CN106911445B - Multi-dimensional resource optimization algorithm for incremental AF-OFDM cooperative network - Google Patents

Multi-dimensional resource optimization algorithm for incremental AF-OFDM cooperative network Download PDF

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CN106911445B
CN106911445B CN201710121101.8A CN201710121101A CN106911445B CN 106911445 B CN106911445 B CN 106911445B CN 201710121101 A CN201710121101 A CN 201710121101A CN 106911445 B CN106911445 B CN 106911445B
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CN106911445A (en
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张阳
韩芮雨
庞立华
栾英姿
张丹
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Guangzhou Its Communication Equipment Co ltd
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Xian University of Electronic Science and Technology
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L27/2601—Multicarrier modulation systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0044—Arrangements for allocating sub-channels of the transmission path allocation of payload
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
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Abstract

The invention belongs to the technical field of cooperative transmission, and discloses an incremental AF-OFDM cooperative network multidimensional resource optimization algorithm which comprises the steps of obtaining channel state information on subcarriers in all time slots, establishing an optimization model taking the network life m as a target according to the multidimensional resource optimization algorithm, calculating optimal power distribution on the subcarriers in all the time slots, determining optimization variables in a transmission process, including an incremental strategy, subcarrier pairing and relay selection, wherein in a useful data transmission process, a time slot is used, a source broadcasts data on the subcarriers with the calculated power, a relay and a target node receive the data, and according to the incremental strategy, a transmission strategy of a second time slot is determined, namely the selected relay forwards information to the target node on the paired subcarriers with the calculated power, or the source sends new data to the target node on the paired subcarriers with the calculated power.

Description

Multi-dimensional resource optimization algorithm for incremental AF-OFDM cooperative network
Technical Field
The invention belongs to the technical field of cooperative transmission, and particularly relates to an algorithm for multi-dimensional resource optimization allocation of an incremental AF-OFDM cooperative network.
Background
At present, in a relay cooperative network with limited energy, a resource allocation scheme in a cooperative transmission mode already considers power allocation on multiple carriers, or jointly considers power allocation and relay selection strategies, or jointly considers power allocation and subcarrier pairing, or jointly considers power allocation and relay selection strategies, and subcarrier pairing, so as to maximize system energy efficiency or system performance, wherein a transmission technical scheme generally adopts an amplify-and-forward (AF), a decode-and-forward (DF), or a hybrid amplify-and-decode-and-forward (DF) protocol, and aiming at a convex optimization problem that an established optimization model is mostly, a traditional method for solving the convex optimization problem (an optimization toolkit, a KKT condition) is adopted, a small number of models established in the technical scheme also have a non-convex optimization problem, and a lagrange dual problem is adopted for solving.
However, problems exist in the existing technical scheme, that is, only power distribution, relay selection and or a plurality of optimization variables in subcarrier matching cannot be considered to the maximum extent to achieve an optimization target, the existing technical scheme is considered under the condition of energy limitation, system energy efficiency or system performance maximization is necessary to achieve, but network service life is critical to be prolonged, a traditional forwarding protocol is adopted, due to the half-duplex characteristic of relays, spectrum efficiency is halved, although system performance is improved, spectrum efficiency is reduced, due to the fact that the considered optimization variables are few, a mathematic optimization model is simple to establish, although a lagrangian dual problem is adopted in a small number of technical schemes to solve a non-convex optimization problem, specific and deep verification is not carried out on the condition that an original problem is converted into a dual problem to be solved, namely, a dual gap is zero theory.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithms.
The scheme provided by the invention considers a multi-dimension optimization variable increment strategy, relay selection, subcarrier pairing and power distribution, takes the service life of a network as an optimization target, and considers an increment AF-OFDM forwarding strategy, so that new information can be effectively transmitted by using a second time slot, and the frequency efficiency is improved. For solving the established non-convex optimization problem, the theory that the dual gap is zero is verified through simulation.
