CN114786194A - Fog access point range expansion bias and transmission power combined adjustment method - Google Patents

Fog access point range expansion bias and transmission power combined adjustment method Download PDF

Info

Publication number
CN114786194A
CN114786194A CN202210285725.4A CN202210285725A CN114786194A CN 114786194 A CN114786194 A CN 114786194A CN 202210285725 A CN202210285725 A CN 202210285725A CN 114786194 A CN114786194 A CN 114786194A
Authority
CN
China
Prior art keywords
access point
power
value
iteration
fog
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210285725.4A
Other languages
Chinese (zh)
Inventor
蒋慧琳
李旋
许彩云
宋翔
李玲
李丽萍
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing Xiaozhuang University
Original Assignee
Nanjing Xiaozhuang University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing Xiaozhuang University filed Critical Nanjing Xiaozhuang University
Priority to CN202210285725.4A priority Critical patent/CN114786194A/en
Publication of CN114786194A publication Critical patent/CN114786194A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/06—TPC algorithms

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a method for jointly adjusting range expansion bias and transmission power of a fog access point, which comprises the following steps: constructing and initializing a fog access network; defining a system energy utility function; the user selects a service cell according to the maximum offset received power; calculating the utility of the initial system; adjusting a range expansion offset value of the fog access point through simulated annealing; dynamically adjusting the sending power of the fog access point through simulated annealing; and setting the offset value and the transmission power of each fog access point to obtain a system energy value. The invention can optimize the range expansion offset value and the sending power of the fog access point with lower complexity, and realize the purpose of improving the system energy efficiency; the invention can obtain the optimal solution of the system energy utility function by adjusting the range expansion bias and the transmission power of each fog access point.

