CN113395684B - 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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CN113395684B
CN113395684B CN202110940450.9A CN202110940450A CN113395684B CN 113395684 B CN113395684 B CN 113395684B CN 202110940450 A CN202110940450 A CN 202110940450A CN 113395684 B CN113395684 B CN 113395684B
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pairs
pair
user
energy consumption
network
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CN113395684A (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

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 514840DEST_PATH_IMAGE001
Is divided into
Figure 123675DEST_PATH_IMAGE002
A plurality of non-overlapping sub-channels in series
Figure 828326DEST_PATH_IMAGE003
Each subchannel having a bandwidth of
Figure 573428DEST_PATH_IMAGE004
(ii) a Then
Figure 587390DEST_PATH_IMAGE005
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure 417942DEST_PATH_IMAGE006
A D2D pair, the set of which is
Figure 926284DEST_PATH_IMAGE007
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure 57051DEST_PATH_IMAGE008
The user and the helper in (1) are respectively marked as a D2D pair
Figure 930329DEST_PATH_IMAGE009
User and D2D pair
Figure 44916DEST_PATH_IMAGE009
Helper, D2D pair
Figure 294631DEST_PATH_IMAGE009
The amount of data that the user needs to process is
Figure 76643DEST_PATH_IMAGE010
The amount of data processed is
Figure 120822DEST_PATH_IMAGE010
The number of processor cycles required is
Figure 473437DEST_PATH_IMAGE011
All users in the network need to be in
Figure 526844DEST_PATH_IMAGE012
The data processing task is completed within the time during which the pair D2D
Figure 101045DEST_PATH_IMAGE009
The user unloads partial data to the D2D pair
Figure 378442DEST_PATH_IMAGE009
The helper is further paired with D2D
Figure 670883DEST_PATH_IMAGE009
The helper performs the remote operation with the D2D pairs
Figure 59139DEST_PATH_IMAGE009
The user performs local operation on the residual data in the whole process;
step 2, pair D2D
Figure 19005DEST_PATH_IMAGE009
The user's offload rate is
Figure 404987DEST_PATH_IMAGE013
Then its local operation frequency is
Figure 981462DEST_PATH_IMAGE014
With local computational power consumption of
Figure 111092DEST_PATH_IMAGE015
Wherein, in the step (A),
Figure 971469DEST_PATH_IMAGE016
is D2D pairs
Figure 528353DEST_PATH_IMAGE009
The effective switched capacitance coefficient of the user;
step 3, pair D2D
Figure 592124DEST_PATH_IMAGE009
The user selects a plurality of continuous sub-channels for operation unloading, and the total unloading power is
Figure 791024DEST_PATH_IMAGE017
Selected set of sub-channels as
Figure 194323DEST_PATH_IMAGE018
With an offloaded throughput of
Figure 984425DEST_PATH_IMAGE019
Wherein, in the step (A),
Figure 473175DEST_PATH_IMAGE020
the number of sub-channels to select for it,
Figure 272504DEST_PATH_IMAGE021
is D2D pairs
Figure 795889DEST_PATH_IMAGE009
User and D2D pair
Figure 694575DEST_PATH_IMAGE009
The gain of the channel between the helpers,
Figure 483670DEST_PATH_IMAGE022
in the case of background noise, the noise level,
Figure 758794DEST_PATH_IMAGE023
for its sub-channel
Figure 136686DEST_PATH_IMAGE024
Is subjected to interference, wherein D2D pairs
Figure 534169DEST_PATH_IMAGE025
The user is
Figure 731932DEST_PATH_IMAGE006
D2D pairs and D2D pairs
Figure 873063DEST_PATH_IMAGE009
Outside of the user
Figure 839882DEST_PATH_IMAGE026
Any one of the users may be selected from the group of users,
Figure 408267DEST_PATH_IMAGE027
is D2D pairs
Figure 358905DEST_PATH_IMAGE025
The total power of the offload by the user,
Figure 975832DEST_PATH_IMAGE028
is D2D pairs
Figure 374321DEST_PATH_IMAGE025
The number of sub-channels selected by the user,
Figure 51290DEST_PATH_IMAGE029
is D2D pairs
Figure 489224DEST_PATH_IMAGE025
User and D2D pair
Figure 972158DEST_PATH_IMAGE030
The gain of the channel between the helpers,
Figure 913569DEST_PATH_IMAGE031
if D2D pairs
Figure 823757DEST_PATH_IMAGE032
Also operating on subchannels
Figure 748987DEST_PATH_IMAGE024
Upper, then it is paired with D2D
Figure 707716DEST_PATH_IMAGE033
Producing interference, D2D pairs
Figure 831530DEST_PATH_IMAGE030
The user's unload time is
Figure 584722DEST_PATH_IMAGE034
With a discharge energy consumption of
Figure 544719DEST_PATH_IMAGE035
；
Step 4, pair D2D
Figure 307139DEST_PATH_IMAGE030
The remote operation time of the helper is
Figure 488721DEST_PATH_IMAGE036
The remote operation frequency is
Figure 740711DEST_PATH_IMAGE037
The remote computing energy consumption is
Figure 109376DEST_PATH_IMAGE038
Wherein, in the step (A),
Figure 737803DEST_PATH_IMAGE039
is D2D pairs
Figure 39471DEST_PATH_IMAGE030
The effective switched capacitance coefficient of the helper;
step 5, pair D2D
Figure 729208DEST_PATH_IMAGE033
Total energy consumed is
Figure 585169DEST_PATH_IMAGE040
Total energy consumption of the whole network D2D pair is
Figure 751708DEST_PATH_IMAGE041
；
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 Better Reply.