The multi-dimensional resource optimization algorithm of the incremental AF-OFDM cooperative network comprises the following steps:
step , obtaining the channel state information on each subcarrier in all time slots, source node,the first relay node and the destination node use S and R respectivelylD denotes, let link S → Rl，Rl→D，
Figure BDA00012370721000000214
，and
Figure BDA00012370721000000215
The quasi-static channel parameters are hs,l,i，hl,d,j，hs,d,iAnd h ands,d,j；
step two, establishing an optimization model taking the network life m as a target according to a multi-dimensional resource optimization algorithm, and calculating the optimal power distribution on each subcarrier in all time slots
Figure BDA0001237072100000023
Figure BDA0001237072100000024
And determining that the optimization variable in the transmission process comprises an increment strategySubcarrier pairing (i, j), relay selection
Figure BDA0001237072100000026
The multi-dimensional resource optimization algorithm introduces an increment strategy binary variable
Figure BDA0001237072100000027
It shows that this transmission uses relay forwarding or direct transmission in two time slots, i, j is 1,2, … N shows that complete transmission processes are completed in the ith, j in two time slots, and another binary variablesIndicating the first relay forwarding information is selected, and the subcarriers between two time slots are paired, each subcarrier can only select no more than 1 relay node to transmit information, namely the set variable should satisfy the following conditionsConditions are as follows:
Figure BDA0001237072100000029
Figure BDA00012370721000000210
Figure BDA00012370721000000211
step three, information data transmission is started, at th time slot, the source node uses the calculated transmission power
Figure BDA00012370721000000212
Figure BDA00012370721000000213
data are broadcast on each subcarrier, the relay and the destination node receive the data, and the transmission strategy of the second time slot is determined according to the increment strategy, namely the selected relay node has power
Figure BDA0001237072100000031
Forwarding information to destination node, or source node, on paired subcarriers j
Figure BDA0001237072100000032
And sending new data to the destination node on the paired subcarrier j, so that complete information transmission processes are realized.
And , performing joint optimization by comprehensively considering a plurality of optimization variables such as increment strategy, relay selection, subcarrier pairing and power distribution by the multi-dimensional resource optimization algorithm, so as to maximize the service life of the network.
And , converting the original problem into a dual problem to solve the optimal power distribution, wherein the multi-dimensional resource optimization model is a non-convex optimization problem and adopts a Lagrangian dual problem to solve:
Figure BDA0001237072100000033
whereinΓA(t)＝τl,n(t)+γi(t)，
Figure BDA0001237072100000035
[x]+＝max(0,x),μt,υlκ is a lagrange multiplier;
Figure BDA0001237072100000036
transmitting power for direct transmission and retransmission for two time slot sources and relays, respectively αl,i＝|hs,l,i|2/σ2,βl,j＝|hl,d,j|2/σ2,γi＝|hs,d,i|2/σ2,andγj＝|hs,d,j|2/σ2Are respectively S → Rl，Rl→D，
Figure BDA0001237072100000037
，and
Figure BDA0001237072100000038
Link signal to noise ratio.
And , calculating the optimal variable with zero dual gap.
And , establishing an optimization objective function of the multi-dimensional resource optimization model, wherein the optimization objective function is integers m, the number of times of realizing the complete information transmission process under the constraint of limited energy is represented, and the whole optimization process adopts an outer layer and inner layer loop nesting method.
, the outer loop uses dichotomy to find the optimal m value, the inner loop uses dual decomposition and sub-gradient algorithm to obtain the optimal power distribution and other resource optimization configuration, and finally determines the optimization variable dimension including increment strategyRelay selection
Figure BDA0001237072100000042
Subcarrier pairing (i, j) and power allocation
Figure BDA0001237072100000043
Another objective of the invention is to provide relay cooperative transmission systems applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm.
Another objective of the invention is to provide mobile terminals applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm.
Another objective of the invention is to provide relay transmitters applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm.
The method has the advantages that on the basis of not increasing the cost of system equipment, through the design of a transmission strategy, a plurality of dimensionality increment strategies, relay selection, subcarrier pairing and power distribution optimization are considered, the survival time of a network is prolonged, the service life of the network is realized to be 148.6% of the service life of the network of the optimization scheme of the traditional AF forwarding protocol, relay selection, subcarrier pairing and power distribution, the increment strategy is considered, a source node sends new data under a direct transmission mode in a second time slot, the spectrum utilization rate is improved by 1 time, the -shaped convex optimization problem can be solved by adopting a KKT condition, but the problem is a complex non-convex optimization problem, the Lagrangian pair problem is adopted for solving, the establishment of a strong dual theory (dual gap is zero) is specifically and deeply verified, the original problem can be converted into a dual problem, and a basis is provided for solving of a similar mathematical model.
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Fig. 1 is a flowchart of an incremental AF-OFDM cooperative network multidimensional resource optimization algorithm provided in an embodiment of the present invention.
Fig. 2 is a specific flowchart for implementing an incremental AF-OFDM-based forwarding scheme optimization algorithm according to an embodiment of the present invention.
Fig. 3 is a diagram of a cooperative transmission system based on incremental AF-OFDM forwarding according to an embodiment of the present invention.
Fig. 4 is a mathematical model diagram of multi-relay cooperation based on an incremental AF-OFDM forwarding scheme according to an embodiment of the present invention.
FIG. 5 is a diagram of a verification simulation with zero dual gap, provided by an embodiment of the present invention.
Fig. 6 is a graph comparing network lifetime of an incremental AF-OFDM cooperative network multidimensional resource optimization algorithm provided in an embodiment of the present invention with other algorithms.
Detailed Description
For purposes of making the objects, aspects and advantages of the present invention more apparent, the present invention will now be described in detail at with reference to the following examples.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
As shown in fig. 1, the incremental AF-OFDM cooperative network multidimensional resource optimization algorithm provided by the embodiment of the present invention includes the following steps:
s101, introducing an increment strategy binary variable, wherein the binary variable is used for indicating a second time slot transmission mode, and when the th time slot is a direct transmission mode, the second time slot sends new information to a destination node;
s102: the multi-carrier cooperative transmission system finds the best matched subcarrier pair, realizes information transmission of two hops and realizes an information transmission process with lower energy consumption;
and S103, under the condition that the optimal power is distributed on each subcarrier of each transmission time slot and the system energy is , the user rate requirement is met, and the service life of the network is maximized.
The application of the principles of the present invention will now be described in further detail with reference to the drawings.
As shown in fig. 2, the multidimensional resource optimization model based on the incremental amplification forwarding-orthogonal frequency division multiplexing (AF-OFDM) forwarding scheme to maximize the network lifetime and the solving process thereof in the embodiment of the present invention include the following steps:
step , obtaining the channel state information of each sub-carrier in all time slots, the source node, the l-th relay node and the destination node use S, R respectivelylD denotes, let link S → Rl，Rl→D，
Figure BDA0001237072100000051
，and
Figure BDA0001237072100000052
The quasi-static channel parameters are hs,l,i，hl,d,j，hs,d,iAnd h ands,d,j；
step two, establishing an optimization model taking the network life m as a target according to a multi-dimensional resource optimization algorithm, and calculating the optimal power distribution on each subcarrier in all time slots
Figure BDA0001237072100000062
And determining during transmission, including an incremental policySubcarrier pairing (i, j), relay selection
Figure BDA0001237072100000064
Step three, designing an information transmission scheme, time slot 1, and the source node using the calculated transmission power
Figure BDA0001237072100000065
Figure BDA0001237072100000066
data are broadcast on each subcarrier, the relay and the destination node receive the data, time slot 2 is determined according to the increment strategy, the selected relay node forwards information to the destination node on the subcarrier matched with the time slot by power or the source node is matched with the time slotOn the subcarrier of the pair with power
Figure BDA0001237072100000067
And sending new data to the destination node to realize times of complete information transmission process.
Fig. 3 shows a cooperative transmission network consisting of base stations, a plurality of relays and mobile terminals, fig. 4 is a mathematical model diagram of a simplified cooperative transmission system, and each relay node RlWhen the direct link between the source node S and the destination node D is very weak, then they may pass through the relay node RlTo complete the communication. Such a scenario may occur when the direct link is obstructed by an obstacle, such as a mountain or the like. Assuming that each link in the network experiences quasi-static fading, i.e. the channel remains unchanged for multiple transmission time slots, the noise on all channels is independent and equally distributed white gaussian noise, subject to CN (0, σ)2) The communication process adopts OFDM multi-carrier transmission, the number of carriers is N, the whole transmission process is divided into two hops, the th hop source node broadcasts information on sub-carriers, the relay node and the destination node receive the information, the second hop relays the information received from the source node to the destination end by adopting an amplification forwarding protocol according to the channel condition, and the destination end forms a received signal by using a Maximum Ratio Combining (MRC) mode S → Rl，Rl→D，And
Figure BDA0001237072100000069
the channel coefficient on each link is hs,l,i，hl,d,j，hs,d,iAnd h ands,d,jthe corresponding link signal-to-noise ratio may be represented as α respectivelyl,i＝|hs,l,i|2/σ2,βl,j＝|hl,d,j|2/σ2，γi＝|hs,d,i|2/σ2And γj＝|hs,d,j|2/σ2。
A multi-relay cooperation system based on an increment AF-OFDM forwarding scheme is characterized in that an increment strategy binary variable is introduced firstly
Figure BDA00012370721000000610
Wherein i, j is 1,2, … N.