Description

Fog access point range expansion bias and transmission power combined adjustment method
Technical Field
The invention relates to a wireless access technology in mobile communication, in particular to a method for jointly adjusting range expansion bias and transmission power of a fog access point.
Background
The 5G broadband wireless communication technology is widely accepted as the most advanced mobile communication technology at present by virtue of its characteristics of high rate, low time delay, high reliability and low power consumption. Under the pressure of ever-increasing mobile network service demands, mobile operators firstly satisfy user demands in a cell splitting manner by establishing new base stations, however, the deployment manner based on cell splitting brings huge network deployment cost pressure to the operators. In this case, a cloud radio access network (C-RAN) architecture and a heterogeneous cloud radio access network (H-CRAN) architecture are successively emerging. The C-RAN combines the advantages of cloud computing and a wireless access network, has the characteristics of centralization, clouding and cooperation, not only reduces the network operation and deployment cost, but also realizes information sharing, but also has the problem of limited network capacity due to the limitation of the capacity of a fronthaul link. The H-CRAN combines the advantages of a heterogeneous network and the advantages of the C-RAN, establishes connection between the conventional high-power node (HPN) and a BBU pool, realizes function separation of a control plane and a service plane, and has the problem of limitation of a forward link. In order to relieve the overhead of a forward link, fog calculation, HPN and C-RAN are combined, a fog radio access network (F-RAN) architecture is proposed, and the pressure of the forward link and the cloud calculation and service pressure are relieved by utilizing special calculation and storage functions of a user and edge network equipment.
Disclosure of Invention
The invention aims to: the invention aims to provide a method for jointly adjusting range expansion bias and transmission power of a fog access point, so that the range expansion bias value and the transmission power of the fog access point are optimized with low complexity, and the energy efficiency of a system is improved.
The technical scheme is as follows: the invention relates to a method for jointly adjusting range expansion bias and transmission power of a fog access point, which comprises the following steps of:
(1) initializing a network, setting a macro cell, a fog access point and a user in the network, initializing range expansion bias, sending power and iteration times, and initializing a service cell of the user;
(2) defining a system energy utility function;
(3) the user selects a service cell according to the maximum offset received power;
(4) calculating the user reachable rate and further calculating the system utility;
(5) fixing the transmission power set of all the fog access points, and updating the bias value of the fog access point l by using simulated annealing;
(6) fixing the bias value sets of all the fog access points, and updating the transmission power of the fog access point l by using simulated annealing;
(7) and (5) changing the target fog access point, repeating the steps (5) to (6), respectively updating the bias value and the transmission power of the target fog access point by using simulated annealing, stopping iteration until a stopping condition is met, setting the bias value and the transmission power of each fog access point, and obtaining a final system energy value by using a system energy utility function formula.
The step (1) is specifically as follows:
(1.1) assuming that the system has M macro cells, L fog access points and K users in total, and the macro cell set is recorded as
Figure BDA0003559836820000021
Set of fog access points
Figure BDA0003559836820000022
The macro cell and the fog access point are collectively called as a cell, and the set of all cells is denoted as
Figure BDA0003559836820000023
Wherein, U represents the union of two sets, and the user set is recorded as
Figure BDA0003559836820000024
(1.2) only the fog access point can change the user service cell by adjusting the range expansion bias, and further jointly transmit power adjustment optimizes network utility, and any fog access point
Figure BDA0003559836820000025
Available range extension bias ofAre collected into
Figure BDA0003559836820000026
Wherein b isminTo minimum bias, bmaxΔ is the offset interval, defined by the operator, for maximum offset; range extension biasing of arbitrary macrocells m
Figure BDA0003559836820000027
(1.3) to ensure coverage, each macrocell m uses a maximum transmission power PmaxA downlink signal is sent, and the fog access point can dynamically change and adjust the sending power of the downlink signal so as to improve the network performance;
(1.4) definition of Δp＝Pl max/(Np-1) is a power interval, wherein NpFor the power class number, the available transmission power of any fog access point is PL＝{0,1·Δp,2·Δp,....,Pl maxAnd b, the range expansion bias of the fog recording access point l is set aslWith a transmission power of PlThe range expansion bias set of all the fog access points is b, and the transmission power set of all the fog access points is P;
(1.5) Range extension bias for any fog Access Point l at initialization
Figure BDA0003559836820000028
Transmission power
Figure BDA0003559836820000029
Wherein P isl maxMaximum transmit power for the mist access point l;
(1.6) user k receives from cell
Figure BDA0003559836820000031
Is recorded as the received signal power
Figure BDA0003559836820000032
During initialization, each user selects the cell with the maximum received signal power as the initial serving cell, and the service of user kCell is marked as Sk；
(1.7) defining the number of external iterations toutNumber of iterations of offset value tbNumber of iterations of power value tpAt initialization, tout＝tb＝tp＝0。
The step (2) is specifically as follows: firstly, defining throughput T of system, i.e. T is reachable rate R of all users kkThe sum of (a) and (b),
Figure BDA0003559836820000033
the utility function of the system is
Figure BDA0003559836820000034
Wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003559836820000035
is the total power loss of the fog access point.
The step (3) is specifically as follows: by PcIndicating the transmission power, G, of cell cc,kRepresenting the average channel gain between cell c and user k, the received signal power
Figure BDA0003559836820000036
User k selects serving cell S according to maximum offset post-received power criterionkTherefore, it is possible to
Figure BDA0003559836820000037
I.e. user k selects the received signal power plus offset value in all cells
Figure BDA0003559836820000038
The largest cell is used as the serving cell; range extension bias for any fog access point l at initialization
Figure BDA0003559836820000039
Therefore, each user selects the cell with the maximum received signal power as the initial serving cell during initialization.
The step (4) is specifically as follows: in the optimization process, the serving cell of the user followsThe change of the transmission power is changed when the serving cell of user k is SkWhen the ue receives a received signal to interference plus noise ratio from the serving cell, the received signal to interference plus noise ratio is:
Figure BDA00035598368200000310
wherein the content of the first and second substances,
Figure BDA00035598368200000311
indicating the serving cell SkAverage channel gain with user k, N0Is the noise power value; according to the shannon formula, the achievable rate of user k is:
