CN107426820A - Multi-user's game improves the resource allocation methods of efficiency in a kind of cognition D2D communication systems - Google Patents
Multi-user's game improves the resource allocation methods of efficiency in a kind of cognition D2D communication systems Download PDFInfo
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Abstract
The resource allocation methods that multi-user's game in a kind of cognition D2D communication systems improves efficiency are claimed in the present invention, are related to cognition wireless network.For the relatively low scene of the efficiency of the frequency spectrum that multiple D2D users are multiplexed multiple phone users in cognition network, the present invention proposes a kind of Resource Allocation Formula of the raising D2D communication system efficiencies based on game theoretical model, in the interference threshold constraints to be communicated no more than user, the resource of system is allocated using Noncooperative game model, and the equilibrium of efficiency and spectrum efficiency come being optimal user efficiency and is reached using Lagrange duality method and KKT alternative manners.
Description
Technical Field
The invention relates to the field of cognitive wireless communication, in particular to a resource allocation technology in a cognitive radio technology.
Background
Cognitive Radio (CR) is an effective method to solve the current spectrum resource shortage. D2D (Device-to-Device) communication technology facilitates more convenient data information exchange between geographically closely located mobile devices. The combination of cognitive radio technology and D2D communication to form cognitive D2D communication has many advantages, and has become a key technology of future mobile communication systems. There is still a wide space for studying resource allocation schemes of D2D communication systems in cognitive radio networks. At present, most of the traditional cognitive radio-based resource allocation schemes for D2D communication pay attention to the improvement of spectrum efficiency, and the optimization model is single. In the existing literature, the method for improving the energy efficiency design of users in the system is limited, the improvement of the overall energy efficiency is not considered, and the complexity of the scheme is high.
In cognitive D2D communication systems, multiplexing cellular user spectrum in an underlay manner by D2D users provides many benefits, such as proximity gain, multiplexing gain, and hop gain. D2D communication also faces new challenges in resource allocation issues because of co-channel interference caused by spectral reuse and because of the limited battery life of user equipment, which affects communication quality of service [ Wang M, Yan Z.A survey on security in D2D communications [ J ]. Mobile networks and Applications,2016:1-14 ]. Many literature studies methods for optimizing user energy efficiency in cognitive D2D Communication, methods for optimizing user energy efficiency in stages using context-aware D2D user discovery methods and resource allocation methods based on iterative power matching [ Zhou Z, Ma G, Zhang D, et al, energy-efficiency context-aware resource allocation in D2D communications: iterative matching approach [ C ]// Information Technology and Communication (ICTC),2016international conference on.ieee,2016:90-96 ]. Although some literature has been studied on energy efficiency resource allocation, satisfaction and fairness for most users are not considered. There are documents that solve the interference problem of D2D users to cellular users by using lagrangian duality theory and jointly optimize the energy efficiency of users [ Mumtaz S, Huq K M S, Rodriguez J, equivalent. energy-efficiency interference management in LTE-D2D communication [ J ]. IETSignal Processing,2016,10(3): 197-. However, many documents do not consider the competition between users and the balance of the spectrum efficiency of the system utility, and only pay attention to how to maximize the spectrum efficiency or to how to limit the interference between users while ignoring the characteristics of users themselves [ Golay N, Mansourfoil P, Molisch AF, ethyl, base-station-associated device-to-device Communications [ J ] IEEE Transactions on Wireless Communications,2014,13(7): 3665-.
Disclosure of Invention
In view of the defects, the invention utilizes the non-cooperative game model to allocate the resources of the system to achieve the purposes of optimizing the energy efficiency of the user and balancing the energy efficiency and the spectrum efficiency when the interference threshold constraint condition of the user communication is not exceeded. The resource allocation method for improving the energy efficiency of the multi-user game in the cognitive D2D communication system is provided, and the problems that in a cognitive D2D communication model, a D2D user multiplexes a cellular user frequency spectrum in an underlay mode, and a D2D user and a cellular user form a non-cooperative game for maximizing respective energy efficiency are considered, and the performances such as the total power consumption of the system and the throughput of the system are improved by improving the energy efficiency of the user and a link.
The technical solution of the invention comprises the following steps:
a resource allocation method for improving energy efficiency of a multi-user game in a cognitive D2D communication system is characterized by comprising the following steps:
s1: the method comprises the steps that a spectrum model of a plurality of D2D users in a cognitive wireless network multiplexing cellular users in an underlay mode is equivalent to a non-cooperative game model formed by a plurality of rational participants for maximizing respective energy efficiency; in this model there are 1 base station, multiple cellular users and multiple pairs of D2D users communicating scenario and M cellular and N D2D communication links in a single OFDM cell. The cellular users preferentially obtain the spectrum resources as the leaders of the game decision, and the D2D users can strive for the spectrum resources as the followers of the game decision after learning the decisions of the cellular users.
