CN112752266B - Joint spectrum access and power control method in D2D haptic communication - Google Patents
Joint spectrum access and power control method in D2D haptic communication Download PDFInfo
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Abstract
A joint spectrum access and power control method in D2D haptic communication relates to the technical field of wireless communication. The invention randomly accesses a resource block to each D2D pair according to a frequency spectrum access mechanism based on competition; calculating the packet error rate of a D2D forward link under a competitive access mechanism, namely from a source end to a destination end; calculating the packet error rate of a D2D reverse link under a competitive access mechanism, namely from a destination end to a source end; calculating the packet error rate of the D2D haptic communication closed loop; establishing an optimization problem, namely minimizing the total packet error rate of the system; modeling an optimization problem as a game; and solving the game Nash equilibrium by adopting a synchronous logarithmic linear learning algorithm. Interference among users can be coordinated through reasonable power control, resource scheduling delay can be effectively unloaded, and the error probability of data packet transmission is reduced, so that the delay and reliability requirements of D2D tactile communication are met.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to a combined spectrum access and power control method for D2D haptic communication.
Background
With the development of wireless communication technology, people no longer satisfy traditional audio-video communication, but hope to obtain more immersive user experience. Based on this, haptic communication technology has been developed. The haptic communication mainly transmits human haptic signals (such as strength, torque, speed, and the like), and can provide multi-dimensional sensing information for a user. Therefore, the haptic communication has a wide application prospect, such as virtual reality, automatic driving, smart medical treatment, and the like.
The haptic communication can be divided into remote haptic communication and local haptic communication according to the distance between the control terminal and the operation terminal. For tele-tactile communication, it is necessary to transmit signals by means of a network infrastructure (network domain); for local tactile communication, the control end and the operation end can directly communicate in a device-to-device (D2D) mode, so that the spectrum utilization efficiency is effectively improved, and the transmission delay is reduced.
However, implementing D2D haptic communication is more challenging than traditional D2D audiovisual communication. Specifically, the audio/video stream has a high throughput requirement, so that only rich bandwidth resources are allocated, and the audio/video stream is generally unidirectional. The difference is that the transmission of the haptic flow is bidirectional transmission, and the transmission comprises that the control end sends a control signal to the operation end on a forward link, and the operation end feeds back the haptic signal to the control end on a reverse link, so that a closed control loop is formed. Furthermore, to ensure the immersive experience of the user, the entire control loop has very strict requirements on latency and reliability, and thus the haptic communication belongs to an ultra-reliable low-latency communication (URLLC) scenario.
Radio resource allocation, including spectrum access and power control, is a key step in implementing D2D haptic communication, as it directly impacts the latency and reliability performance of the communication. Currently, there is a small body of literature investigating the problem of haptic communication resource management. The literature [ heated Human-in-the-Loop Mobile Networks: A Radio Resource Allocation permission on Haptical Communications, IEEE trans. Wireless.Commun., vol.17, No.7, pp.4493-4508,2018] proposes a greedy algorithm with low complexity and a greedy Resource Allocation scheme close to the optimal solution, respectively, for two Resource Allocation situations of perceptual coding and symmetric design. The document Fog Computing for 5G Tactile Industrial Internet of Things QoE-Aware Resource Allocation Model, IEEE trans. Ind. Informatt, vol.15, No.5, pp.3085-3092,2019 proposes a dynamic Resource Allocation Model based on user experience to cope with haptic communication applications in the Internet of Things, and implements the Model using Java.
However, the above documents are all based on a request-grant mechanism, i.e. the user needs to make a resource scheduling request to the base station and wait for the base station to grant before using the spectrum resource. Obviously, this process will degrade the end-to-end latency to the point that the latency requirements for haptic communication cannot be met.