Rk＝Wk log(1+γk)
wherein, WkIs the bandwidth of user k; the system utility is defined as the system energy utility, and the function can be specifically written as:
Figure BDA0003559836820000041
where T is the system throughput and the energy utility H depends on the serving cell of the user and the transmit power of each cell, so H is a function of the set of mist access point range extension bias values and the set of mist access point transmit powers, which can be written as H (b, P).
The step (5) is specifically as follows:
(5.1) first, the maximum number of iterations of the offset value is set
Figure BDA0003559836820000042
Selecting a current target fog access point l, and setting an offset value initial temperature parameter for offset value adjustment
Figure BDA0003559836820000043
Coefficient of temperature displacement
Figure BDA0003559836820000044
Coefficient of temperature drop
Figure BDA0003559836820000045
Calculating the current offset value according to the initial temperature parameter of the offset value and the temperature drop coefficient to adjust the potential temperature
Figure BDA0003559836820000046
Figure BDA0003559836820000047
(5.2) by
Figure BDA0003559836820000048
Determining an average displacement distance of offset values at a current potential temperature
Figure BDA0003559836820000049
Figure BDA00035598368200000410
By tbRepresenting the number of iterations corresponding to the iteration of the offset value, i.e. the number of iterations of the current offset value, t at the time of the first iterationbThe potential offset displacement value of the mist access point l is iterated this time as 0
Figure BDA00035598368200000411
Comprises the following steps:
Figure BDA00035598368200000412
wherein randn is a randomly generated [ -1,1 ] centered at 0]Random numbers within the interval that satisfy a normal distribution,
Figure BDA00035598368200000413
to average displacement distance by offset value
Figure BDA00035598368200000414
Is a central random offset value satisfying a normal distribution of]Representing rounding;
(5.3) the potential bias values obtained by the cell l in this iteration are:
Figure BDA00035598368200000415
wherein, bl(tb-) is the previous bias value iteration for the fog access point l (i.e., the t-thb-1 iteration) of the obtained offset value, tbWhen equal to 0, bl(tb-) 0, increase
Figure BDA00035598368200000416
And reduction of
Figure BDA00035598368200000417
All have a probability of 50%, the symbol x]→BMeans for mapping the value of x to the closest bias value to x in the set of available range extension biases B;
(5.4) note the tbSet of potential bias values for all mist access points for a sub-iteration of
Figure BDA0003559836820000051
Wherein
Figure BDA0003559836820000052
The set formed by the offset values of all mist access points except the mist access point l is demisted for the previous iteration, and the set formed by the offset values of all mist access points in the previous iteration is recorded as b (t)b-) then the principle of updating the bias value of the fog access point l for this iteration is:
Figure BDA0003559836820000053
i.e. the set of potential bias values b obtained only at this iterationtemp(tb) Corresponding system energy value H (b)temp(tb) System energy efficiency greater than that of the previous iterationValue H (b (t)b-) of the cloud, iterate this round over the bias value b for the fog access pointl(tb) According to the following
Figure BDA0003559836820000054
Setting;
(5.5) updating tb＝tb+1, update
Figure BDA0003559836820000055
And
Figure BDA0003559836820000056
starting the next iteration to obtain a new iteration
Figure BDA0003559836820000057
And bl(tb) Updating the offset value of the fog access point l according to an offset value updating principle;
(5.6) continuing the iteration until the number of iterations
Figure BDA0003559836820000058
Or bl(tb) The times of keeping unchanged is larger than a preset bias iteration threshold value xibAnd stopping updating the offset value of the fog access point l, and recording the offset value set of all the fog access points as b at the moment.
The step (6) is specifically as follows:
(6.1) first, the number of iterations of the maximum power value is set
Figure BDA0003559836820000059
Setting initial temperature parameters for power regulation
Figure BDA00035598368200000510
Coefficient of temperature displacement
Figure BDA00035598368200000511
Coefficient of temperature drop
Figure BDA00035598368200000512
According to the use for power regulationCalculating the potential temperature of the current power adjustment according to the initial temperature parameter and the temperature drop coefficient
Figure BDA00035598368200000513
Figure BDA00035598368200000514
(6.2) by
Figure BDA00035598368200000515
Determining the average displacement distance of the power value under the current potential temperature
Figure BDA00035598368200000516
Figure BDA00035598368200000517
By tpRepresenting the number of iterations corresponding to the power iteration (i.e. the current number of power iterations, t at the time of the first iteration)p0), this iteration of the potential power shift value of the fog access point/
Figure BDA00035598368200000518
Comprises the following steps:
Figure BDA0003559836820000061
Figure BDA0003559836820000062
is the average distance of displacement of power values
Figure BDA0003559836820000063
A random power shift value centered to satisfy a normal distribution;
(6.3) the potential power value obtained by the mist access point l in this iteration is:
Figure BDA0003559836820000064
wherein, Pl(tp-) is the previous power iteration (i.e., tth) for the fog access point lp-1 iteration) of the obtained power value, tpWhen equal to 0, Pl(tp-)＝Pl maxIncrease of
Figure BDA0003559836820000065
And reduction of
Figure BDA0003559836820000066
All probabilities of being 50%, sign
Figure BDA0003559836820000067
Means for mapping the value of x to the set of available transmit powers PLThe one power value closest to the value of x;
(6.4) note tpSet of potential power values for all mist access points for a sub-iteration of
Figure BDA00035598368200000612
Wherein
Figure BDA00035598368200000613
The power values of all the fog access points except the fog access point l are set for the previous iteration, and the set formed by the power values of all the fog access points in the previous iteration is recorded as P (t)p-) then the power value updating principle of the iteration fog access point l is:
Figure BDA0003559836820000068
i.e. the set P of potential power values obtained only at this iterationtemp(tp) Corresponding system energy value H (P)temp(tp) Is greater than the system effective value H (P (t)) corresponding to the previous iterationp-) of the power value P of the iterative mist access point ll(tp) According to Pl temp(tp) Setting;
(6.5) updating tp＝tp+1, update
Figure BDA0003559836820000069
And
Figure BDA00035598368200000610
starting the next iteration to obtain new Pl temp(tp) And Pl(tp) Updating the power value of the fog access point l according to a power value updating principle;
(6.6) iterating repeatedly until the number of iterations
Figure BDA00035598368200000611
Or Pl(tp) The times of keeping unchanged is larger than a preset power iteration threshold value xipAnd stopping updating the power value of the fog access point l, and recording the power value set of all the fog access points as P at the moment.
The step (7) is specifically as follows: by tout＝tout+1 updating external iteration times, changing the target fog access point, and repeating the steps (5) to (6), namely respectively updating the bias value and the transmission power of the target fog access point by using simulated annealing until the external iteration times toutGreater than or equal to a preset external iteration threshold value