S2: the energy efficiency maximization problem of D2D users and nest users in the cognitive wireless network is obtained according to the design of the non-cooperative game model; wherein the energy efficiency maximization problem of the ith pair of D2D users is
The energy efficiency maximization problem of the kth cellular user is
In the formula:energy efficiency, r, for the ith pair of D2D usersi dFor the i-th pair D2D transmission rates,for the transmission power of the i-th pair D2D transmitter,the maximum transmit power constraint for the D2D user,for the energy efficiency of the kth cellular user,for the transmission rate of the kth cellular user,for the transmit power of the kth cellular user,the maximum transmit power constraint for a cellular user,the minimum transmission rate for the ith pair of D2D users,the minimum transmission rate for the kth cellular user,the sender policy for the ith pair of D2D users,for the policies on the senders of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs,for the policy of the kth cellular user,a policy for other cellular users than the kth cellular user among the M cellular users.
S3: and solving the energy efficiency maximization problem in the step S2 by adopting a Lagrangian dual method. The method comprises the following two contents of finding the power which maximizes the energy efficiency and finding the minimum Lagrangian factor corresponding to the optimal power.
In the scheme, the energy efficiency maximization problem based on the interference threshold is constructed under the constraint condition of the interference threshold of the cellular user, and the problem of maximizing the system energy efficiency is converted into a convex optimization problem by introducing a convex optimization theory; the energy efficiency maximization problem based on the interference threshold isFor the transmission power of the i-th pair D2D transmitter,for the interference channel gain between the transmitting end of the kth channel, the ith pair D2D and the base station,the maximum interference that the kth cellular user can tolerate.
The acquisition process of the energy efficiency maximization problem of the D2D user and the cellular user in the cognitive wireless network comprises the following steps:
firstly, respectively calculating the signal-to-interference-and-noise ratio SINR of a D2D user and a cellular user;
the SINR of the ith pair D2D on the kth channel is:
wherein,is the transmission power of the i-th pair D2D transmitting sides,is the transmit power of the kth cellular user,is the transmit power of the j-th pair D2D,is the channel gain between the i-th pair D2D,is the interference channel gain for the kth cellular user to the i-th pair D2D receiving end,is the interference channel gain of the j-th pair D2D on the i-th pair D2D receiving end, N0Is the noise power;
the signal to interference plus noise ratio (SINR) of the kth cellular user received by the base station is as follows:
wherein,is the channel gain between the kth cellular user and the base station,in the kth channel, the ith pair D2D is used for the interference channel gain between the transmitting end and the base station;
respectively calculating the total power consumed by the D2D user and the cellular user;
the i-th pair D2D has a transmission rate ofThe total power consumed by the i-th pair D2D is
The k cell uses a transmission rate ofThe total power consumed by the kth cellular subscriber, irrespective of the base station's circuit power consumption, is
Wherein p iscirCircuit power consumption of user, D2D generation of circuit power consumption at both sending end and receiving end, power amplification factor of η, 0<η<1；
Finally, respectively calculating the energy efficiency of the i pair of D2D user sending ends and the energy efficiency of the k cellular user;
the strategy of the sending end of the ith pair of D2D users is
Wherein,is the maximum transmit power constraint for the D2D user;
the strategy of the k cellular user is
Wherein,is the maximum transmit power constraint for the cellular user;
the strategies for the senders of the other D2D users except the ith pair of D2D users in the N pair of D2D are as follows:
the strategies for other cellular users than the kth cellular user among the M cellular users are:
for the maximum transmit power of the transmit end of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs,maximum transmit power for cellular users other than the kth cellular user among the M cellular users;
energy efficiency for ith pair of D2D usersIs composed of
Energy efficiency of kth cellular subscriberIs composed of
Power policy set P for D2D users and cellular usersdAnd PcAre respectively as
The invention has the advantages and beneficial effects that:
on the basis, the invention considers that the interference threshold constraint condition of user communication is not exceeded, and utilizes the non-cooperative game model to allocate the resources of the system to achieve the purposes of optimizing the energy efficiency of the user and balancing the energy efficiency and the spectrum efficiency, thereby well solving the problem of multi-user resource allocation in the actual network. The user game mode is adopted, so that the energy efficiency of the user is effectively improved; the Lagrange dual method is adopted, so that the average energy efficiency of the link can be effectively improved; compared with other suboptimal methods, the KKT iterative method has better effect of solving the energy efficiency resource distribution problem.
Drawings
FIG. 1 is a D2D communication model in a cognitive network;
FIG. 2 is a graph illustrating the impact of different iteration times on user energy efficiency;
FIG. 3 is a graph illustrating the effect of different iteration numbers on the average energy efficiency of a link;
FIG. 4 is a graph of the effect of D2D user number on the total power consumption of the system;
FIG. 5 is a graph of the effect of the number of cellular users on the average energy efficiency of D2D;
FIG. 6 compares the method of the present invention with two other methods.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, which include the following steps:
101. the system of the scheme is a cognitive D2D communication system model, as shown in FIG. 1, which is composed of a single OFDM cell, 1 base station, 2 cellular users (CUE1, CUE2) and 2 pairs of D2D. D2D users have cognitive capabilities, and D2D users can multiplex the spectrum resources of cellular users in an underlay mode to establish D2D links. Assume that there are M cellular communication links and N D2D communication links in this model.
102. According to fig. 1, the signal to interference plus noise ratio SINR of the ith pair D2D on the kth channel of the present invention is:
is the transmission power of the ith pair D2D to the transmitting end;is the transmit power of the kth cellular user;is the transmission power of the jth pair D2D to the transmitting end;is the channel gain between the ith pair of D2D pairs;is the interference channel gain for the kth cellular user to the receiving end of the ith pair of D2D;is the interference channel gain of the transmitting end of the j-th pair of D2D to the receiving end of the i-th pair of D2D; n is a radical of0Is the noise power; n is the number of D2D communication links.
103. The signal to interference plus noise ratio (SINR) of the kth cellular user received by the base station is as follows:
wherein,is the channel gain between the kth cellular user and the base station;in the kth channel, the ith pair D2D is responsible for the interference channel gain between the sender and the base station.
Then, the transmission rate that can be achieved for the i-th pair D2D isThe k-th cellular user can reach a transmission rate ofM is the number of cellular communication links.
Total power consumed by the i-th pair D2DThe two parts are included, one is the total transmission power when the M channels are multiplexed, and the other is the circuit power consumption of the transmitting end and the receiving end of the D2D pair. Thus, the total power consumed by the i-th pair D2D is:
wherein p iscirCircuit power consumption of user, circuit power consumption generated by both the sending end and the receiving end of D2D, and power consumption of all user circuits are the same. η is power amplification factor, generally 0<η<1。
The total power consumed by the kth cellular user comprises two parts, one part is the cellular user transmission power, and the other part is the circuit power consumption of the cellular user transmission end. The circuit power consumption of the base station is not considered here. Thus, the total power consumed by the kth cellular user is:
104. in the non-cooperative gaming communication model, each user is selfish and wishes to maximize their energy efficiency. Therefore, the strategy of the sending end of the ith pair of D2D users isWherein,is the maximum transmit power constraint for the D2D user.Representing the transmit side policy for the ith pair of D2D users, the policy for the kth cellular user is:a policy indicating the kth cellular user, wherein,is the maximum transmit power constraint for the cellular user. The strategies for the senders of the other D2D users except the ith pair of D2D users in the N pair of D2D are as follows:shows the strategy of the sender of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs,represents the maximum transmit power of the transmit end of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs. The strategies for other cellular users than the kth cellular user among the M cellular users are:representing the policy of other cellular users than the k-th cellular user among the M cellular users,indicating the transmit power of cellular users other than the k-th cellular user among the M cellular users,indicating the transmit power of cellular users other than the k-th cellular user among the M cellular users.
Energy efficiency for ith pair of D2D usersNot only dependent on the transmission power of the i-th pair of D2D usersBut also on the i-th pairThe strategy of the sender of the other D2D users except the D2D user is as follows:
the energy efficiency maximization problem of the ith pair of D2D users can be expressed by a mathematical expression:
then, the energy efficiency of the kth cellular subscriberComprises the following steps:
then, the energy efficiency maximization problem of the corresponding kth cellular user can be expressed as a mathematical expression:
thus, the energy efficiency of the entire system network is:
wherein, Pd，PcPower policy sets for D2D users and cellular users, respectively.
105. Will tolerate the k cellular userIs defined as the maximum interferenceThe energy efficiency maximization problem based on the interference threshold can be converted into:
and obtaining a Lagrangian dual problem by using a Lagrangian multiplication function and finding out an optimal solution of the function by using a KKT condition.
The following solution and analysis were made to the problems established above.
1. Energy efficiency maximization problem design
Since both the expression (6) and the expression (10) have fractional forms, their objective functions are both non-convex. To solve the closed-form solution of the objective function, we convert a non-convex function into a convex function using nonlinear fractional programming. Therefore, the maximum energy efficiency of the ith pair of D2D users can be defined asThe expression is as follows:
wherein,the optimal transmission power adopted by the ith pair of D2D users according to other user strategies.