Disclosure of Invention
The invention mainly aims at the problem that the existing resource allocation scheme can cause the increase of D2D tactile communication time delay and the reduction of reliability, and provides a combined spectrum access and power control method. The method can effectively eliminate the resource scheduling time delay and reduce the error probability of data packet transmission, thereby meeting the time delay and reliability requirements of D2D tactile communication.
The invention provides a method for combining spectrum access and power control in D2D haptic communication, which comprises the following steps:
the method comprises the following steps: for the local tactile communication scene, the control end and the operation end can directly communicate by means of D2D. Thus, the control node and the operation node form a D2D pair, wherein the control node is the source node and the operation node is the destination node. Suppose there are N D2D pairs and K orthogonal resource blocks (N) in a cell>K) Respectively using
And
and (4) showing. Wherein, D2D uses e for the source end and the destination end of n respectivelynAnd rnRepresenting that all sources and destinations are formed separately
And
each D2D pair randomly accesses one resource block according to the contention-based spectrum access mechanism.
Step two: calculating the packet error rate of the D2D forward link under the competitive access mechanism, namely the destination end r nPacket error rate of
The forward link is from a source end to a destination end; according to short data packet formula under finite block length, packet error rate
Depending on the destination rnReceived signal-to-noise ratio of
Destination terminal r under calculation competition access mechanismnReceived signal-to-noise ratio of
Step three: calculating the packet error rate of the D2D reverse link under the competitive access mechanism, namely the source end enPacket error rate of
The reverse link is from a destination end to a source end; according to the short data packet formula under the finite block length, the packet error rate
Dependent on source enReceived signal-to-noise ratio of
Source end e under calculation competition access mechanismnReceived signal-to-noise ratio of
Step four: the packet error rate of the D2D haptic communication closed loop is calculated. According to step two and step three, the probability of successful transmission of the D2D haptic communication closed loop is
Thus, the closed loop packet error rate can be approximated as
Step five: and establishing an optimization problem. The total packet error rate of N D2D pairs in the network is
Based on this, under the contention access mechanism, the optimization goal of power control is to minimize the total packet error rate of the system, i.e. the total packet error rate
s.t.
Wherein, P ═ P (P)1,...,pn,...,pN) For N D2D pairs of transmit power vectors,
consists of the transmitting power of a source end and a destination end, S is the maximum transmitting power grade which can be adopted by the source end and the destination end, and epsilon thA closed loop packet error rate threshold for each D2D pair.
Step six: the optimization problem is modeled as a game. The optimization problem is a mixed integer nonlinear programming problem and is solved by adopting a game theory. Building (2)The standing game model is
Wherein
In order to be a collection of gaming participants,
in order to be a policy space, the policy space,
is the set of policies for game participant n. u. ofn(pn,p-n) Representing the utility function of a game participant n, where pnFor the transmission power of game participants n, p-nIs the transmission power of the other gaming participants than gaming participant n. Thus, the proposed power control bet can be modeled as
Step seven: and solving game Nash equilibrium. By adopting a synchronous log linear learning (SLL) algorithm, the optimal Nash equilibrium solution can be converged on the premise of no information interaction and coordination mechanism, namely the sum of the packet error rates of all D2D pairs under a competitive access mechanism is minimized. The SLL algorithm is based on the boltzmann exploration strategy, i.e., the probability of a participant selecting a strategy with higher utility is greater than the probability with a strategy with lower utility. Therefore, the boltzmann exploration strategy is considered to be an effective method for getting rid of local optima and finally achieving global optima.
The invention provides a resource access mechanism based on competition. Specifically, a number of orthogonal resource blocks are first reserved for D2D haptic communication. When a data packet needs to be transmitted, the source end or the destination end can randomly access a resource block on a forward link or a reverse link without sending a resource scheduling request and waiting for authorization of a base station. Although the access mechanism can effectively unload the scheduling delay, due to the random access, when two or more users access the same resource block, mutual interference occurs among the users, and the reliability of transmission is affected. Then, interference among users can be coordinated through reasonable power control, so that the time delay and reliability requirements of D2D haptic communication are met simultaneously.