Figure BDA0003559836820000071
Or stopping external iteration when the times that the fog access point bias value and power value sets b and P are kept unchanged in the iteration process are larger than a threshold eta, setting the bias value and the sending power of each fog access point according to the finally obtained fog access point bias value set b and power value set P, and obtaining a final system energy effective value H by using a system energy utility function formula.
A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method of jointly adjusting mist access point range extension bias and transmit power as described above.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing a mist access point range extension biasing and transmit power joint adjustment method as described above.
Has the beneficial effects that: compared with the prior art, the invention has the following advantages:
1. the invention can optimize the range expansion offset value and the sending power of the fog access point with lower complexity, and realize the purpose of improving the energy efficiency of the system;
2. the invention can obtain the optimal solution of the system energy utility function by adjusting the range expansion bias and the transmission power of each fog access point.
Drawings
FIG. 1 is a flow chart of the steps of the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in fig. 1, a method for jointly adjusting the range expansion bias and the transmission power of a fog access point includes the following steps:
(1) initializing a network, setting a macro cell, a fog access point and a user in the network, initializing range expansion bias, sending power and iteration times, and initializing a service cell of the user;
(2) defining a system energy utility function;
(3) the user selects a service cell according to the maximum offset received power;
(4) calculating the user reachable rate and further calculating the system utility;
(5) fixing the transmission power set of all the fog access points, and updating the bias value of the fog access point l by using simulated annealing;
(6) fixing the bias value sets of all the fog access points, and updating the transmission power of the fog access point l by using simulated annealing;
(7) and (5) changing the target fog access point, repeating the steps (5) to (6), respectively updating the bias value and the transmission power of the target fog access point by using simulated annealing, stopping iteration until a stopping condition is met, setting the bias value and the transmission power of each fog access point, and obtaining a final system energy value by using a system energy utility function formula.
The step (1) is specifically as follows:
(1.1) assuming that the system has M macro cells, L fog access points and K users in total, and the macro cell set is recorded as
Figure BDA0003559836820000081
Set of fog access points
Figure BDA0003559836820000082
The macro cell and the fog access point are collectively called as a cell, and the set of all cells is denoted as
Figure BDA0003559836820000083
Wherein, U represents the union of two sets, and the user set is recorded as
Figure BDA0003559836820000084
(1.2) only the fog access point can change the user service cell by adjusting the range expansion bias, and further jointly transmit power adjustment optimizes network utility, and any fog access point
Figure BDA0003559836820000085
Is a set of available range extension biases of
Figure BDA0003559836820000086
Wherein b isminTo minimum bias, bmaxΔ is the offset interval, defined by the operator, for maximum offset; range extension biasing for arbitrary macro cell m
Figure BDA0003559836820000087
(1.3) to ensure coverage, each macrocell m uses a maximum transmission power PmaxA downlink signal is sent, and the fog access point can dynamically change and adjust the sending power of the downlink signal so as to improve the network performance;
(1.4) definition of Δp＝Pl max/(Np-1) is a power interval, wherein NpFor the power class number, the available transmission power of any fog access point is PL＝{0,1·Δp,2·Δp,....,Pl maxB, the range expansion bias of the fog recording access point l is set aslWith a transmission power of PlThe range expansion bias set of all the fog access points is b, and the transmission power set of all the fog access points is P;
(1.5) Range extension bias for any fog Access Point l at initialization
Figure BDA0003559836820000088
Transmission power
Figure BDA0003559836820000089
Wherein P isl maxMaximum transmit power for the mist access point l;
(1.6) user k received from cell
Figure BDA00035598368200000810
Is recorded as the received signal power
Figure BDA00035598368200000811
During initialization, each user selects the cell with the maximum received signal power as the initial serving cell, and the serving cell of user k is marked as Sk；
(1.7) defining the number of external iterations toutBias value iteration number tbNumber of iterations of power value tpAt initialization, tout＝tb＝tp＝0。
The step (2) is specifically as follows: firstly, defining the throughput T of the system, namely T is the reachable rate R of all users kkThe sum of (a) and (b),
Figure BDA0003559836820000091
the utility function of the system is
Figure BDA0003559836820000092
Wherein the content of the first and second substances,
Figure BDA0003559836820000093
is the total power loss of the fog access point.
The step (3) is specifically as follows: by PcIndicating the transmission power of cell c, Gc,kRepresenting the average channel gain between cell c and user k, the received signal power
Figure BDA0003559836820000094
User k selects serving cell S according to maximum offset post-received power criterionkTherefore, it is possible to
Figure BDA0003559836820000095
I.e. user k selects the received signal power plus offset value in all cells
Figure BDA0003559836820000096
The largest cell is taken as the serving cell; range extension bias for any fog access point l at initialization
Figure BDA0003559836820000097
Therefore, each user selects the cell with the maximum received signal power as the initial serving cell during initialization.
The step (4) is specifically as follows: in the optimization process, the serving cell of the user changes along with the change of the transmission power, and when the serving cell of the user k is SkThen, the received signal to interference plus noise ratio from the serving cell is:
Figure BDA0003559836820000098
wherein the content of the first and second substances,
Figure BDA0003559836820000099
indicating the serving cell SkAverage channel gain with user k, N0Is the noise power value; according to Shannon's formula, user kThe achievable rate is:
Rk＝Wk log(1+γk)
wherein, WkIs the bandwidth of user k; the system utility is defined as the system energy utility, and the function can be specifically written as:
Figure BDA00035598368200000910
where T is the system throughput and the energy utility H depends on the user's serving cell and the transmit power of each cell, so H is a function of the mist access point range extension offset value and the mist access point transmit power and can be written as H (b, P).
The step (5) is specifically as follows:
(5.1) first, the maximum number of iterations of the offset value is set
Figure BDA0003559836820000101
Selecting a current target fog access point l, and setting an offset value initial temperature parameter for offset value adjustment
Figure BDA0003559836820000102
Coefficient of temperature displacement
Figure BDA0003559836820000103
Coefficient of temperature drop
Figure BDA0003559836820000104