Figure BDA00012370721000000611
Indicating a direct transmission mode, source node is powered at th time slot
Figure BDA0001237072100000071
Sending information to a destination node on the ith subcarrier;
Figure BDA0001237072100000072
representing a relay AF forwarding mode, source nodes supply power at th time slotAnd transmitting the information to the relay node on the ith subcarrier. Binary variable
Figure BDA0001237072100000074
And
Figure BDA0001237072100000075
similarly, the second slot transmission mode is indicated when
Figure BDA0001237072100000076
At time, the selected relay node is powered on
Figure BDA0001237072100000077
Forwarding information to the destination node on subcarrier j, otherwise the source node will be powered
Figure BDA0001237072100000078
new messages are sent to the destination node on sub-carrier j
Figure BDA0001237072100000079
The second time slot will send new messages to the destination node, which makes full use of bandwidth resources and further increases the spectrum utilization rate .
Secondly, the multi-carrier cooperative transmission system finds the best matching (i, j) sub-carrier pair, realizes the information transmission of two hops, realizes the information transmission process with lower energy consumption, assumes that the information sent by the source is transmitted on N sub-carriers, and the relay forwarding is also on N sub-carriers, can obtain higher mutual information if the two-hop channels are paired according to the actual size of the two-hop channels, the following gives theories to deduce why the two-hop channels are advantageous, without losing generality, the invention assumes two sub-channels, and the th hop channel coefficient is aiI is 1,2 and a1＞a2The second hopping channel coefficient is bjJ is 1,2 and b1＞b2. Definition Ai＝Psai，Bi＝PrbiThe rate of realization of the out-of-order pairing of subcarriers is smaller than the rate when the subcarriers are best matched, i.e.:
Figure BDA00012370721000000710
this theory extrapolates to the N sub-carrier case, A1≥A2≥…≥ANAnd B1≥B2≥…≥BNAnd (6) pairing.
Again, another binary variables
Figure BDA00012370721000000711
Indicating that the first relay forwarding information is selected;
Figure BDA00012370721000000712
indicates that subcarrier pair (i, j) is allocated to relay node RlTo avoid interference, it is ensured that subcarriers between two time slots are paired, and each subcarrier can only select no more than 1 relay node to transmit information, i.e., the set variables should satisfy the following conditions:
Figure BDA00012370721000000713
Figure BDA00012370721000000714
Figure BDA0001237072100000081
and finally, under the condition that the optimal power is distributed on each subcarrier of each transmission time slot and the system energy is , the user rate requirement is met, and the service life of the network is maximized.
The achievable rate for an -pass complete transmission system is solved as follows:
when in use
Figure BDA0001237072100000082
And is
Figure BDA0001237072100000083
Time, relay RlThe receiving end equivalent signal-to-noise ratio obtained by adopting the AF forwarding mode is as follows:
Figure BDA0001237072100000084
mutual information in the cooperation mode is as follows:
Figure BDA0001237072100000085
for ease of solution, the above equation is approximated as:
Figure BDA0001237072100000086
this approximation is reasonable, has negligible impact on the results, and has applications in many studies.
Mutual information in the non-cooperative mode may be expressed as follows:
time slot is
Figure BDA0001237072100000087
The second time slot is
Figure BDA0001237072100000088
The invention adopts the maximum ratio combining technology, and the average reachable speed from the source node to the destination node after the bandwidth is classified into is as follows:
the factor 1/2 exists because the transmission of each information symbol actually occupies two slots, resulting in a -half reduction in spectral efficiency in each direction, but because of the fact that
Figure BDA00012370721000000810
The presence of (a) can improve spectral efficiency.
The setting of four optimization variables is described previously herein, and the following section is the construction and solution of the mathematical model of the present invention.
The invention defines the service life of the network as the time T for the network to run under the condition of meeting the requirement of the QoS of the user, transmission processes TsCan be divided into two equal time slots TpTherefore, the objective function m for optimizing the network life can be converted into the number of complete transmission processes, i.e. T ═ m · 2Tp. In addition, the
Figure BDA0001237072100000091
Represents the node k, k ∈ { S, RlTotal energy of }, RdRepresenting the lowest rate requirement, the model was built as follows:
wherein the multidimensional optimization variable X (t) { X (1), …, X (t), X (m);
Figure BDA0001237072100000093
the model is mixed integer nonlinear programming problems, and the original problem is difficult to solve due to the discrete characteristic of an optimization target and the existence of binary variables.