The invention provides a D2D haptic communication-oriented combined spectrum access and power control method, which can effectively unload resource scheduling delay and reduce the error probability of data packet transmission, thereby meeting the delay and reliability requirements of D2D haptic communication. The method comprises the steps of firstly adopting a frequency spectrum access mode based on a competition mechanism to unload resource scheduling time delay, and then reducing the packet error rate of transmission through reasonable power control under the mechanism. Specifically, the power control problem is converted into a non-cooperative game model, and a distributed learning algorithm is adopted to solve Nash equilibrium.
Drawings
FIG. 1 is a diagram of a D2D haptic communication model of the present invention.
Fig. 2 is a diagram illustrating interference analysis between D2D pairs under the contention mechanism of the present invention.
Fig. 3 is a flow chart of the joint spectrum access and power control of the present invention.
Fig. 4a is a schematic diagram showing the comparison between the algorithm of the present invention and the optimal solution for different iteration numbers about the total packet error rate.
Fig. 4b is a graph showing the power selection comparison of different pairs of D2D for different iterations.
Fig. 5a is a schematic diagram of a relationship between packet error rate and packet length under different algorithm environments.
Fig. 5b is a schematic diagram of a relationship between packet error rate and number of resource blocks in different algorithm environments.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The D2D haptic communication model is further described with reference to FIG. 1. A D2D pair consists of a source and a destination. In haptic communication, the source terminal is typically a haptic device, i.e., human action, sensation can be converted into a haptic signal input through various encoding techniques. The destination is typically a remote control, i.e. it can interact with the environment and feed back tactile signals to the source.
The communication process of D2D haptic communication is described as follows. First, the source peer transmits a control signal to the destination peer over the forward link. The destination then interacts with the environment based on the received control signals and sends haptic feedback signals to the source via the reverse link, forming a closed-loop D2D haptic communication model. In the present invention, the source and destination of multiple D2D are strictly synchronized in time when transmitting.
Referring to fig. 2, the interference generated between the pair of D2D in the contention mechanism is further analyzed. Analyzing the destination r for the forward link example1The interference experienced. Considering the finiteness of the transmitting power and the fading characteristics of the wireless channel, each source end can only affect the destination end within a certain coverage range. For example, the pink shaded area can be regarded as the source end e 3Of the source end e3Destination ends within the coverage area can be affected, but destination ends outside the coverage area cannot be affected. Assume that 3D 2D pairs in the figure access the same resource block simultaneously. Then, the destination terminal r1Will be received by the source e2Without being influenced by the source e3Due to the destination end r1At the source end e2Is not in the source end e3Within the coverage of (c). Similarly, on the reverse link, the source e1Will receive the destination end r3Because of the source end e1At the destination end r3Within the coverage of (c).
The implementation steps of the present invention will be further explained with reference to fig. 3:
the method comprises the following steps: suppose that N D2D pairs and K orthogonal resource blocks coexist in a cell and are used respectively
And
and (4) showing. Wherein D2D is divided into source end and destination end of nFor use of enAnd rnRepresenting that all sources and destinations are formed separately
And
each D2D pair randomly accesses one resource block according to the contention-based spectrum access mechanism.
Step two: calculating the packet error rate of the D2D forward link (source end to destination end) under the competitive access mechanism, namely the destination end rnThe packet error rate of (d). Under a competitive access mechanism, a user randomly accesses one resource block in an equal probability mode. At this time, if D2D accesses resource block k to n, the destination r nAt a received signal-to-noise ratio SNR of
Wherein,
as a source end enTransmit power of H (e)n,rn) As a source end enTo the destination end rnChannel gain of σ21/K is the probability that D2D accesses resource block K to i;
is a vector of the source transmit power,
is in a vector PeAll to the destination end rnHas a signal-to-noise ratio exceeding gammath1The source terminal set of (2); wherein, γth1To the destination end rnIf other sources go to rnSNR of greater than gammath1Then, it will be directed to the destination rnWill not otherwise interfere with the reception of rnThe reception of (2) causes an impact; e.g. of the typemIs DThe source end of the 2D pair m,
as a source end emTransmit power of H (e)m,rn) As a source end emTo the destination end rnThe channel gain of (a); e.g. of the typeiThe source end of pair i of D2D,
as a source end eiTransmit power of H (e)i,rn) As a source end eiTo the destination end rnThe channel gain of (1).