Further, the preferred response learning algorithm Better Reply described in step 6 specifically includes the following steps:
step 6.1, in the initialization state, D2D pairs
Figure 642303DEST_PATH_IMAGE009
User' s
Figure 236096DEST_PATH_IMAGE042
Randomly selecting a number of consecutive sub-channels
Figure 844932DEST_PATH_IMAGE043
And unloading ratio
Figure 487266DEST_PATH_IMAGE044
The combined strategy is recorded as
Figure 294685DEST_PATH_IMAGE045
；
Step 6.2 in
Figure 997061DEST_PATH_IMAGE046
In the second iteration, a D2D pair is randomly selected
Figure 93193DEST_PATH_IMAGE033
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 352268DEST_PATH_IMAGE046
the number of iterations is indicated and,
Figure 951876DEST_PATH_IMAGE047
，
Figure 887471DEST_PATH_IMAGE048
is the maximum iteration number; divide D2D pairs in the network
Figure 470899DEST_PATH_IMAGE033
The set of policies for all but D2D pairs is
Figure 517353DEST_PATH_IMAGE049
；
Step 6.3, update D2D pairs
Figure 971468DEST_PATH_IMAGE033
Updating the policy according to equation (1):
Figure 281226DEST_PATH_IMAGE050
Figure 148688DEST_PATH_IMAGE051
wherein the content of the first and second substances,
Figure 936516DEST_PATH_IMAGE052
for one of the federation policies that it tries at random,
Figure 822301DEST_PATH_IMAGE053
is based on
Figure 37382DEST_PATH_IMAGE054
The full network D2D of (2) for total energy consumption,
Figure 392139DEST_PATH_IMAGE055
is based on
Figure 983658DEST_PATH_IMAGE056
The whole network D2D pair total energy consumption.
Further, the whole network D2D has the corresponding joint strategy for the total energy consumption
Figure 412365DEST_PATH_IMAGE057
To the whole net
Figure 126243DEST_PATH_IMAGE006
The individual pairs of D2D each calculate their energy consumed according to steps 2-5 and accumulate the energy consumption obtained.