The established mathematical optimization models are non-convex optimization models, the solving is complex, the solving of the original problem can be converted into the solving of the dual problem on the premise of ensuring the zero dual gap of the non-convex optimization problem, FIG. 5 is the verification that the dual gap is zero, the dual gap is zero when the iteration times tend to be infinite, the maximum value of the original problem is equivalent to the minimum value of the Lagrangian dual problem, the verification process of the strong dual theory is as follows, the current optimal value m is set to be 150, the iteration times are h to be 4000, the iteration step length is set to be variable and reduced
Figure BDA0001237072100000101
It can be seen from the data in the figure that the lagrangian function value is less than 151, getting closer to m when iterating to 3500.
The optimization problem is solved by adopting a lagrangian dual problem as follows:
given m, the lagrangian function of the optimization problem is:
Figure BDA0001237072100000102
wherein mu is [ mu ]1，μ2，…，μm],υ＝[υ1，υ2，…，υl]κ is a lagrange multiplier, i.e., a dual variable;
such a dual function is represented as:
Figure BDA0001237072100000103
the dual problems of the original optimization problem are as follows:
Figure BDA0001237072100000104
the optimization problem can be decomposed into two sub-problems, optimizing power allocation and determining binary variables.
Sub-problem 1 is:
Figure BDA0001237072100000105
wherein
Figure BDA0001237072100000106
The optimal power allocation on each subcarrier can be obtained by solving the above equation. Sub-problem 1 is specifically:
Figure BDA0001237072100000107
at the moment, given dual variables are assumed to obtain the optimal power solution
Figure BDA0001237072100000111
The following were used:
Figure BDA0001237072100000112
wherein
Figure BDA0001237072100000113
Figure BDA0001237072100000114
Sub-problem 2 is:
Figure BDA0001237072100000115
wherein
Figure BDA0001237072100000116
Similar to sub-problem 1, sub-problem 2 is specifically:
Figure BDA0001237072100000117
wherein
Figure BDA0001237072100000121
Figure BDA0001237072100000122
To maximize the Lagrangian function the invention selects the best relay, even though
Figure BDA0001237072100000123
Maximized Relay*：
Figure BDA0001237072100000124
And when the subcarrier pairing variable is optimized, finding the optimal subcarrier pair (i, j) by adopting Hungarian matching:
Figure BDA0001237072100000125
the binary variable can be determined by the method
Figure BDA0001237072100000126
And user rate under optimal power allocation
Figure BDA0001237072100000127
In order to solve the dual problem, the dual variable is updated by adopting a sub-gradient algorithm, wherein the gradient is as follows:
Figure BDA0001237072100000128
Figure BDA0001237072100000129
Figure BDA00012370721000001210
wherein
Figure BDA00012370721000001211
Having been solved from the above, the dual variable update formula is:
μt(in+1)＝[μt(in)-η(in)Δμt]+；
κ(in+1)＝[κ(in)-θ(in)Δκ]+；
Figure BDA00012370721000001212
where in is the number of iterations, η (in), θ (in),
Figure BDA00012370721000001213
the iteration step size is the smallest drop.
Fig. 6 is a simulation diagram of the multidimensional optimization algorithm of the present invention, and the global optimum curve is the algorithm proposed by the present invention, which shows that the network lifetime is superior to other optimization algorithms. As the minimum constraint rate increases, the network lifetime value decreases.