Calculating the current offset value according to the initial temperature parameter of the offset value and the temperature drop coefficient to adjust the potential temperature
Figure BDA0003559836820000105
Figure BDA0003559836820000106
(5.2) by
Figure BDA0003559836820000107
Determining an average displacement distance of offset values at a current potential temperature
Figure BDA0003559836820000108
Figure BDA0003559836820000109
By tbRepresenting the number of iterations corresponding to the iteration of the offset value, i.e. the number of iterations of the current offset value, t at the time of the first iterationbAt this time, the potential offset displacement value of the mist access point l is iterated to be 0
Figure BDA00035598368200001010
Comprises the following steps:
Figure BDA00035598368200001011
wherein randn is a randomly generated [ -1,1 ] centered at 0]Random numbers within the interval that satisfy a normal distribution,
Figure BDA00035598368200001012
to average displacement distance by offset value
Figure BDA00035598368200001013
A random offset value [ alpha ], [ alpha ] that satisfies a normal distribution as a center]Representing rounding;
(5.3) the potential bias values obtained by cell l in this iteration are:
Figure BDA00035598368200001014
wherein, bl(tb-) is the previous iteration of the bias value for the fog access point l (i.e., tthb-1 iteration) of the obtained offset value, tbWhen b is equal to 0l(tb-) 0, increase
Figure BDA00035598368200001015
And reduction of
Figure BDA00035598368200001016
All probabilities of being 50%, the symbol [ x ]]→BMeans for mapping the value of x to the closest bias value to x in the set of available range extension biases B;
(5.4) note the tbSet of potential bias values for all mist access points for a sub-iteration to be
Figure BDA00035598368200001017
Wherein
Figure BDA00035598368200001018
The set formed by the offset values of all mist access points except the mist access point l is demisted for the previous iteration, and the set formed by the offset values of all mist access points in the previous iteration is recorded as b (t)b-) then the principle of updating the bias value of the iterative fog access point l this time is:
Figure BDA0003559836820000111
i.e. the set of potential bias values b obtained only at this iterationtemp(tb) Corresponding system energy value H (b)temp(tb) Is greater than the system effective value H (b (t)) corresponding to the previous iterationb-) of the cloud, iterate this round over the bias value b for the fog access pointl(tb) According to
Figure BDA0003559836820000112
Setting;
(5.5) updating tb＝tb+1, update
Figure BDA0003559836820000113
And
Figure BDA0003559836820000114
starting the next iteration to obtain a new iteration
Figure BDA0003559836820000115
And bl(tb) Updating the offset value of the fog access point l according to an offset value updating principle;
(5.6) continuing the iteration until the number of iterations
Figure BDA0003559836820000116
Or bl(tb) The times of keeping unchanged are larger than a preset bias iteration threshold value xibAnd stopping updating the offset value of the fog access point l, and recording the offset value set of all the fog access points as b at the moment.
The step (6) is specifically as follows:
(6.1) first, the number of iterations of the maximum power value is set
Figure BDA0003559836820000117
Setting initial temperature parameters for power regulation
Figure BDA0003559836820000118
Coefficient of temperature displacement
Figure BDA0003559836820000119
Coefficient of temperature drop
Figure BDA00035598368200001110
Calculating the potential temperature of the current power regulation according to the initial temperature parameter and the temperature reduction coefficient for power regulation
Figure BDA00035598368200001111
Figure BDA00035598368200001112
(6.2) by
Figure BDA00035598368200001113
Determining the average displacement distance of the power value under the current potential temperature
Figure BDA00035598368200001114
Figure BDA00035598368200001115
By tpRepresents the number of iterations corresponding to the power iteration (i.e. the current number of power iterations, t at the time of the first iteration)p0), this iteration's potential power shift value of the fog access point/
Figure BDA00035598368200001116
Comprises the following steps:
Figure BDA00035598368200001117
Figure BDA0003559836820000121
is the average distance of displacement of power values
Figure BDA0003559836820000122
A random power shift value centered to satisfy a normal distribution;
(6.3) the potential power value obtained by the mist access point l in this iteration is:
Figure BDA0003559836820000123
wherein, Pl(tp-) is the previous power iteration (i.e., tth) for the fog access point lp-1 iteration) of the obtained power value, tpWhen P is 0l(tp-)＝Pl maxIncrease of
Figure BDA0003559836820000124
And reduction of
Figure BDA0003559836820000125
All probabilities of (2) are 50%, sign
Figure BDA0003559836820000126
Means for mapping the value of x to the set of available transmit powers PLThe one power value closest to the value of x;
(6.4) note tpSet of potential power values for all mist access points for a sub-iteration to be
Figure BDA0003559836820000127
Wherein
Figure BDA00035598368200001212
The power values of all mist access points except the mist access point l are set for the last iteration, and the set formed by the power values of all mist access points in the last iteration is recorded as P (t)p-) then the power value updating principle of the iteration fog access point l is:
Figure BDA0003559836820000128
i.e. the set P of potential power values obtained only at this iterationtemp(tp) Corresponding system energy value H (P)temp(tp) Is greater than the system effective value H (P (t)) corresponding to the previous iterationp-) of the power value P of the iterative mist access point ll(tp) According to Pl temp(tp) Setting;
(6.5) updating tp＝tp+1, update
Figure BDA0003559836820000129
And
Figure BDA00035598368200001211
starting the next iteration to obtain new Pl temp(tp) And Pl(tp) Updating the power value of the fog access point l according to a power value updating principle;
(6.6) reactionRepeating the iteration till the number of iterations
Figure BDA00035598368200001210
Or Pl(tp) The times of keeping unchanged are larger than a preset power iteration threshold value xipAnd stopping updating the power value of the fog access point l, and recording the power value set of all the fog access points as P at the moment.
The step (7) is specifically as follows: by tout＝tout+1, updating the external iteration times, changing the target fog access point, and repeating the steps (5) to (6), namely respectively updating the bias value and the transmission power of the target fog access point by using simulated annealing until the external iteration times toutGreater than or equal to a preset external iteration threshold value
Figure BDA0003559836820000131
Or stopping external iteration when the times that the fog access point bias value and power value sets b and P are kept unchanged in the iteration process are larger than a threshold eta, setting the bias value and the sending power of each fog access point according to the finally obtained fog access point bias value set b and power value set P, and obtaining a final system energy effective value H by using a system energy utility function formula.
A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a mist access point range extension bias and transmit power joint adjustment method as described above.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the computer program implementing a mist access point range extension biasing and transmit power joint adjustment method as described above.