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, the user can share spectrum resources according to conditions such as network topology and the like, the frequency utilization mode is more flexible, and the communication performance can be improved.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
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 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 640401DEST_PATH_IMAGE001
Is divided into
Figure 832348DEST_PATH_IMAGE002
A plurality of non-overlapping sub-channels in series
Figure 381141DEST_PATH_IMAGE003
Each subchannel having a bandwidth of
Figure 751074DEST_PATH_IMAGE004
(ii) a Then
Figure 18107DEST_PATH_IMAGE005
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure 951428DEST_PATH_IMAGE006
A D2D pair, the set of which is
Figure 417044DEST_PATH_IMAGE007
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure 144829DEST_PATH_IMAGE008
The user and the helper in (1) are respectively marked as a D2D pair
Figure 695896DEST_PATH_IMAGE009
User and D2D pair
Figure 167329DEST_PATH_IMAGE009
Helper, D2D pair
Figure 690714DEST_PATH_IMAGE009
The amount of data that the user needs to process is
Figure 917296DEST_PATH_IMAGE010
The amount of data processed is
Figure 893342DEST_PATH_IMAGE010
The number of processor cycles required is
Figure 214471DEST_PATH_IMAGE011
All users in the network need to be in
Figure 592363DEST_PATH_IMAGE012
The data processing task is completed within the time during which the pair D2D
Figure 724267DEST_PATH_IMAGE009
The user unloads partial data to the D2D pair
Figure 187609DEST_PATH_IMAGE009
The helper is further paired with D2D
Figure 266423DEST_PATH_IMAGE009
The helper performs the remote operation with the D2D pairs
Figure 561139DEST_PATH_IMAGE009
The user performs local operation on the residual data in the whole process;
step 2, pair D2D
Figure 67206DEST_PATH_IMAGE009
The user's offload rate is
Figure 814582DEST_PATH_IMAGE013
Then its local operation frequency is
Figure 431509DEST_PATH_IMAGE014
With local computational power consumption of
Figure 331463DEST_PATH_IMAGE015
Wherein, in the step (A),
Figure 8432DEST_PATH_IMAGE016
is D2D pairs
Figure 446366DEST_PATH_IMAGE009
The effective switched capacitance coefficient of the user;
step 3, pair D2D
Figure 663721DEST_PATH_IMAGE009
The user selects a plurality of continuous sub-channels for operation unloading, and the total unloading power is
Figure 870711DEST_PATH_IMAGE017
Selected set of sub-channels as
Figure 780898DEST_PATH_IMAGE018
With an offloaded throughput of
Figure 440550DEST_PATH_IMAGE019
Wherein, in the step (A),
Figure 664858DEST_PATH_IMAGE020
the number of sub-channels to select for it,
Figure 523092DEST_PATH_IMAGE021
is D2D pairs
Figure 541864DEST_PATH_IMAGE009
User and D2D pair
Figure 396DEST_PATH_IMAGE009
The gain of the channel between the helpers,
Figure 762816DEST_PATH_IMAGE022
in the case of background noise, the noise level,
Figure 944398DEST_PATH_IMAGE023
for its sub-channel
Figure 930809DEST_PATH_IMAGE024
Is subjected to interference, wherein D2D pairs
Figure 565053DEST_PATH_IMAGE025
The user is
Figure 927901DEST_PATH_IMAGE006
D2D pairs and D2D pairs
Figure 229569DEST_PATH_IMAGE009
Outside of the user
Figure 324564DEST_PATH_IMAGE026
Any one of the users may be selected from the group of users,
Figure 508421DEST_PATH_IMAGE027
is D2D pairs
Figure 612643DEST_PATH_IMAGE025
The total power of the offload by the user,
Figure 50709DEST_PATH_IMAGE028
is D2D pairs
Figure 847763DEST_PATH_IMAGE025
The number of sub-channels selected by the user,
Figure 191020DEST_PATH_IMAGE029
is D2D pairs
Figure 161250DEST_PATH_IMAGE025
User and D2D pair
Figure 906352DEST_PATH_IMAGE009
The gain of the channel between the helpers,
Figure 671046DEST_PATH_IMAGE031
if D2D pairs
Figure 767178DEST_PATH_IMAGE032
Also operating on subchannels
Figure 213203DEST_PATH_IMAGE024
Upper, then it is paired with D2D
Figure 875128DEST_PATH_IMAGE033
Producing interference, D2D pairs
Figure 748406DEST_PATH_IMAGE009
The user's unload time is
Figure 331834DEST_PATH_IMAGE034
With a discharge energy consumption of
Figure 367836DEST_PATH_IMAGE035
；
Step 4, pair D2D
Figure 353109DEST_PATH_IMAGE030
The remote operation time of the helper is
Figure 459605DEST_PATH_IMAGE036
The remote operation frequency is
Figure 264750DEST_PATH_IMAGE037
The remote computing energy consumption is
Figure 114895DEST_PATH_IMAGE038
Wherein, in the step (A),