Since D2D randomly accesses resource block n under the contention mechanism, the received signal-to-noise ratio relative to K resource blocks is
According to the short packet formula under the finite block length, the packet error rate of the D2D forward link (source end to destination end) is
Wherein,
is a Gaussian Q function, t is an integral variable, dt is a first derivative of t,
l is the packet length, η is the number of information bits transmitted, and 
Step three: calculating the packet error rate of the D2D reverse link (from the destination end to the source end) under the competitive access mechanism, namely the source end enThe packet error rate of (d). Under the contention mechanism, the received signal-to-noise ratio of D2D on K resource blocks to n is
Wherein,
for the destination end rnTransmit power of H (e)n,rn) As a source end enTo the destination end rnChannel gain of σ21/K is the probability that D2D accesses resource block K to i;
for the vector of transmit powers of the destination,
is in a vector PrDown, all to the source end enHas a signal-to-noise ratio exceeding gammath2In which γth2To the source end enA signal-to-noise ratio threshold causing interference; r ismFor the destination of D2D pair m,
to a destination end rmTransmit power of H (e)n,rm) As a source end enTo the destination end rmThe channel gain of (a); r isiFor the destination of D2D pair i,
to a destination end riTransmit power of H (e)n,ri) As a source end enTo the destination end riThe channel gain of (1).
According to the short packet formula under the finite block length, the packet error rate of the reverse link (destination end to source end) of D2D is
Wherein,
is a Gaussian Q function, t is an integral variable, dt is a first derivative of t,
l is the packet length, η is the number of information bits transmitted, and
step four: the packet error rate of the D2D haptic communication closed loop is calculated. According to step two and step three, the probability of successful transmission of the D2D haptic communication closed loop is
Due to the fact that
And
is substantially 10-3～10-5Of order of magnitude, therefore, the closed loop packet error rate can be approximated as
Step five: and establishing an optimization problem. The total packet error rate of N D2D pairs in the network is
Based on this, under the contention access mechanism, the optimization goal of power control is to minimize the total packet error rate of the system, i.e. the total packet error rate
s.t.
Wherein, P ═ P (P)1,...,pn,...,pN) For N D2D pairs of transmit power vectors,
consists of the transmitting power of a source end and a destination end, S is the maximum transmitting power grade which can be adopted by the source end and the destination end, and epsilonthA closed loop packet error rate threshold for each D2D pair.
Step six: the optimization problem is modeled as a game. The optimization problem is a mixed integer nonlinear programming problem and is solved by adopting a game theory. The game model is
Wherein
In order to be a collection of gaming participants,
in order to be a policy space, the policy space,
is the set of policies for game participant n. Due to the fact that
Therefore, it is not only easy to use
Can be expressed as
un(pn,p-n) Representing the utility function of a game participant n, where pnFor the transmission power of game participants n, p-nIs the transmission power of the other gaming participants than gaming participant n. In this model, un(pn,p-n) Is defined as
Wherein r isiFor the destination of D2D pair i,
to a destination end riThe packet error rate of (2); e.g. of the typejBeing the source end of D2D pair j, 
As a source end ejThe packet error rate of (d);
as source end enSet of destinations affected when transmitting at transmit power S, i.e.