The invention aims at maximizing the service life of the network, provides multi-dimensional resource optimization algorithms based on an incremental amplification forwarding-orthogonal frequency division multiplexing (AF-OFDM) forwarding scheme, and prolongs the survival time of the network.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (9)

1, kinds of increment AF-OFDM cooperation network multi-dimensional resource optimization algorithm, characterized in that, the said increment AF-OFDM cooperation network multi-dimensional resource optimization algorithm includes the following steps:
step , obtaining the channel state information of each sub-carrier in all time slots, the source node, the l-th relay node and the destination node use S, R respectivelylD represents that a link from a source node S to a relay node R is setlRelay node RlTo the destination node D, the source node S goes from the subcarrier i to the destination node D, and the quasi-static channel parameters of the source node S from the subcarrier j to the destination node D are h respectivelys,l,i(t)，hl,d,j(t)，hs,d,i(t) and hs,d,j(t), the quasi-static channel parameters are assumed to be constant in cooperative transmissions divided into two slots, the argument t may be omitted, and the quasi-static channel parameters may be written as h in cooperative transmissionss,l,i，hl,d,j，hs,d,iAnd hs,d,j；
Step two, establishing an optimization model taking the network life m as a target according to a multi-dimensional resource optimization algorithm, and calculating the optimal power distribution on each subcarrier in all time slots
Figure FDA0002236839960000011
Pl j,(C,2)(t) and determining optimization variables in the transmission process comprises an incremental strategy
Figure FDA0002236839960000012
Subcarrier pairing (i, j), relay selection
Figure FDA0002236839960000013
The multi-dimensional resource optimization algorithm introduces an increment strategy binary variable
Figure FDA0002236839960000014
Respectively representing two time slot acquisitions of the current transmissionRepeating or direct transmission, i 1,2, …, N and j 1,2, …, N representing complete transmission process, wherein N is N sub-carriers, N is binary variable variables
Figure FDA0002236839960000015
The method comprises the steps of selecting the ith relay forwarding information, pairing subcarriers between two time slots, and selecting no more than 1 relay node for transmitting information by each subcarrier, wherein the set variables meet the following conditions:
Figure FDA0002236839960000016
Figure FDA0002236839960000017
Figure FDA0002236839960000018
step three, information data transmission is started, at th time slot, the source node uses the calculated transmission power
Figure FDA0002236839960000019
Figure FDA0002236839960000021
data are broadcast on each subcarrier, the relay and the destination node receive the data, and the transmission strategy of the second time slot is determined according to the increment strategy, namely the selected relay node has the power Pl j,(C,2)(t) forwarding information to a destination node, or source node, on the paired subcarriers j
Figure FDA0002236839960000022
And sending new data to the destination node on the paired subcarrier j, so that complete information transmission processes are realized.
2. The incremental AF-OFDM cooperative network multidimensional resource optimization algorithm of claim 1, wherein the multidimensional resource optimization algorithm performs joint optimization for comprehensively considering a plurality of optimization variables of an incremental strategy, relay selection, subcarrier pairing and power allocation, so as to maximize the network lifetime.
3. The incremental AF-OFDM cooperative network multidimensional resource optimization algorithm of claim 1, wherein the multidimensional resource optimization model is a non-convex optimization problem, and is solved by a lagrangian dual problem; firstly, converting an original problem into a dual problem to solve optimal power distribution:
Figure FDA0002236839960000023
wherein
Figure FDA0002236839960000024
ΓA(t)＝τl,n(t)+γi(t)，
Figure FDA0002236839960000025
[x]+＝max(0,x),μt,υlκ is a lagrange multiplier;
Figure FDA0002236839960000026
Pl j,(C,2)(t) transmit powers for direct transmission and forwarding for two slot sources and relays, respectively; the noise on all channels is additive white Gaussian noise which is independently and identically distributed, the mean value is 0, and the variance is sigma2；αl,i(t)＝|hs,l,i(t)|/σ2，βl,j(t)＝|hl,d,j(t)|/σ2，γi(t)＝|hs,d,i(t)|/σ2And γj(t)＝|hs,d,j(t)|/σ2Respectively a link source node S to a relay node RlRelay node RlTo the eyesAnd the source node S is connected with the destination node D from the subcarrier i, and the source node S is connected with the link signal-to-noise ratio of the destination node D from the subcarrier j.
4. The incremental AF-OFDM cooperative network multidimensional resource optimization algorithm of claim 3, wherein dual gaps are zero when calculating optimization variables.
5. The incremental AF-OFDM cooperative network multidimensional resource optimization algorithm of claim 1, wherein the objective function of optimization established by the multidimensional resource optimization model is integers m, which represent the number of times of implementing a complete information transmission process under the constraint of limited energy, and the whole optimization process adopts an outer layer and inner layer loop nesting method.
6. The incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm of claim 5, wherein the outer loop finds an optimal m value by a dichotomy; the inner layer circularly uses dual decomposition and a sub-gradient algorithm to obtain the optimal power allocation and other resource optimization configurations, and finally, the determination of the optimization variable dimension comprises an increment strategy
Figure FDA0002236839960000031
Relay selectionSubcarrier pairing (i, j) and power allocation
Figure FDA0002236839960000033
Pl j,(C,2)(t)。
7, relay cooperative transmission systems applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm of any of claims 1 to 6.
8, kinds of mobile terminals applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm of any of claims 1 to 6.
9, relay transmitters applying the incremental AF-OFDM cooperative network multi-dimensional resource optimization algorithm of any of claims 1 to 6.
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