Figure 954675DEST_PATH_IMAGE039
is D2D pairs
Figure 169755DEST_PATH_IMAGE030
The effective switched capacitance coefficient of the helper;
step 5, pair D2D
Figure 258934DEST_PATH_IMAGE033
Total energy consumed is
Figure 850452DEST_PATH_IMAGE040
Total energy consumption of the whole network D2D pair is
Figure 92209DEST_PATH_IMAGE041
；
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 Better Reply, which comprises the following specific steps:
step 6.1, in the initialization state, D2D pairs
Figure 743770DEST_PATH_IMAGE030
User' s
Figure 523507DEST_PATH_IMAGE042
Randomly selecting a number of consecutive sub-channels
Figure 715454DEST_PATH_IMAGE043
And unloading ratio
Figure 998668DEST_PATH_IMAGE044
The combined strategy is recorded as
Figure 883448DEST_PATH_IMAGE045
；
Step 6.2 in
Figure 884902DEST_PATH_IMAGE046
In the second iteration, a D2D pair is randomly selected
Figure 880539DEST_PATH_IMAGE033
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 283839DEST_PATH_IMAGE046
the number of iterations is indicated and,
Figure 277203DEST_PATH_IMAGE047
，
Figure 77537DEST_PATH_IMAGE048
is the maximum iteration number; divide D2D pairs in the network
Figure 548970DEST_PATH_IMAGE033
The set of policies for all but D2D pairs is
Figure 869093DEST_PATH_IMAGE049
；
Step 6.3, updateD2D pairs
Figure 298937DEST_PATH_IMAGE033
Updating the policy according to equation (1):
Figure 9404DEST_PATH_IMAGE050
Figure 346845DEST_PATH_IMAGE051
wherein the content of the first and second substances,
Figure 724736DEST_PATH_IMAGE052
for one of the federation policies that it tries at random,
Figure 856640DEST_PATH_IMAGE053
is based on
Figure 585562DEST_PATH_IMAGE054
The full network D2D of (2) for total energy consumption,
Figure 398797DEST_PATH_IMAGE055
is based on
Figure 444245DEST_PATH_IMAGE056
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 300m × 300m 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 user is 0.1W, and the data amount 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 step (A), the random generation is carried out, the data processing time limit is 1 second, and the effective switching capacitance coefficients of a user and a 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 1MHz, and the background noise N0= 90dBm, D2D pair
Figure 684733DEST_PATH_IMAGE030
User and D2D pair
Figure 697689DEST_PATH_IMAGE030
The channel gain between helpers is
Figure 580194DEST_PATH_IMAGE058
Where dn is the physical distance between the two, fc is the carrier frequency, and the channel gain between the user of D2D for n and the helper of D2D for m is
Figure 667099DEST_PATH_IMAGE059
Wherein dnm is 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 executes the Better response learning algorithm Better Reply 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 DEST_PATH_IMAGE002
Is divided into
Figure DEST_PATH_IMAGE004
A plurality of non-overlapping sub-channels in series
Figure DEST_PATH_IMAGE006
Each subchannel having a bandwidth of
Figure DEST_PATH_IMAGE008
(ii) a Then
Figure DEST_PATH_IMAGE010
Any variable bandwidth channel is composed of a plurality of continuous non-overlapping sub-channels, and the total is
Figure DEST_PATH_IMAGE012
A D2D pair, the set of which is
Figure DEST_PATH_IMAGE014
A D2D pair containing a user with uninstalling requirement and a helper providing calculation service, and D2D pair
Figure DEST_PATH_IMAGE016
The user and the helper in (1) are respectively marked as a D2D pair
Figure DEST_PATH_IMAGE018
User and D2D pair
Figure 343029DEST_PATH_IMAGE018
Helper, D2D pair
Figure 729011DEST_PATH_IMAGE018
The amount of data that the user needs to process is
Figure DEST_PATH_IMAGE020
The amount of data processed is
Figure 712011DEST_PATH_IMAGE020
The number of processor cycles required is
Figure DEST_PATH_IMAGE022
All users in the network need to be in
Figure DEST_PATH_IMAGE024
The data processing task is completed within the time during which the pair D2D
Figure 215542DEST_PATH_IMAGE018
The user unloads partial data to the D2D pair
Figure 498756DEST_PATH_IMAGE018
The helper is further paired with D2D
Figure 790060DEST_PATH_IMAGE018
The helper performs the remote operation with the D2D pairs
Figure 791514DEST_PATH_IMAGE018
The user performs local operation on the residual data in the whole process;
step (ii) of2, D2D pairs
Figure 459256DEST_PATH_IMAGE018
The user's offload rate is
Figure DEST_PATH_IMAGE026
Then its local operation frequency is