Introduction 1: maximum energy efficiency for ith pair of D2D usersIf and only if the following equation is satisfied:
and (3) proving that: for arbitrary decision setWe can get:
by modifying equation (12), we can obtain:
therefore, whenWhile, typeHas a maximum value of 0, and can be obtained by solving the formula (6)After the syndrome is confirmed.
2, leading: to the formula
There is a unique solution
And (3) proving that: as can be seen from the formula (16),is a function ofContinuously monotonically decreasing. Thus, it is possible to provideWith a unique solutionBut also by a counter-proof method. After the syndrome is confirmed.
Similarly, we define the maximum energy efficiency of the kth cellular user asA lemma 3 similar to lemma 1 can be obtained.
And 3, introduction: maximum energy efficiency for kth cellular subscriberIf and only if the following equation is satisfied:
wherein,and the optimal transmission power adopted by the k cellular user according to other user strategies. And whereinIs not unique [ Dinkelbach W.on nonlinear fractional programming [ J ]].Managementscience,1967,13(7):492-498.]. After the syndrome is confirmed.
2. Maximum energy efficiency solution for cellular users and D2D users
Arbitrary resource allocation policy for ith pair of D2D usersComprises the following steps:
arbitrary resource allocation strategy for kth cellular userComprises the following steps:
thus, the Lagrangian multiplication function for the ith versus D2D user may be ordered as
Wherein, αi，βiIs the lagrangian factor under the constraint in equation (20).
The dual problem of equation (20) can be broken down into two sub-problems: firstly, a user adopts an optimal strategy to find power for maximizing energy efficiency; and secondly, finding the minimum Lagrange factor corresponding to the optimal power. Namely, the following problems are involved:
for any givenThe corresponding solution can be found:
wherein, the shape is { a }+Is taken to be the maximum value between (0, a).
When solving the minimization problem of the Lagrange factor, the method solves the problems by using a gradient method:
wherein tau is the number of iterations; mu.si,αAnd mui,βIs a very small parameter, μi,α>0，μi,β>0。
Likewise, the kth cellular user may be responsible for any given energy efficiencyThen the corresponding optimal transmit power solution can be found:
wherein,kand thetakIs the lagrangian factor under the constraint in equation (25).
It is known that a nash equilibrium solution exists when the utility function is a continuous quasi-convex function and the strategy set is a non-empty closed convex set. In formula (7) the molecule ri dIs aboutThe convex function of (a) is,k ∈ M. the denominator is aboutThe mapping function of (2). Therefore, the temperature of the molten metal is controlled,is a pseudo-convex function. The strategy set is as follows:is a non-empty closed convex set. There is a nash equilibrium for the non-cooperative gaming process. That is, the above method can converge to nash equalization, which is a power allocation decision set. The strategy achieves a balance that no user can individually improve its energy efficiency with some power decision. And the set of policies is
In the following, for simulation analysis of the resource allocation scheme for improving energy efficiency of the multi-user game in the cognitive D2D communication system, it is assumed that the system bandwidth is 10MHz, the radius of the cell is 500m, cellular users and D2D users are randomly distributed in the cell, the distance from the cellular user capable of being multiplexed with the link to the base station is within 100m, and the maximum power of the cellular user is within 100mThe D2D users form D2D pairs in the range of 50m, and the maximum transmission power of the D2D userNoise power spectral density is-174 dBm/Hz.. furthermore, the COST231-Hata urban propagation model PL after being corrected according to the communication reference between the base station and all users is 36.7+35 × lg (d),path loss between cellular users and D2D users (ref [ Andrews M, Kumaran K, Ramanan K, et al].IEEE Communications Magazine,2001,39(2):150-154.]) 66.5+40 × lg (D), and the distance between the D2D pairs is small, a free space model PL 38.4+20 × lg (D) is used.
Fig. 2 first discusses the impact of the number of iterations on user energy efficiency. D2D users and cellular users update their energy efficiency through iteration, and eventually converge to nash equilibrium. It can also be seen that the convergence speed of the cellular user is faster and the number of iterations required is less. And the number of the D2D users in the network is more than that of the cellular users, so the number of iterations required by the D2D users is more, and the convergence speed is slower.
Fig. 3 is a graph illustrating the effect of the number of game iterations on the average energy efficiency of a link. Simulation shows that compared with a Random method and an Energy-effect method, the method provided by the invention has better performance. This is due to the fact that the network model used in the present invention has better proximity gain and channel multiplexing gain. The higher proximity gain is due to the shorter distance between the D2D users of the present invention. The higher channel multiplexing gain is due to the more reasonable setting of the interference threshold of the present invention.
Fig. 4 shows the relationship between the total power consumption of the system and the number of D2D users. And the method provided by the invention is compared with the Random method. As the number of users increases, the total power consumption of the system increases. The method provided by the invention has the characteristic of low energy consumption under the condition of keeping the number of users to be constant, but the users in the Random method have to consume more power in order to ensure the communication quality of the users.
FIG. 5 is an average Energy efficiency relationship of D2D users when comparing the Energy-efficiency method with the method of the present invention as the number of CUEs changes, in case that the number of D2D users is 10 and 5. When the number of D2D users is reduced from 10 to 5, the energy efficiency of D2D users is also reduced. This is because the D2D sender detects a decrease in the number of better-matching D2D receivers, and therefore the D2D user energy efficiency is also decreased. As the number of CUE users increases, the cellular links that can be reused by D2D users increases, so the energy efficiency of D2D users also increases.
Fig. 6 is a comparison on the CDF curve for the total capacity of the system for the three methods. Under the condition of the same probability density cumulative function, the system total capacity performance of the method provided by the invention is superior to the performance of the Energy-efficiency method and the Random method, because the method jointly optimizes the sending power and the transmission rate of the user, so the performance is better. The Energy-effect method is superior to the Random method.
Claims (5)
1. A resource allocation method for improving energy efficiency of a multi-user game in a cognitive D2D communication system is characterized by comprising the following steps:
s1: the method comprises the steps that a spectrum model of a plurality of D2D users in a cognitive wireless network multiplexing cellular users in an underlay mode is equivalent to a non-cooperative game model formed by a plurality of rational participants for maximizing respective energy efficiency;
s2: the energy efficiency maximization problem of D2D users and nest users in the cognitive wireless network is obtained according to the design of the non-cooperative game model; wherein the energy efficiency maximization problem of the ith pair of D2D users is
<mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>max</mi> <mrow> <mo>{</mo> <mrow> <msubsup> <mi>U</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>E</mi> <mi>E</mi> </mrow> <mi>d</mi> </msubsup> <mrow> <mo>(</mo> <mrow> <msubsup> <mi>p</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>i</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>k</mi> </mrow> <mi>c</mi> </msubsup> </mrow> <mo>)</mo> </mrow> </mrow> <mo>}</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mtable> <mtr> <mtd> <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> </mrow> </mtd> <mtd> <mrow> <mi>C</mi> <mn>1</mn> <mo>:</mo> <msubsup> <mi>r</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>R</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>min</mi> </mrow> <mi>d</mi> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow></mrow> </mtd> <mtd> <mrow> <mi>C</mi> <mn>2</mn> <mo>:</mo> <mn>0</mn> <mo>&le;</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>max</mi> </mrow> <mi>d</mi> </msubsup> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> </mtable> </mfenced>
The energy efficiency maximization problem of the kth cellular user is
<mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>m</mi> <mi>a</mi> <mi>x</mi> <mo>{</mo> <msubsup> <mi>U</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>E</mi> <mi>E</mi> </mrow> <mi>c</mi> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>p</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>i</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>k</mi> </mrow> <mi>c</mi> </msubsup> <mo>)</mo> </mrow> <mo>}</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mtable> <mtr> <mtd> <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> </mrow> </mtd> <mtd> <mrow> <mi>C</mi> <mn>3</mn> <mo>:</mo> <msubsup> <mi>r</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>R</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>min</mi> </mrow> <mi>c</mi> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow></mrow> </mtd> <mtd> <mrow> <mi>C</mi> <mn>4</mn> <mo>:</mo> <mn>0</mn> <mo>&le;</mo> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>max</mi> </mrow> <mi>d</mi> </msubsup> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> </mtable> </mfenced>
In the formula:energy efficiency, r, for the ith pair of D2D usersi dFor the i-th pair D2D transmission rates,for the transmission power of the i-th pair D2D transmitter,the maximum transmit power constraint for the D2D user,for the energy efficiency of the kth cellular user,for the transmission rate of the kth cellular user,for the transmit power of the kth cellular user,the maximum transmit power constraint for a cellular user,the minimum transmission rate for the ith pair of D2D users,the minimum transmission rate for the kth cellular user,the sender policy for the ith pair of D2D users,for the policies on the senders of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs,for the policy of the kth cellular user,a policy for other cellular users than the kth cellular user among the M cellular users;
s3: and solving the energy efficiency maximization problem in the step S2 by adopting a Lagrangian dual method.
2. The method for allocating the energy-efficient resource in the cognitive D2D communication system based on the multiuser game as claimed in claim 1, wherein the method comprises the following steps: the method also comprises the steps of constructing an energy efficiency maximization problem based on the interference threshold under the constraint condition of the interference threshold of the cellular user, and converting the problem of maximizing the system energy efficiency into a convex optimization problem by introducing a convex optimization theory; energy efficiency based on interference thresholdThe maximization problem is For the transmission power of the i-th pair D2D transmitter,for the interference channel gain between the transmitting end of the kth channel, the ith pair D2D and the base station,the maximum interference that the kth cellular user can tolerate.
3. The method for allocating the energy-efficient resource in the cognitive D2D communication system based on the multiuser game as claimed in claim 1, wherein the method comprises the following steps: the acquisition process of the energy efficiency maximization problem of the D2D user and the cellular user in the cognitive wireless network comprises the following steps:
firstly, respectively calculating the signal-to-interference-and-noise ratio SINR of a D2D user and a cellular user;
the SINR of the ith pair D2D on the kth channel is:
<mrow> <msubsup> <mi>&gamma;</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>=</mo> <mfrac> <mrow> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <msubsup> <mi>h</mi> <mi>i</mi> <mi>k</mi> </msubsup> </mrow> <mrow> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <msubsup> <mi>h</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>i</mi> </mrow> <mi>k</mi> </msubsup> <mo>+</mo> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mi>j</mi> <mo>&NotEqual;</mo> <mi>i</mi> </mrow> <mi>N</mi> </msubsup> <msubsup> <mi>p</mi> <mi>j</mi> <mi>k</mi> </msubsup> <msubsup> <mi>h</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>i</mi> </mrow> <mi>k</mi> </msubsup> <mo>+</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </mfrac> </mrow>
wherein,is the transmission power of the i-th pair D2D transmitting sides,is the transmit power of the kth cellular user,is the transmit power of the j-th pair D2D,is the channel gain between the i-th pair D2D,is the interference channel gain for the kth cellular user to the i-th pair D2D receiving end,is the interference channel gain of the j-th pair D2D on the i-th pair D2D receiving end, N0Is the noise power;
the signal to interference plus noise ratio (SINR) of the kth cellular user received by the base station is as follows:
<mrow> <msubsup> <mi>&gamma;</mi> <mi>c</mi> <mi>k</mi> </msubsup> <mo>=</mo> <mfrac> <mrow> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <msubsup> <mi>h</mi> <mi>c</mi> <mi>k</mi> </msubsup> </mrow> <mrow> <msubsup> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </msubsup> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <msubsup> <mi>h</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>c</mi> </mrow> <mi>k</mi> </msubsup> <mo>+</mo> <msub> <mi>N</mi> <mn>0</mn> </msub> </mrow> </mfrac> </mrow>
wherein,is the channel gain between the kth cellular user and the base station,in the kth channel, the ith pair D2D is used for the interference channel gain between the transmitting end and the base station;
respectively calculating the total power consumed by the D2D user and the cellular user;
the i-th pair D2D has a transmission rate ofThe total power consumed by the i-th pair D2D is
<mrow> <msubsup> <mi>p</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>t</mi> <mi>o</mi> <mi>t</mi> <mi>a</mi> <mi>l</mi> </mrow> <mi>d</mi> </msubsup> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <mfrac> <mn>1</mn> <mi>&eta;</mi> </mfrac> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>+</mo> <mn>2</mn> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>i</mi> <mi>r</mi> </mrow> </msub> </mrow>
The k cell uses a transmission rate ofThe total power consumed by the kth cellular subscriber, irrespective of the base station's circuit power consumption, is
<mrow> <msubsup> <mi>p</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>t</mi> <mi>o</mi> <mi>t</mi> <mi>a</mi> <mi>l</mi> </mrow> <mi>c</mi> </msubsup> <mo>=</mo> <mfrac> <mn>1</mn> <mi>&eta;</mi> </mfrac> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <mo>+</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>i</mi> <mi>r</mi> </mrow> </msub> </mrow>
Wherein p iscirCircuit power consumption of user, D2D generation of circuit power consumption at both sending end and receiving end, power amplification factor of η, 0<η<1；