Claims (10)

1. A method for jointly adjusting range expansion bias and transmission power of a fog access point is characterized by comprising the following steps:
(1) initializing a network, setting a macro cell, a fog access point and a user in the network, initializing range expansion bias, sending power and iteration times, and initializing a service cell of the user;
(2) defining a system energy utility function;
(3) the user selects a service cell according to the maximum offset received power;
(4) calculating the user reachable rate and further calculating the system utility;
(5) fixing the transmission power set of all the fog access points, and updating the bias value of the fog access point l by using simulated annealing;
(6) fixing the bias value sets of all the fog access points, and updating the transmission power of the fog access point l by using simulated annealing;
(7) and (5) changing the target fog access point, repeating the steps (5) to (6), respectively updating the offset value and the transmitting power of the target fog access point by using simulated annealing, stopping iteration until a stopping condition is met, setting the offset value and the transmitting power of each fog access point, and obtaining a final system energy value by using a system energy utility function formula.
2. The method for jointly adjusting the range expansion bias and the transmission power of the fog access point according to claim 1, wherein the step (1) is specifically as follows:
(1.1) assuming that the system has M macro cells, L fog access points and K users in total, and the macro cell set is recorded as
Figure FDA0003559836810000011
Set of fog access points as
Figure FDA0003559836810000012
The macro cell and the fog access point are collectively called as a cell, and the set of all cells is denoted as
Figure FDA0003559836810000013
Wherein, U represents the union of two sets, and the user set is recorded as
Figure FDA0003559836810000014
(1.2) Only the mist Access Point can be adjustedThe range expansion bias changes the user service cell, and then the combined emission power adjusts and optimizes the network utility, any fog access point
Figure FDA0003559836810000015
Is a set of available range extension biases of
Figure FDA0003559836810000016
Wherein b isminTo minimum bias, bmaxIs the maximum offset, Δ is the offset interval, defined by the operator; range extension biasing for arbitrary macro cell m
Figure FDA0003559836810000017
(1.3) to ensure coverage, each macrocell m uses a maximum transmission power PmaxA downlink signal is sent, and the fog access point can dynamically change and adjust the sending power of the fog access point so as to improve the network performance;
(1.4) definition of Δp＝Pl max/(Np-1) is a power interval, wherein NpFor the power class number, the available transmission power of any fog access point is PL＝{0,1·Δp,2·Δp,....,Pl maxB, the range expansion bias of the fog recording access point l is set aslWith a transmission power of PlThe range expansion bias set of all the fog access points is b, and the transmission power set of all the fog access points is P;
(1.5) Range extension bias for any fog Access Point l at initialization
Figure FDA0003559836810000021
Transmission power
Figure FDA0003559836810000022
Wherein P isl maxMaximum transmit power for the mist access point l;
(1.6) user k receives from cell
Figure FDA0003559836810000023
Is recorded as the received signal power
Figure FDA0003559836810000024
During initialization, each user selects the cell with the maximum received signal power as the initial serving cell, and the serving cell of user k is marked as Sk；
(1.7) defining the number of external iterations toutBias value iteration number tbNumber of iterations of power value tpAt initialization, tout＝tb＝tp＝0。
3. The method for jointly adjusting range expansion bias and transmission power of a fog access point according to claim 1, wherein the step (2) is specifically: firstly, defining the throughput T of the system, namely T is the reachable rate R of all users kkThe sum of (a) and (b),
Figure FDA0003559836810000025
the utility function of the system is
Figure FDA0003559836810000026
Wherein, the first and the second end of the pipe are connected with each other,
Figure FDA0003559836810000027
is the total power loss of the fog access point.
4. The method for jointly adjusting the range expansion bias and the transmission power of the fog access point according to claim 1, wherein the step (3) is specifically as follows: by PcIndicating the transmission power, G, of cell cc,kRepresenting the average channel gain between cell c and user k, the received signal power
Figure FDA0003559836810000028
User k selects serving cell S according to maximum offset post-received power criterionkTherefore, it is possible to
Figure FDA0003559836810000029
I.e. user k selects the received signal power plus offset value in all cells
Figure FDA00035598368100000210
The largest cell is used as the serving cell; range extension bias for any fog access point l at initialization
Figure FDA00035598368100000211
Therefore, each user selects the cell with the maximum received signal power as the initial serving cell during initialization.
5. The method for jointly adjusting the range expansion bias and the transmission power of the fog access point according to claim 1, wherein the step (4) is specifically as follows: in the optimization process, the serving cell of the user is changed along with the change of the transmission power, and when the serving cell of the user k is SkWhen the ue receives a received signal to interference plus noise ratio from the serving cell, the received signal to interference plus noise ratio is:
Figure FDA0003559836810000031
wherein the content of the first and second substances,
Figure FDA0003559836810000032
indicating the serving cell SkAverage channel gain with user k, N0Is the noise power value; according to the shannon formula, the achievable rate of user k is:
Rk＝Wklog(1+γk)
wherein, WkIs the bandwidth of user k; the system utility is defined as the system energy utility, and the function can be specifically written as:
Figure FDA0003559836810000033
where T is the system throughput and the energy utility H depends on the serving cell of the user and the transmit power of each cell, so H is a function of the set of mist access point range extension bias values and the set of mist access point transmit powers, which can be written as H (b, P).
6. The method for jointly adjusting the range expansion bias and the transmission power of the fog access point according to claim 1, wherein the step (5) is specifically as follows:
(5.1) first, the maximum number of iterations of the offset value is set
Figure FDA0003559836810000034
Selecting a current target fog access point l, and setting an offset value initial temperature parameter for offset value adjustment
Figure FDA0003559836810000035
Coefficient of temperature displacement
Figure FDA0003559836810000036
Coefficient of temperature drop
Figure FDA0003559836810000037
Calculating the current offset value according to the initial temperature parameter of the offset value and the temperature drop coefficient to adjust the potential temperature
Figure FDA0003559836810000038
Figure FDA0003559836810000039
(5.2) by
Figure FDA00035598368100000310
Determining an average displacement distance of offset values at a current potential temperature
Figure FDA00035598368100000311
Figure FDA00035598368100000312
By tbRepresenting the iteration number corresponding to the iteration of the offset value, i.e. the iteration number of the current offset value, t during the first iterationbThe potential offset displacement value of the mist access point l is iterated this time as 0
Figure FDA00035598368100000313