Figure DEST_PATH_IMAGE028
With local computational power consumption of
Figure DEST_PATH_IMAGE030
Wherein, in the step (A),
Figure DEST_PATH_IMAGE032
is D2D pairs
Figure 439719DEST_PATH_IMAGE018
The effective switched capacitance coefficient of the user;
step 3, pair D2D
Figure 901924DEST_PATH_IMAGE018
The user selects a plurality of continuous sub-channels for operation unloading, and the total unloading power is
Figure DEST_PATH_IMAGE034
Selected set of sub-channels as
Figure DEST_PATH_IMAGE036
With an offloaded throughput of
Figure DEST_PATH_IMAGE038
Wherein, in the step (A),
Figure DEST_PATH_IMAGE040
the number of sub-channels to select for it,
Figure DEST_PATH_IMAGE042
is D2D pairs
Figure 454258DEST_PATH_IMAGE018
User and D2D pair
Figure 660111DEST_PATH_IMAGE018
The gain of the channel between the helpers,
Figure DEST_PATH_IMAGE044
in the case of background noise, the noise level,
Figure DEST_PATH_IMAGE046
for its sub-channel
Figure DEST_PATH_IMAGE048
Is subjected to interference, wherein D2D pairs
Figure DEST_PATH_IMAGE050
The user is
Figure 229502DEST_PATH_IMAGE012
D2D pairs and D2D pairs
Figure 128188DEST_PATH_IMAGE018
Outside of the user
Figure DEST_PATH_IMAGE052
Any one of the users may be selected from the group of users,
Figure DEST_PATH_IMAGE054
is D2D pairs
Figure 41917DEST_PATH_IMAGE050
The total power of the offload by the user,
Figure DEST_PATH_IMAGE056
is D2D pairs
Figure 956521DEST_PATH_IMAGE050
The number of sub-channels selected by the user,
Figure DEST_PATH_IMAGE058
is D2D pairs
Figure 803254DEST_PATH_IMAGE050
User and D2D pair
Figure 607262DEST_PATH_IMAGE018
The gain of the channel between the helpers,
Figure DEST_PATH_IMAGE060
if D2D pairs
Figure DEST_PATH_IMAGE062
Also operating on subchannels
Figure 444506DEST_PATH_IMAGE048
Upper, then it is paired with D2D
Figure DEST_PATH_IMAGE064
Producing interference, D2D pairs
Figure 726583DEST_PATH_IMAGE018
The user's unload time is
Figure DEST_PATH_IMAGE066
With a discharge energy consumption of
Figure DEST_PATH_IMAGE068
；
Step 4, pair D2D
Figure 631085DEST_PATH_IMAGE018
The remote operation time of the helper is
Figure DEST_PATH_IMAGE070
The remote operation frequency is
Figure DEST_PATH_IMAGE072
The remote computing energy consumption is
Figure DEST_PATH_IMAGE074
Wherein, in the step (A),
Figure DEST_PATH_IMAGE076
is D2D pairs
Figure 126700DEST_PATH_IMAGE018
The effective switched capacitance coefficient of the helper;
step 5, pair D2D
Figure 546180DEST_PATH_IMAGE064
Total energy consumed is
Figure DEST_PATH_IMAGE078
Total energy consumption of the whole network D2D pair is
Figure DEST_PATH_IMAGE080
；
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 Better Reply.
2. The distributed operation offloading method based on variable bandwidth channel according to claim 1, wherein the Better response learning algorithm Better Reply in step 6 is as follows:
step 6.1, in the initialization state, D2D pairs
Figure 802587DEST_PATH_IMAGE018
User' s
Figure DEST_PATH_IMAGE082
Randomly selecting a number of consecutive sub-channels
Figure DEST_PATH_IMAGE084
And unloading ratio
Figure DEST_PATH_IMAGE086
The combined strategy is recorded as
Figure DEST_PATH_IMAGE088
；
Step 6.2 in
Figure DEST_PATH_IMAGE090
In the second iteration, a D2D pair is randomly selected
Figure 247081DEST_PATH_IMAGE064
Policy updates are made and the remaining pairs of D2D remain current, where,
Figure 861734DEST_PATH_IMAGE090
the number of iterations is indicated and,
Figure DEST_PATH_IMAGE092
，
Figure DEST_PATH_IMAGE094
is the maximum iteration number; divide D2D pairs in the network
Figure 643876DEST_PATH_IMAGE064
The set of policies for all but D2D pairs is
Figure DEST_PATH_IMAGE096
；
Step 6.3, update D2D pairs
Figure 432535DEST_PATH_IMAGE064
Updating the policy according to equation (1):
Figure DEST_PATH_IMAGE098
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE100
for one of the federation policies that it tries at random,
Figure DEST_PATH_IMAGE102
is based on
Figure DEST_PATH_IMAGE104
The full network D2D of (2) for total energy consumption,
Figure DEST_PATH_IMAGE106
is based on
Figure DEST_PATH_IMAGE108
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 DEST_PATH_IMAGE110
For the whole network of D2D pairs, the consumed energy is calculated according to steps 2-5 respectively, and the obtained energy consumption is accumulated.
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