. 2, since the distance between D2D pair 1 and D2D pair 2 in fig. 1 is relatively short, to avoid mutual interference, both sides operate on non-overlapping channels, and since D2D pair 3 in fig. 1 is relatively far from the other two D2D pairs, to increase the transmission rate, it operates in the full frequency band, and the used channels overlap with D2D pair 1 and D2D pair 2. In addition, since D2D in fig. 1 offloads more data for 1, it occupies more spectrum resources than D2D for 2.
The invention discloses a distributed operation unloading method based on a variable bandwidth channel, which comprises the following steps:
step 1, the total bandwidth of the frequency spectrum in the network is
Figure 977483DEST_PATH_IMAGE001
Is divided into
Figure 192563DEST_PATH_IMAGE002
A plurality of non-overlapping sub-channels in series
Figure 485004DEST_PATH_IMAGE003
Each subchannel having a bandwidth of
Figure 669998DEST_PATH_IMAGE004
(ii) a Then
Figure 98705DEST_PATH_IMAGE005
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure 484687DEST_PATH_IMAGE006
A D2D pair, the set of which is
Figure 624944DEST_PATH_IMAGE007
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure 754574DEST_PATH_IMAGE008
The user and the helper in (1) are respectively recorded as the user
Figure 37788DEST_PATH_IMAGE009
And helpers
Figure 719305DEST_PATH_IMAGE009
User of
Figure 720759DEST_PATH_IMAGE009
The amount of data to be processed is
Figure 388501DEST_PATH_IMAGE010
The amount of data processed is
Figure 916434DEST_PATH_IMAGE010
The number of processor cycles required is
Figure 378639DEST_PATH_IMAGE011
All users in the network need to be in
Figure 867390DEST_PATH_IMAGE012
The data processing task is completed within a time period during which the user is
Figure 197877DEST_PATH_IMAGE009
Offloading portions of data to a helper
Figure 282114DEST_PATH_IMAGE009
Then help the person
Figure 39854DEST_PATH_IMAGE009
Performing remote operations while the user is simultaneously
Figure 78218DEST_PATH_IMAGE009
Performing local operation on the residual data in the whole process;
step 2, the user
Figure 87762DEST_PATH_IMAGE009
Has a discharge ratio of
Figure 324708DEST_PATH_IMAGE013
Then its local operation frequency is
Figure 394295DEST_PATH_IMAGE014
With local computational power consumption of
Figure 592058DEST_PATH_IMAGE015
Wherein
Figure 31392DEST_PATH_IMAGE016
for the user
Figure 263791DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 3, the user
Figure 504279DEST_PATH_IMAGE009
Selecting a plurality of continuous sub-channels for operation unloading, wherein the total unloading power is
Figure 313972DEST_PATH_IMAGE017
Selected set of sub-channels as
Figure 930898DEST_PATH_IMAGE018
With an offloaded throughput of
Figure 752224DEST_PATH_IMAGE019
Wherein
Figure 553826DEST_PATH_IMAGE020
the number of sub-channels to select for it,
Figure 726182DEST_PATH_IMAGE021
for the user
Figure 615640DEST_PATH_IMAGE009
And helpers
Figure 947265DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 795135DEST_PATH_IMAGE022
in the case of background noise, the noise level,
Figure 189207DEST_PATH_IMAGE023
for its sub-channel
Figure 499666DEST_PATH_IMAGE024
Is subject to interference, wherein the user
Figure 295584DEST_PATH_IMAGE025
Is composed of
Figure 173410DEST_PATH_IMAGE006
D2D centering user
Figure 320358DEST_PATH_IMAGE009
Other than
Figure 82777DEST_PATH_IMAGE026
Any one of the users may be selected from the group of users,
Figure 857835DEST_PATH_IMAGE027
for the user
Figure 781929DEST_PATH_IMAGE025
The total power of the offload of (1),
Figure 150593DEST_PATH_IMAGE028
for the user
Figure 575758DEST_PATH_IMAGE025
The number of sub-channels to be selected,
Figure 346268DEST_PATH_IMAGE029
for the user
Figure 441263DEST_PATH_IMAGE025
And helpers
Figure 923322DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 761966DEST_PATH_IMAGE030
if D2D pairs
Figure 511616DEST_PATH_IMAGE025
Also operating on subchannels
Figure 43091DEST_PATH_IMAGE024
Upper, then it is paired with D2D
Figure 120769DEST_PATH_IMAGE009
Generate interference, users
Figure 153316DEST_PATH_IMAGE009
Is unloaded for a time of
Figure 898418DEST_PATH_IMAGE031
With a discharge energy consumption of
Figure 335215DEST_PATH_IMAGE032
；
Step 4, the helper
Figure 290402DEST_PATH_IMAGE009
The remote operation time is
Figure 736427DEST_PATH_IMAGE033
The remote operation frequency is
Figure 70456DEST_PATH_IMAGE034
The remote computing energy consumption is
Figure 566903DEST_PATH_IMAGE035
Wherein
Figure 619173DEST_PATH_IMAGE036
for the help of
Figure 603309DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 5, pair D2D
Figure 447637DEST_PATH_IMAGE009
Total energy consumed is
Figure 226237DEST_PATH_IMAGE037
Total energy consumption of the whole network D2D pair is
Figure 31382DEST_PATH_IMAGE038
；
Step 6, realizing the minimization of the energy consumption of the whole network by a distributed operation unloading method through a better response learning algorithm, which comprises the following specific steps:
step 6.1, user in initialization state
Figure 678264DEST_PATH_IMAGE039
Randomly selecting a number of consecutive sub-channels
Figure 252465DEST_PATH_IMAGE040
And unloading ratio
Figure 326600DEST_PATH_IMAGE041
The combined strategy is recorded as
Figure 87883DEST_PATH_IMAGE042
；
Step 6.2 in
Figure 39921DEST_PATH_IMAGE043
In the second iteration, a D2D pair is randomly selected
Figure 203049DEST_PATH_IMAGE009
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 448085DEST_PATH_IMAGE043
the number of iterations is indicated and,
Figure 696664DEST_PATH_IMAGE044
，
Figure 950928DEST_PATH_IMAGE045
is the maximum iteration number; divide D2D pairs in the network
Figure 234142DEST_PATH_IMAGE009
The set of policies for all but D2D pairs is
Figure 791025DEST_PATH_IMAGE046
；
Step 6.3, update D2D pairs
Figure 917113DEST_PATH_IMAGE009
Updating the policy according to equation (1):
Figure 584855DEST_PATH_IMAGE047
Figure 722575DEST_PATH_IMAGE048
wherein,
Figure 79388DEST_PATH_IMAGE049
for one of the federation policies that it tries at random,
Figure 568138DEST_PATH_IMAGE050
is based on
Figure 898625DEST_PATH_IMAGE051
The full network D2D of (2) for total energy consumption,
Figure 890852DEST_PATH_IMAGE052
is based on
Figure 55117DEST_PATH_IMAGE053
The whole network D2D pair total energy consumption.
Example 1
In order to intuitively explain the beneficial effects of the invention, the following simulation experiment is carried out on the method of the invention, Matlab software is adopted for system simulation, and the parameter setting does not influence the generality.
The simulation parameters are set as follows: there are 3D 2D pairs in a 300 x 300 network, each D2D pair is composed of 1 user with unloading requirement and 1 helper capable of providing operation service, the total unloading power of the users is 0.1W,the amount of data required to be processed is [0.1, 2 ]] ×106Randomly generated (bits), and the number of processor cycles required for each bit of data is 500, 1500]In the (A) random generation, the data processing time limit is 1 second, and the effective switched capacitances of the user and the helper are respectively 10-27And 10-29The fastest operation frequency of the user and the helper is 1.2 multiplied by 109And 3X 109(time/second), the total amount of frequency spectrum resources is 6MHz, and the frequency spectrum resources are divided into 6 continuous non-overlapping sub-channels, the bandwidth of each sub-channel is 1 MHz, and the background noise NO= 90dBm, the channel gain between user n and helper is
Figure 624639DEST_PATH_IMAGE055
Wherein d isnIs the physical distance between the two, fcFor the carrier frequency, the channel gain between user n and helper m is
Figure 493237DEST_PATH_IMAGE056
Wherein d isnIs the physical distance between the two. Network topology as shown in fig. 3, triangles represent users, dots represent helpers, solid lines between triangles and dots represent connection relationships inside pairs of D2D, and numbers represent serial numbers of pairs of D2D.
Based on the network environment shown in fig. 3, each pair of D2D performs a better response learning algorithm in a distributed manner, and the convergence effect is shown in fig. 4. The results shown are averaged from 500 independent simulations. It can be seen that the proposed algorithm is able to converge to a stable solution. In addition, compared with the operation unloading method based on isomorphic bandwidth non-overlapping channels, the method can save about 7% of energy.
The combination of simulation experiments shows that the distributed operation unloading method based on the variable bandwidth channel can save the energy consumption of the terminal. The energy saving reason is two: firstly, terminals with more unloading demands can use more spectrum resources, obtain higher transmission rate and shorter unloading time, and therefore unloading energy consumption is reduced; and secondly, the unloading time is shortened, so that the helper has more remote operation time, the remote operation can be performed at a lower frequency, and the operation energy consumption is reduced.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims (3)

1. A distributed operation unloading method based on a variable bandwidth channel is characterized by comprising the following steps:
step 1, the total bandwidth of the frequency spectrum in the network is
Figure 269556DEST_PATH_IMAGE001
Is divided into
Figure 255966DEST_PATH_IMAGE002
A plurality of non-overlapping sub-channels in series
Figure 421368DEST_PATH_IMAGE003
Each subchannel having a bandwidth of
Figure 767905DEST_PATH_IMAGE004
(ii) a Then
Figure 335152DEST_PATH_IMAGE005
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure 226885DEST_PATH_IMAGE006
A D2D pair, the set of which is
Figure 614004DEST_PATH_IMAGE007
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure 514964DEST_PATH_IMAGE008
The user and the helper in (1) are respectively recorded as the user
Figure 687450DEST_PATH_IMAGE009
And helpers
Figure 750084DEST_PATH_IMAGE009
User of
Figure 890079DEST_PATH_IMAGE009
The amount of data to be processed is
Figure 63571DEST_PATH_IMAGE010
The amount of data processed is
Figure 339832DEST_PATH_IMAGE010
The number of processor cycles required is
Figure 838946DEST_PATH_IMAGE011
All users in the network need to be in
Figure 455784DEST_PATH_IMAGE012
The data processing task is completed within a time period during which the user is
Figure 432967DEST_PATH_IMAGE009
Offloading portions of data to a helper
Figure 94893DEST_PATH_IMAGE009
Then help the person
Figure 499329DEST_PATH_IMAGE009
Performing remote operations while the user is simultaneously
Figure 348337DEST_PATH_IMAGE009
Performing local operation on the residual data in the whole process;
in the step 2, the step of mixing the raw materials,user' s
Figure 129211DEST_PATH_IMAGE009
Has a discharge ratio of
Figure 396375DEST_PATH_IMAGE013
Then its local operation frequency is
Figure 237292DEST_PATH_IMAGE014
With local computational power consumption of
Figure 573596DEST_PATH_IMAGE015
Wherein
Figure 892582DEST_PATH_IMAGE016
for the user
Figure 512788DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 3, the user
Figure 259027DEST_PATH_IMAGE009
Selecting a plurality of continuous sub-channels for operation unloading, wherein the total unloading power is
Figure 348206DEST_PATH_IMAGE017
Selected set of sub-channels as
Figure 205303DEST_PATH_IMAGE018
With an offloaded throughput of
Figure 696327DEST_PATH_IMAGE019
Wherein
Figure 613468DEST_PATH_IMAGE020
the number of sub-channels to select for it,
Figure 409517DEST_PATH_IMAGE021
for the user
Figure 70305DEST_PATH_IMAGE009
And helpers
Figure 415836DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 503878DEST_PATH_IMAGE022
in the case of background noise, the noise level,
Figure 36490DEST_PATH_IMAGE023
for its sub-channel
Figure 766549DEST_PATH_IMAGE024
Is subject to interference, wherein the user
Figure 215853DEST_PATH_IMAGE025
Is composed of
Figure 474796DEST_PATH_IMAGE006
D2D centering user
Figure 494705DEST_PATH_IMAGE009
Other than
Figure 762875DEST_PATH_IMAGE026
Any one of the users may be selected from the group of users,
Figure 817419DEST_PATH_IMAGE027
for the user
Figure 247263DEST_PATH_IMAGE025
The total power of the offload of (1),
Figure 505200DEST_PATH_IMAGE028
for the user
Figure 311482DEST_PATH_IMAGE025
The number of sub-channels to be selected,
Figure 220533DEST_PATH_IMAGE029
for the user
Figure 86857DEST_PATH_IMAGE025
And helpers
Figure 81358DEST_PATH_IMAGE009
The gain of the channel in between is increased,
Figure 206178DEST_PATH_IMAGE030
if D2D pairs
Figure 969735DEST_PATH_IMAGE025
Also operating on subchannels
Figure 6961DEST_PATH_IMAGE024
Upper, then it is paired with D2D
Figure 223178DEST_PATH_IMAGE009
Generate interference, users
Figure 636842DEST_PATH_IMAGE009
Is unloaded for a time of
Figure 254905DEST_PATH_IMAGE031
With a discharge energy consumption of
Figure 213765DEST_PATH_IMAGE032
；
Step 4, the helper
Figure 917279DEST_PATH_IMAGE009
The remote operation time is
Figure 134634DEST_PATH_IMAGE033
The remote operation frequency is
Figure 607203DEST_PATH_IMAGE034
The remote computing energy consumption is
Figure 986232DEST_PATH_IMAGE035
Wherein
Figure 442621DEST_PATH_IMAGE036
for the help of
Figure 175917DEST_PATH_IMAGE009
Effective switching capacitance of (1);
step 5, pair D2D
Figure 34151DEST_PATH_IMAGE009
Total energy consumed is
Figure 318502DEST_PATH_IMAGE037
Total energy consumption of the whole network D2D pair is
Figure 996608DEST_PATH_IMAGE038
；
And 6, realizing the minimization of the energy consumption of the whole network by a distributed operation unloading method through a better response learning algorithm.
2. The method of claim 1, wherein the optimal response learning algorithm in step 6 is as follows:
step 6.1, user in initialization state
Figure 555765DEST_PATH_IMAGE039
Randomly selecting a number of consecutive sub-channels
Figure 2927DEST_PATH_IMAGE040
And unloading ratio
Figure 474491DEST_PATH_IMAGE041
The combined strategy is recorded as
Figure 639893DEST_PATH_IMAGE042
；
Step 6.2 in
Figure 471583DEST_PATH_IMAGE043
In the second iteration, a D2D pair is randomly selected
Figure 38830DEST_PATH_IMAGE009
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 196142DEST_PATH_IMAGE043
the number of iterations is indicated and,
Figure 583261DEST_PATH_IMAGE044
，
Figure 467910DEST_PATH_IMAGE045
is the maximum iteration number; divide D2D pairs in the network
Figure 155243DEST_PATH_IMAGE009
The set of policies for all but D2D pairs is
Figure 217877DEST_PATH_IMAGE046
；
Step 6.3, update D2D pairs
Figure 92292DEST_PATH_IMAGE009
Updating the policy according to equation (1):
Figure 531363DEST_PATH_IMAGE047
Figure 807624DEST_PATH_IMAGE048
wherein,
Figure 791892DEST_PATH_IMAGE049
for one of the federation policies that it tries at random,
Figure 153603DEST_PATH_IMAGE050
is based on
Figure 396365DEST_PATH_IMAGE051
The full network D2D of (2) for total energy consumption,
Figure 527132DEST_PATH_IMAGE052
is based on
Figure 931569DEST_PATH_IMAGE053
The whole network D2D pair total energy consumption.
3. The method of claim 2, wherein the total network D2D is based on a corresponding joint strategy for total energy consumption
Figure 780576DEST_PATH_IMAGE054
To the whole net
Figure 76297DEST_PATH_IMAGE006
The individual pairs of D2D each calculate their energy consumed according to steps 2-5 and accumulate the energy consumption obtained.
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