Finally, respectively calculating the energy efficiency of the i pair of D2D user sending ends and the energy efficiency of the k cellular user;
the strategy of the sending end of the ith pair of D2D users is
<mrow> <msubsup> <mi>p</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>|</mo> <mn>0</mn> <mo>&le;</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <mi>k</mi> <mo>&Element;</mo> <mi>M</mi> <mo>}</mo> <mo>,</mo> <mo>&ForAll;</mo> <mi>i</mi> <mo>&Element;</mo> <mi>N</mi> </mrow>
Wherein,is the maximum transmit power constraint for the D2D user;
the strategy of the k cellular user is
<mrow> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <mo>|</mo> <mn>0</mn> <mo>&le;</mo> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mi>c</mi> </msubsup> <mo>}</mo> <mo>,</mo> <mo>&ForAll;</mo> <mi>k</mi> <mo>&Element;</mo> <mi>M</mi> </mrow>
Wherein,is the maximum transmit power constraint for the cellular user;
the strategies for the senders of the other D2D users except the ith pair of D2D users in the N pair of D2D are as follows:
<mrow> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>i</mi> </mrow> <mi>d</mi> </msubsup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>p</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>|</mo> <mn>0</mn> <mo>&le;</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msubsup> <mi>p</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <mi>k</mi> <mo>&Element;</mo> <mi>M</mi> <mo>,</mo> <mi>j</mi> <mo>&Element;</mo> <mi>N</mi> <mo>,</mo> <mi>j</mi> <mo>&NotEqual;</mo> <mi>i</mi> <mo>}</mo> <mo>,</mo> <mo>&ForAll;</mo> <mi>i</mi> <mo>&Element;</mo> <mi>N</mi> </mrow>
the strategies for other cellular users than the kth cellular user among the M cellular users are:
<mrow> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>k</mi> </mrow> <mi>c</mi> </msubsup> <mo>=</mo> <mo>{</mo> <msubsup> <mi>p</mi> <mi>c</mi> <mi>l</mi> </msubsup> <mo>|</mo> <mn>0</mn> <mo>&le;</mo> <msubsup> <mi>p</mi> <mi>c</mi> <mi>l</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>p</mi> <mrow> <mi>l</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> <mi>c</mi> </msubsup> <mo>,</mo> <mi>l</mi> <mo>&Element;</mo> <mi>M</mi> <mo>,</mo> <mi>l</mi> <mo>&NotEqual;</mo> <mi>k</mi> <mo>}</mo> <mo>,</mo> <mo>&ForAll;</mo> <mi>k</mi> <mo>&Element;</mo> <mi>M</mi> </mrow>
for the maximum transmit power of the transmit end of the other D2D users than the ith pair of D2D users in the N pair of D2D pairs,maximum transmit power for cellular users other than the kth cellular user among the M cellular users;
energy efficiency for ith pair of D2D usersIs composed of
<mrow> <msubsup> <mi>U</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>E</mi> <mi>E</mi> </mrow> <mi>d</mi> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>p</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>i</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>k</mi> </mrow> <mi>c</mi> </msubsup> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msubsup> <mi>r</mi> <mi>i</mi> <mi>d</mi> </msubsup> <msubsup> <mi>p</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>t</mi> <mi>o</mi> <mi>t</mi> <mi>a</mi> <mi>l</mi> </mrow> <mi>d</mi> </msubsup> </mfrac> <mo>=</mo> <mfrac> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>log</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <msubsup> <mi>&gamma;</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> </mrow> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <mfrac> <mn>1</mn> <mi>&eta;</mi> </mfrac> <msubsup> <mi>p</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>+</mo> <mn>2</mn> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>i</mi> <mi>r</mi> </mrow> </msub> </mrow> </mfrac> </mrow>
Energy efficiency of kth cellular subscriberIs composed of
<mrow> <msubsup> <mi>U</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>E</mi> <mi>E</mi> </mrow> <mi>c</mi> </msubsup> <mrow> <mo>(</mo> <mrow> <msubsup> <mi>p</mi> <mi>i</mi> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>i</mi> </mrow> <mi>d</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mi>k</mi> <mi>c</mi> </msubsup> <mo>,</mo> <msubsup> <mi>p</mi> <mrow> <mo>-</mo> <mi>k</mi> </mrow> <mi>c</mi> </msubsup> </mrow> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <msubsup> <mi>r</mi> <mi>k</mi> <mi>c</mi> </msubsup> <msubsup> <mi>p</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>t</mi> <mi>o</mi> <mi>t</mi> <mi>a</mi> <mi>l</mi> </mrow> <mi>c</mi> </msubsup> </mfrac> <mo>=</mo> <mfrac> <mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>log</mi> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mrow> <mn>1</mn> <mo>+</mo> <msubsup> <mi>&gamma;</mi> <mi>c</mi> <mi>k</mi> </msubsup> </mrow> <mo>)</mo> </mrow> </mrow> <mrow> <mfrac> <mn>1</mn> <mi>&eta;</mi> </mfrac> <msubsup> <mi>p</mi> <mi>c</mi> <mi>k</mi> </msubsup> <mo>+</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>i</mi> <mi>r</mi> </mrow> </msub> </mrow> </mfrac> <mo>.</mo> </mrow>
4. The method for allocating the multi-user game energy-efficiency-improving resource in the cognitive D2D communication system according to any one of claims 1 to 3, wherein the method comprises the following steps: power policy set P for D2D users and cellular usersdAnd PcAre respectively as
5. The method for allocating the energy-efficient resource in the cognitive D2D communication system based on the multiuser game as claimed in any one of claims 4, wherein the method comprises the following steps: the solving of the energy efficiency maximization problem in the step S2 by using the lagrangian dual method includes finding a power for maximizing energy efficiency and finding a minimum lagrangian factor corresponding to the optimal power.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108093411A (en) * | 2018-01-10 | 2018-05-29 | 重庆邮电大学 | Scheduling of resource optimization method based on channel signature in D2D communication networks |
| CN108156624A (en) * | 2018-02-08 | 2018-06-12 | 南京邮电大学 | Interference dynamic optimization method based on game theory in super-intensive networking |
| CN108366427A (en) * | 2018-03-16 | 2018-08-03 | 西安电子科技大学 | Throughput of system and efficiency balance method based on power control in D2D communications |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012066433A1 (en) * | 2010-11-19 | 2012-05-24 | Nokia Corporation | Signaling mixed resource allocations for d2d communications |
| CN104066098A (en) * | 2013-03-18 | 2014-09-24 | 上海贝尔股份有限公司 | Method used for distributed wireless network and equipment thereof |
| CN104796991A (en) * | 2015-04-08 | 2015-07-22 | 南京邮电大学 | OFDMA (orthogonal frequency division multiple access) system resource distributing method based on potential game |
| CN104883727A (en) * | 2015-06-10 | 2015-09-02 | 中国人民解放军理工大学 | Power distribution method for D2D user rate maximization in cellular heterogeneous network |
| CN104954970A (en) * | 2015-05-28 | 2015-09-30 | 中国科学院计算技术研究所 | D2D (device to device) resource allocation method and system |
| WO2015152797A1 (en) * | 2014-04-01 | 2015-10-08 | Telefonaktiebolaget L M Ericsson (Publ) | System and method for obtaining and using device-to-device frequency-related capability and configuration preferences |
| WO2016166705A1 (en) * | 2015-04-15 | 2016-10-20 | Telefonaktiebolaget L M Ericsson (Publ) | Energy-efficient multi-hop communication schemes for wireless networks |
| CN106604398A (en) * | 2016-11-25 | 2017-04-26 | 北京邮电大学 | Resource distribution method and device |
-
2017
- 2017-05-27 CN CN201710391811.2A patent/CN107426820B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012066433A1 (en) * | 2010-11-19 | 2012-05-24 | Nokia Corporation | Signaling mixed resource allocations for d2d communications |
| CN104066098A (en) * | 2013-03-18 | 2014-09-24 | 上海贝尔股份有限公司 | Method used for distributed wireless network and equipment thereof |
| WO2015152797A1 (en) * | 2014-04-01 | 2015-10-08 | Telefonaktiebolaget L M Ericsson (Publ) | System and method for obtaining and using device-to-device frequency-related capability and configuration preferences |
| CN104796991A (en) * | 2015-04-08 | 2015-07-22 | 南京邮电大学 | OFDMA (orthogonal frequency division multiple access) system resource distributing method based on potential game |
| WO2016166705A1 (en) * | 2015-04-15 | 2016-10-20 | Telefonaktiebolaget L M Ericsson (Publ) | Energy-efficient multi-hop communication schemes for wireless networks |
| CN104954970A (en) * | 2015-05-28 | 2015-09-30 | 中国科学院计算技术研究所 | D2D (device to device) resource allocation method and system |
| CN104883727A (en) * | 2015-06-10 | 2015-09-02 | 中国人民解放军理工大学 | Power distribution method for D2D user rate maximization in cellular heterogeneous network |
| CN106604398A (en) * | 2016-11-25 | 2017-04-26 | 北京邮电大学 | Resource distribution method and device |
Non-Patent Citations (4)
| Title |
|---|
| ZHENYU ZHOU ET AL: "Energy-Efficient Resource Allocation for D2D Communications Underlaying Cloud-RAN-Based LTE-A Networks", 《 IEEE INTERNET OF THINGS JOURNAL》 * |
| 肖琦: "基于SCMA的D2D系统中无线资源管理研究", 《西南交通大学硕士学位论文》 * |
| 谢显中，李传文，杨和林: "认知D2D通信中基于博弈论的动态频谱分配方案", 《北京邮电大学学报》 * |
| 谢显中，田瑜，姚鑫凌，雷维嘉: "认知网络中D2D全双工通信的速率最大化功率分配算法", 《电子与信息学报》 * |
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