Wherein
In the same way, the method for preparing the composite material,
is as the destination terminal rnSet of source terminals affected when transmitting at a transmit power SI.e. by
Wherein
Therefore, unThe physical meaning is the sum of the packet error rates of all the sources and destinations affected by the game participant n.
Thus, the proposed power control game can be modeled as
Step seven: and solving game Nash equilibrium. By adopting a synchronous log linear learning (SLL) algorithm, the optimal Nash equilibrium solution can be converged on the premise of no information interaction and coordination mechanism, namely the sum of the packet error rates of all D2D pairs under a competitive access mechanism is minimized. The algorithm is based on the boltzmann exploration strategy, i.e. the probability of a participant selecting a strategy with higher utility is greater than the probability of a strategy with lower utility. Therefore, the boltzmann exploration strategy is considered to be an effective method for getting rid of local optima and finally achieving global optima. The proposed algorithm is as follows:
algorithm 1 power control algorithm based on SLL
Initialization: setting the initial iteration time t as 0, and initializing power vectors p (0) of all game participants as p1(0),...,pN(0) Therein of 
And is provided with
In addition, a binary indication variable is set
All game participants simultaneously perform the following steps:
Repeat
t＝t+1
If bn(t-1) ═ 0, game participant n updates its policy according to the following rules
Wherein p' is the strategy taken by the game participant n at time t;
representation collection
Number of middle elements, δnThe exploration rate for the gaming participant n. Furthermore, if pn(t)≠pn(t-1) setting bn(t) ═ 1; otherwise, set bn(t)＝0。
End if
If bn(t-1) ═ 1, game participant n updates its policy according to the following rules
Wherein, beta is a learning parameter,
and
the utility of the betting participant n at times t-1 and t-2 respectively,
then, set up bn(t)＝0。
End if
If constraint condition
Cannot satisfy
Setting p (t) ═ p (t-1)
End if
Until
pnRemain unchanged.
The effect of the invention will be further described with reference to fig. 4 and 5:
the simulation in the invention is based on software MatlabR2016 a. The simulation parameter parameters are set as follows: the number of the D2D pairs is 10, the number of the resource blocks is 3, the actual quantized power set is {0.1,0.2,0.3}, the noise power is-100 dBm, the distance from the source end to the destination end of the D2D is 15m, and the threshold r of the signal-to-noise ratio isth20dB, 400bits of information bits, and 50channel use of packet length. Thus, the set of policies for each gaming participant is
Fig. 4 analyzes the convergence of the proposed game learning algorithm. In fig. 4a, the proposed algorithm gradually converges to the optimal power selection strategy over a number of iterations. It should be noted that even if the algorithm reaches optimal power selection, it is still possible to jump out of the current scheme to explore unknown areas, as shown by the red circles. Finally, when the number of iterations is large enough, the proposed algorithm will converge. Fig. 4b further illustrates the convergence of the algorithm. We randomly picked 4D 2D pairs from 10D 2D pairs, denoted D2D pair 1, D2D pair 2, D2D pair 3 and D2D pair 4 respectively. When the number of algorithm iterations is large enough, the power selection of each D2D pair will converge to a particular strategy.
Fig. 5 shows the relation between the packet error rate and the packet length and the number of resource blocks, respectively. Wherein "BR" is an optimal response algorithm, i.e. in each iteration of the algorithm, the user selects the strategy that maximizes his own benefit. As shown in fig. 5a, the packet error rate of all algorithms decreases as the packet length increases until it approaches 0. In fig. 5b, as the number of resource blocks increases, the packet error rate of all algorithms is decreasing. This is because, as the number of resource blocks increases, the probability that a user will access the same resource block will decrease. In addition, when K ≧ 10, each user can be assigned a dedicated resource block, so no interference occurs between each other.
Claims (9)
1. A method for combining spectrum access and power control in D2D haptic communication is characterized by comprising the following steps:
the method comprises the following steps: for a local tactile communication scene, a control end and an operation end are directly communicated in a D2D mode, and the control end and the operation end form a D2D pair, wherein the control end is a source end, and the operation end is a destination end; suppose there are N D2D pairs and K orthogonal resource blocks in a cell, where N is>K, respectively using
And
represents; wherein, D2D uses e for the source end and the destination end of n respectively nAnd rnMeaning that all sources and destinations constitute e ═ e, respectively1,...,en,...,eNAnd
each D2D pair randomly accesses a resource block according to a frequency spectrum access mechanism based on competition;
step two: calculating the packet error rate of the D2D forward link under the competitive access mechanism, namely the destination end rnPacket error rate of
The forward link is from a source end to a destination end; according to the short data packet formula under the finite block length, the packet error rate
Depending on the destination rnReceived signal-to-noise ratio of
Calculating contestDestination terminal r under contention access mechanismnReceived signal-to-noise ratio of
Step three: calculating the packet error rate of the D2D reverse link under the competitive access mechanism, namely the source end enPacket error rate of
The reverse link is from a destination end to a source end; according to the short data packet formula under the finite block length, the packet error rate
Dependent on source enReceived signal-to-noise ratio of
Source end e under calculation competition access mechanismnReceived signal-to-noise ratio of
Step four: calculating the packet error rate of the D2D tactile communication closed loop, wherein the successful transmission probability of the D2D tactile communication closed loop is that according to the step two and the step three
Thus, the closed loop packet error rate is approximately
Step five: the optimization problem is established, and the total packet error rate of N D2D pairs in the network is
Based on this, under the contention access mechanism, the optimization goal of power control is to minimize the total packet error rate of the system, i.e. the total packet error rate
s.t.
Wherein, P ═ P (P)1,...,pn,...,pN) For N D2D pairs of transmit power vectors,
consists of the transmitting power of a source end and a destination end, S is the maximum transmitting power grade which can be adopted by the source end and the destination end, and epsilonthA closed loop packet error rate threshold for each D2D pair;
step six: modeling the optimization problem as a game and establishing a game model as
Wherein
In order to be a collection of gaming participants,
in order to be a policy space, the policy space,
set of policies for game participant n, un(pn,p-n) Representing the utility function of a game participant n, where pnFor the transmission power of game participants n, p-nFor the transmission power of other game participants than game participant n, the proposed power control game is modeled as
Step seven: and (3) solving game Nash equilibrium, adopting a synchronous logarithmic linear learning algorithm, and converging to an optimal Nash equilibrium solution on the premise of no information interaction and coordination mechanism, namely minimizing the sum of the packet error rates of all D2D pairs under a competitive access mechanism.
2. The method of joint spectrum access and power control in D2D haptic communication of claim 1, wherein transmissions of source and destination ends of D2D are synchronized in time.
3. The method of claim 1, wherein the destination-side packet error rate in step two is determined by combining spectrum access and power control in D2D haptic communication 
And destination terminal rnReceived signal-to-noise ratio of
The relationship of (1) is:
wherein,
is a Gaussian Q function, t is an integral variable, dt is a first derivative of t,
l is the packet length, eta is the number of information bits transmitted, and
4. the method for joint spectrum access and power control in D2D haptic communication according to claim 3, wherein the destination r isnReceived signal-to-noise ratio of
The calculation method of (2) is as follows: assuming that D2D accesses resource block k for n at this time, the destination rnAt a received signal-to-noise ratio SNR of
Wherein,
as a source end enTransmit power of H (e)n,rn) As a source end enTo the destination end rnChannel gain of σ21/K is the probability that D2D accesses resource block K to i;
is a vector of the source transmit power,
is in a vector PeAll to the destination end rnHas a signal-to-noise ratio exceeding gammath1The source terminal set of (2); wherein, γth1To the destination end rnIf other sources go to rnSNR of greater than gammath1Then, it will be directed to the destination rnWill not otherwise interfere with the reception of rnThe reception of (2) causes an impact; e.g. of the typemThe source end of D2D pair m,
as a source end emTransmit power of H (e)m,rn) As a source end emTo the destination end rnThe channel gain of (a); e.g. of the typeiThe source end of pair i of D2D, 
As a source end eiTransmit power of H (e)i,rn) As a source end eiTo the destination end rnThe channel gain of (a);
since D2D randomly accesses resource block n under the contention mechanism, the received signal-to-noise ratio relative to K resource blocks is
5. The method of claim 1, wherein the source-end packet error rate in step three is determined by combining spectrum access and power control in D2D haptic communication
And source end enReceived signal-to-noise ratio of
The relationship of (1) is:
wherein,
is a Gaussian Q function, t is an integral variable, dt is a first derivative of t,
l is the packet length, η is the number of information bits transmitted, and
6. the method of claim 5, wherein the source e is a source e for joint spectrum access and power control in D2D haptic communicationnReceived signal-to-noise ratio of
The calculation method of (2) is as follows: under the contention mechanism, the received signal-to-noise ratio of D2D on K resource blocks to n is
Wherein,
to a destination end rnTransmit power of H (e)n,rn) As a source end enTo the destination end rnChannel gain of σ21/K is the probability that D2D accesses resource block K to i;
for the vector of transmit powers of the destination,
is in a vector PrDown, all to the source end enHas a signal-to-noise ratio exceeding gammath2In which γth2To the source end e nA signal-to-noise ratio threshold causing interference; r is a radical of hydrogenmFor the destination of D2D versus m,
to a destination end rmTransmit power of H (e)n,rm) As a source end enTo the destination end rmThe channel gain of (a); r isiFor the destination of D2D pair i,
to a destination end riTransmit power of H (e)n,ri) As a source end enTo the destination end riThe channel gain of (1).
7. The method for combined spectrum access and power control in D2D haptic communication of claim 1, wherein the policy set for game participant n in step six
Can be expressed as
Wherein, S is the maximum transmit power level that the source end and the destination end can adopt.
8. The method for combined spectrum access and power control in D2D haptic communication of claim 1, wherein the utility function u of game participant n in step sixn(pn,p-n) Is defined as
Wherein r isiFor the destination of D2D pair i,
to a destination end riThe packet error rate of (2); e.g. of the typejBeing the source end of D2D pair j,
as a source end ejThe packet error rate of (2);
as source end enSet of destinations affected when transmitting at transmit power S, i.e.
Wherein
In the same way, the method for preparing the composite material,
is as the destination terminal rnSet of source terminals affected when transmitting at the transmission power S, i.e.
Wherein
Therefore, unThe physical meaning is the sum of the packet error rates of all the sources and destinations affected by the game participant n.
9. The method for combined spectrum access and power control in D2D haptic communication according to claim 1, wherein the power control algorithm based on log-linear learning of synchronization in step seven is as follows:
initialization: setting the initial iteration time t as 0 and initializing all gamesParticipant's power vector p (0) ═ { p { (p) }1(0),...,pN(0) Therein of
And is
In addition, a binary indication variable is set
All game participants simultaneously perform the following steps:
t＝t+1
if b isn(t-1) ═ 0, game participant n updates its policy according to the following rules
Wherein p' is the strategy taken by the game participant n at time t;
representation collection
Number of middle elements, δnAn exploration rate for game participant n; if p isn(t)≠pn(t-1) setting bn(t) ═ 1; otherwise, set bn(t)＝0；
If b isn(t-1) ═ 1, game participant n updates its policy according to the following rules
Wherein, beta is a learning parameter,
and
the utility of the betting participant n at times t-1 and t-2 respectively,
then, set up bn(t)＝0；
If the constraint condition is satisfied
pnKeeping the same; if the constraint condition cannot be satisfied, p (t) ═ p (t-1) is set.
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