Comprises the following steps:
Figure FDA00035598368100000314
wherein randn is a randomly generated [ -1,1 ] centered at 0]Random numbers within the interval that satisfy a normal distribution,
Figure FDA0003559836810000041
to average displacement distance by offset value
Figure FDA0003559836810000042
Is a central random offset value satisfying a normal distribution of]Representing rounding;
(5.3) the potential bias values obtained by cell l in this iteration are:
Figure FDA0003559836810000043
wherein, bl(tb-) is the previous iteration of the bias value for the fog access point l (i.e., tthb-1 iteration) of the obtained offset value, tbWhen b is equal to 0l(tb-) 0, increase
Figure FDA0003559836810000044
And reduce
Figure FDA0003559836810000045
All have a probability of 50%, the symbol x]→BMeans for mapping the value of x to the one of the set of available range extension offsets B that is closest to x;
(5.4) note the tbSet of potential bias values for all mist access points for a sub-iteration of
Figure FDA0003559836810000046
Wherein
Figure FDA0003559836810000047
The set formed by the offset values of all mist access points except the mist access point l is demisted for the previous iteration, and the set formed by the offset values of all mist access points in the previous iteration is recorded as b (t)b-) then the principle of updating the bias value of the fog access point l for this iteration is:
Figure FDA0003559836810000048
i.e. the set of potential bias values b obtained at this iteration onlytemp(tb) Corresponding system energy value H (b)temp(tb) Is greater than the system effective value H (b (t)) corresponding to the previous iterationb-) of the fog window, iterate this round over the bias value b for the fog access pointl(tb) According to
Figure FDA0003559836810000049
Setting;
(5.5) update tb＝tb+1, update
Figure FDA00035598368100000410
And
Figure FDA00035598368100000411
starting the next iteration to obtain a new iteration
Figure FDA00035598368100000412
And bl(tb) Updating the offset value of the fog access point l according to an offset value updating principle;
(5.6) continuing the iteration until the number of iterations
Figure FDA00035598368100000413
Or bl(tb) The times of keeping unchanged are larger than a preset bias iteration threshold value xibAnd stopping updating the offset value of the fog access point l, and recording the offset value set of all the fog access points as b at the moment.
7. The mist access point range expansion bias and transmit power joint adjustment method of claim 1, wherein the step (6) is specifically:
(6.1) first, the maximum number of iterations of the power value is set
Figure FDA0003559836810000051
Setting initial temperature parameters for power regulation
Figure FDA0003559836810000052
Coefficient of temperature displacement
Figure FDA0003559836810000053
Coefficient of temperature drop
Figure FDA0003559836810000054
Calculating the potential temperature of the current power regulation according to the initial temperature parameter and the temperature drop coefficient for power regulation
Figure FDA0003559836810000055
Figure FDA0003559836810000056
(6.2) by
Figure FDA0003559836810000057
Determining the average displacement distance of the power value under the current potential temperature
Figure FDA0003559836810000058
Figure FDA0003559836810000059
By tpRepresents the number of iterations corresponding to the power iteration (i.e. the current number of power iterations, t at the time of the first iteration)p0), this iteration of the potential power shift value of the fog access point/
Figure FDA00035598368100000510
Comprises the following steps:
Figure FDA00035598368100000511
Figure FDA00035598368100000512
is the average distance of displacement at power level
Figure FDA00035598368100000513
A random power shift value centered to satisfy a normal distribution;
(6.3) the potential power value obtained by the mist access point l in this iteration is:
Figure FDA00035598368100000514
wherein, Pl(tp-) is the previous power iteration (i.e., tth) for the fog access point lp1 iteration) of the power value obtained, tpWhen equal to 0, Pl(tp-)＝Pl maxIncrease of
Figure FDA00035598368100000515
And reduce
Figure FDA00035598368100000516
All probabilities of (2) are 50%, sign
Figure FDA00035598368100000517
Means for mapping the value of x to the set of available transmit powers PLThe one power value closest to the value of x;
(6.4) note the tpSet of potential power values for all mist access points for a sub-iteration of
Figure FDA00035598368100000518
Wherein
Figure FDA00035598368100000519
The power values of all the fog access points except the fog access point l are set for the previous iteration, and the set formed by the power values of all the fog access points in the previous iteration is recorded as P (t)p-) then the power value updating principle of the iteration fog access point l is:
Figure FDA00035598368100000520
i.e. the set P of potential power values obtained only at this iterationtemp(tp) Corresponding system energy value H (P)temp(tp) Is greater than the system effective value H (P (t)) corresponding to the previous iterationp-) of the power value P of the iterative mist access point ll(tp) According to Pl temp(tp) Setting;
(6.5) updatetp＝tp+1, update
Figure FDA0003559836810000061
And
Figure FDA0003559836810000062
starting the next iteration to obtain new Pl temp(tp) And Pl(tp) Updating the power value of the fog access point l according to a power value updating principle;
(6.6) iterating repeatedly until the number of iterations
Figure FDA0003559836810000063
Or Pl(tp) The times of keeping unchanged is larger than a preset power iteration threshold value xipAnd stopping updating the power value of the fog access point l, and recording the power value set of all the fog access points as P at the moment.
8. The method for jointly adjusting the range expansion bias and the transmission power of the fog access point according to claim 1, wherein the step (7) is specifically as follows: by tout＝tout+1, updating the external iteration times, changing the target fog access point, and repeating the steps (5) to (6), namely respectively updating the bias value and the transmission power of the target fog access point by using simulated annealing until the external iteration times toutGreater than or equal to a preset external iteration threshold value
Figure FDA0003559836810000064
Or stopping external iteration when the times that the fog access point bias value and power value sets b and P are kept unchanged in the iteration process are larger than a threshold eta, setting the bias value and the sending power of each fog access point according to the finally obtained fog access point bias value set b and power value set P, and obtaining a final system energy effective value H by using a system energy utility function formula.
9. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a mist access point range extension bias and transmit power joint adjustment method as claimed in any one of claims 1-8.
10. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program implements a mist access point range extension bias and transmit power joint adjustment method as claimed in any one of claims 1 to 8.
CN202210285725.4A 2022-03-23 2022-03-23 Fog access point range expansion bias and transmission power combined adjustment method Pending CN114786194A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210285725.4A CN114786194A (en) 2022-03-23 2022-03-23 Fog access point range expansion bias and transmission power combined adjustment method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210285725.4A CN114786194A (en) 2022-03-23 2022-03-23 Fog access point range expansion bias and transmission power combined adjustment method

Publications (1)

Publication Number Publication Date
CN114786194A true CN114786194A (en) 2022-07-22

Family

ID=82426067

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210285725.4A Pending CN114786194A (en) 2022-03-23 2022-03-23 Fog access point range expansion bias and transmission power combined adjustment method

Country Status (1)

Country Link
CN (1) CN114786194A (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105357683A (en) * 2015-12-03 2016-02-24 东南大学 Gibbs sampling-based ultra-dense heterogeneous network optimal cell range expansion bias adjustment method
US20160165468A1 (en) * 2014-12-09 2016-06-09 Futurewei Technologies, Inc. Method and apparatus for optimizing cell specific antenna configuration parameters
CN105722205A (en) * 2016-02-01 2016-06-29 东南大学 Ultra-dense heterogeneous network energy efficiency based resource allocation method
CN108171318A (en) * 2017-11-30 2018-06-15 河南大学 One kind is based on the convolutional neural networks integrated approach of simulated annealing-Gaussian function
CN110505643A (en) * 2019-09-23 2019-11-26 杭州电子科技大学 Extensive mimo system uplink efficiency optimization method based on simulated annealing
CN111257847A (en) * 2020-03-23 2020-06-09 西安电子科技大学 FDA radar directional diagram decoupling method based on simulated annealing algorithm

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160165468A1 (en) * 2014-12-09 2016-06-09 Futurewei Technologies, Inc. Method and apparatus for optimizing cell specific antenna configuration parameters
CN105357683A (en) * 2015-12-03 2016-02-24 东南大学 Gibbs sampling-based ultra-dense heterogeneous network optimal cell range expansion bias adjustment method
CN105722205A (en) * 2016-02-01 2016-06-29 东南大学 Ultra-dense heterogeneous network energy efficiency based resource allocation method
CN108171318A (en) * 2017-11-30 2018-06-15 河南大学 One kind is based on the convolutional neural networks integrated approach of simulated annealing-Gaussian function
CN110505643A (en) * 2019-09-23 2019-11-26 杭州电子科技大学 Extensive mimo system uplink efficiency optimization method based on simulated annealing
CN111257847A (en) * 2020-03-23 2020-06-09 西安电子科技大学 FDA radar directional diagram decoupling method based on simulated annealing algorithm

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
朱文祥: "超密集无线网络能量效率关键技术研究", 超密集无线网络能量效率关键技术研究, 15 December 2018 (2018-12-15), pages 2 *

Similar Documents

Publication Publication Date Title
CN108848563B (en) Energy-efficiency-based resource allocation method for downlink of cooperative NOMA (non-orthogonal multiple access) system
CN107708197B (en) high-energy-efficiency heterogeneous network user access and power control method
CN111314935B (en) Method for minimizing downlink transmission delay based on NOMA-MEC system
CN108064077A (en) The power distribution method of full duplex D2D in cellular network
CN112702097A (en) Joint beamforming and power control method for UAV-assisted cellular network
CN104853425A (en) A power control method for heterogeneous network uplink
US6961582B2 (en) Transmission power control method and system for CDMA communication system
CN101778465B (en) Error estimation based proportion power control method in CDMA (Code Division Multiple Access) cellular system
CN114302497A (en) Scheduling method applied to coexistence of unauthorized millimeter-wave band heterogeneous networks
CN110602722A (en) Design method for joint content pushing and transmission based on NOMA
CN111315017A (en) SCMA system energy-saving-based resource allocation method
CN112261662B (en) Transmission method for improving energy efficiency of NOMA cooperative communication system
CN104079335A (en) 3D MIMO beamforming method with robustness in multi-cell OFDMA network
WO2021136472A1 (en) Two user uplink transmission rateless encoding method and rateless code decoding method
CN106912059B (en) Cognitive relay network joint relay selection and resource allocation method supporting mutual information accumulation
CN113301638A (en) D2D communication spectrum allocation and power control algorithm based on Q learning
CN102131279A (en) Method and device for adjusting transmission power
CN114786194A (en) Fog access point range expansion bias and transmission power combined adjustment method
CN115884343A (en) High-mobility ad hoc network dynamic power distribution method based on directional multi-beam antenna
CN114189852B (en) Downlink multiuser beam alignment and data transmission method for millimeter wave hidden communication
CN113490277B (en) SWIPT-based energy allocation and time slot switching coefficient joint optimization method in H-CRAN
CN113453197B (en) User pairing method combining mobile prediction and dynamic power
CN112839344B (en) Relay node deployment optimization method for multi-hop relay network
WO2016202186A1 (en) Power allocation method for multi-user mobile relay communication system
CN110572871B (en) Wireless energy-carrying relay system with multiple eavesdropping nodes and resource allocation method thereof

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination