CN114339976A - Resource allocation method meeting time delay constraint in unmanned aerial vehicle ad hoc network - Google Patents
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Abstract
The invention discloses a resource allocation method meeting time delay constraint in an unmanned aerial vehicle ad hoc network, which mainly solves the problems that each unmanned aerial vehicle obtains self transmission capability by simply and blindly increasing transmission power and frequency bandwidth, so that interference to other unmanned aerial vehicles in the unmanned aerial vehicle ad hoc network is caused, energy of the unmanned aerial vehicle is wasted, time delay is caused by retransmission data, and the like; the main implementation scheme comprises: 1) setting a revenue function of unmanned aerial vehicle nodes in the unmanned aerial vehicle ad hoc network according to an interval protection condition of communication channel frequency in the unmanned aerial vehicle ad hoc network and an expected reachable condition of channel transmission capacity; 2) and setting a cost function of unmanned aerial vehicle nodes in the unmanned aerial vehicle ad hoc network according to the condition that the current frequency bandwidth and the transmitting power of each unmanned aerial vehicle and the maximum usable frequency bandwidth and the maximum transmitting power are adjusted and optimized by the unmanned aerial vehicle ad hoc network.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a method for optimally distributing network resources such as transmission power, spectrum bandwidth and the like to each node of an unmanned aerial vehicle under the condition that retransmission times are met as a time delay guarantee constraint condition in an unmanned aerial vehicle ad hoc network.
Background
In recent years, the battlefield application of the unmanned aerial vehicle is more and more emphasized, and the tactical internet of the unmanned aerial vehicle becomes an important development direction of battlefield communication in the future. Unmanned aerial vehicle Ad-Hoc Network (UANET) has come under such a demand, and is developed based on traditional Mobile Ad-Hoc Network (MANET). UANET can deploy fast and provide safe and reliable, anti-interference, the strong communication network of survivability, can effectively reduce single unmanned aerial vehicle's load and expense, can assist other current battlefield communication modes simultaneously, promotes unmanned aerial vehicle operation platform combat radius and combat efficiency by a wide margin. For a large scale of the unmanned aerial vehicle cluster network, wireless resource management is usually performed on the whole ad hoc network unmanned aerial vehicle node, and a large network delay and a high routing overhead caused by a planar topological structure are avoided through resource allocation, so that the utilization rate of shared wireless channel resources is improved, the application of network bandwidth is optimized, and the routing overhead can be reduced. Because the networking communication of the unmanned aerial vehicle cluster has the characteristics of distributed environment, node mobility, dynamic change of network topology, unstable link and the like, the delay sensitive application guarantee capability of the unmanned aerial vehicle ad hoc network needs to be enhanced. The game theory brings a brand-new thought and method for analyzing and designing a wireless communication system, interdisciplinary intersection and application can often cause great progress and innovation in theory and technology, and the further research on resource allocation application of the game theory in the unmanned aerial vehicle ad hoc network has important theoretical significance.
Disclosure of Invention
The invention aims to solve the main technical problems that: in consideration of practical application scenes, each unmanned aerial vehicle of the unmanned aerial vehicle ad hoc network selects proper frequency bandwidth and transmitting power under the condition of satisfying time delay constraint conditions within limited transmission times to enable the transmission capability of each unmanned aerial vehicle to achieve balanced optimization, so that the unmanned aerial vehicles are restrained from acquiring self transmission capability by simply and blindly increasing the transmitting power and the frequency bandwidth, interference on other unmanned aerial vehicles in the unmanned aerial vehicle ad hoc network and waste of self energy are avoided, and network performance of each node of the unmanned aerial vehicle ad hoc network in the communication process is guaranteed.
The technical scheme provided by the invention comprises the following steps:
(1) in an unmanned aerial vehicle ad hoc network with N unmanned aerial vehicles in total communicating with ground equipment, according to the interval protection condition of communication channel frequency and the expected reachable condition of channel transmission capacity in the unmanned aerial vehicle ad hoc network, a revenue function of an unmanned aerial vehicle node i in the unmanned aerial vehicle ad hoc network is established, and the mathematical description is as follows:
wherein, alpha is the channel interval protection bandwidth, beta is the channel capacity reachable factor, piIndicating the transmission power of the ith drone, wiIndicating the frequency bandwidth, h, allocated to the ith droneiIndicating the channel gain, N, from the ith user to the terrestrial device0/2 is the additive white Gaussian noise power spectrum density, I, of the user receiving endiFor receiver interference to drone i, μ is the interference factor of the signal between drone nodes, γiFor a receiver SINR corresponding to UAV i, the mathematical description is as follows:
(2) according to the condition that the current frequency bandwidth and the transmitting power of each unmanned aerial vehicle and the maximum usable frequency bandwidth and the maximum transmitting power of the unmanned aerial vehicle ad hoc network are adjusted and optimized, an i cost function of the unmanned aerial vehicle node in the unmanned aerial vehicle ad hoc network is established, and the mathematical description is as follows:
wherein, wmaxIs the maximum frequency bandwidth, p, available in the unmanned aerial vehicle ad hoc networkminTo the minimum usable transmit power, wminAnd carrying out self-organizing on the network for the unmanned aerial vehicle to obtain the minimum usable frequency bandwidth.
(3) Considering that the drone has a certain error probability in transmitting data, this requires retransmission of this data until the receiver can correctly receive itThis inevitably causes delay; when a plurality of unmanned aerial vehicles carry out data transmission simultaneously, there is queuing delay still. Here, only the wrong retransmission delay is considered, and controlling the retransmission times of the drones can restrict the transmission delay of the drones. If the ad hoc network of the unmanned aerial vehicle adopts Multilevel Differential Phase Shift Keying (MDPSK) as a modulation mode, for any M-level DPSK signal, for the ith unmanned aerial vehicle, the approximate formula of the error rate calculation is as follows
Wherein
γiIs the signal-to-noise ratio of the symbol. Setting the error code correcting capacity of each frame as C, the average length of each frame in communication as L, and the average correct transmission probability of each frame as Pf＝(1-Pe)L-C. Defining the system requirement of the unmanned aerial vehicle ad hoc network as maximum two times of retransmission as the probability threshold of the time delay guarantee constraint condition as PthEstablishing the probability that the data frame of each unmanned aerial vehicle node needs to be transmitted for 2 times at most as PnThe mathematical description is as follows:
from the formula (4)
Then the constraint of the available bit error rate
Then the receiver sir constraint for drone i is
Where erfcinv (x) is the inverse of erfc (x)
Then the transmit power constraint of the ith drone is
(4) Establishing a mathematical model of resource distribution such as spectrum bandwidth and transmitting power based on a non-cooperative game under the condition of satisfying retransmission delay constraint conditions in the unmanned aerial vehicle ad hoc network:
wherein u isi(wi,pi) The utility function of the unmanned plane node i in the unmanned plane ad hoc network based on the network transmission performance is shown, w belongs to [ w ∈ [ ]min,wmax],P∈[pmin,pmax]Policy space, P, for unmanned aerial vehicle node transmit power and spectral bandwidthn≥PthIn order to control the data frame retransmission times of the unmanned aerial vehicle as the transmission delay constraint condition of the nodes of the unmanned aerial vehicle, the transmission delay constraint condition needs to satisfy the formula (8).
In the game model, the transmission power and the spectrum bandwidth of each unmanned aerial vehicle node are finally balanced, namely, the equation (9) has certain Nash balance.
Setting the nash equilibrium power of the drone node to p, then the drone node in the network individually changes its transmit power to deviate from this equilibrium, all at an increased cost, i.e. the cost of it is increased
Wherein
Representing the transmit power vectors of all other users except user i. For determining the transmission power in the equalization, equation (9) ui(p) determining piAnd let it be 0, we can obtain:
considering the SINR gamma at the receiving end under the correct demodulation conditioni＝hipi/IiMuch greater than 1, which can be approximated by equation (10)
Therefore, an optimized transmission power expression of the unmanned aerial vehicle node in the Nash equilibrium state can be obtained:
setting the nash equilibrium power as w, then a node of a drone in the drone ad hoc network individually changes its frequency bandwidth to deviate from this equilibrium, and its cost will increase, that is:
wherein
A frequency bandwidth vector representing all nodes except the frequency bandwidth of drone node i. To find the frequency bandwidth in equalization, u is pairedi(wi) Calculating wiAnd let it be 0, we can obtain:
considering that the interference from adjacent nodes in the unmanned aerial vehicle ad hoc network communication is far more than Gaussian white noise, namely
And the channel interval protection bandwidth alpha is also far smaller than the frequency bandwidth w used by the nodeiCan be approximated by the formula (13)
By working up formula (14) to give
Order to
And a, b, c, d > 0, as can be seen from formula (15)
awi 3-bwi 2+cwi-d＝0 (16)
When the formula is determined as B2The equation has one real root and one pair of conjugate virtual roots when the-4 AC is more than 0, wherein A ═ b2-3ac，B＝-bc+9ad，C＝c2-3bd
Where j is the imaginary symbol, Δ1＝-b2+3ac，Δ2＝2b3-9abc+27a2d
The obvious real root is greater than 0, and the expression (17) can obtain an optimized frequency bandwidth expression of the unmanned plane node i in the state of Nash equilibrium:
(5) in the process of information transmission, each unmanned aerial vehicle node expects the frequency bandwidth and the transmission power to be as large as possible, so that satisfactory communication capacity and correct transmission probability can be obtained, and the final aim in the process of mutual gaming is that each unmanned aerial vehicle node can obtain high communication quality under the condition of time delay constraint at the expense of proper transmission power and proper frequency spectrum bandwidth. In the game model, the transmission power and the spectrum bandwidth of each unmanned aerial vehicle node finally reach nash equilibrium, that is, the optimized values of the transmission power and the spectrum bandwidth can be solved by using the following iterative process:
i. initializing the transmitting power and frequency bandwidth of each user, setting a probability threshold P of carrying out retransmission at most twice as a time delay guarantee constraint conditionth；
Using the combination of the formula (12) and the formula (20) to obtain the transmission power and the frequency bandwidth of the ith user;
judging whether the transmission power constraint condition in the formula (8) is met, comparing the probability that the data frame of the unmanned aerial vehicle node i in the formula (4) needs to be transmitted for 2 times at most with a probability threshold taking a target as a time delay guarantee constraint condition, if the probability is smaller than the target threshold, and if the probability is not met, setting the transmission power of the ith user as the minimum value in the formula (8);
iv, determining whether formula (16) is satisfied or not, and determining that formula Δ is B2-4AC > 0 condition, if the condition is not satisfied, setting the spectrum bandwidth of the ith user to the minimum corresponding to the decision formula in formula (16);
and iii, continuing to increase the transmission power and the frequency bandwidth of the user i, simultaneously gradually reducing the transmission power and the frequency bandwidth of the obtained previous i-1 user, and updating the transmission power or the frequency bandwidth of the user i by using the formula (12) or the formula (20) until the conditions are met.
if iterate k +1 times, | | p*(k+1),p*(k)≤ξ1I and W*(k+1),w*(k)≤ξ2And | l, where ξ is a threshold set in the iteration process, if the difference between the transmission power and the frequency bandwidth before and after the iteration is smaller than a threshold value, the iteration process is stopped, and the obtained result can be regarded as a Nash equilibrium solution of the frequency spectrum bandwidth and the transmission power, otherwise ii is continuously executed, and the iteration calculation is carried out until the transmission power and the frequency spectrum bandwidth are converged.
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FIG. 1: and all nodes of the unmanned aerial vehicle are distributed in the active area of the unmanned aerial vehicle ad hoc network.
FIG. 2: and (4) a relation curve of the optimized transmitting power of the unmanned aerial vehicle node and the frequency bandwidth.
FIG. 3: and (4) a relation curve of the optimized frequency bandwidth and the transmitting power of the unmanned aerial vehicle node.
Detailed Description
The technical solution provided by the present invention will be described in detail with reference to specific examples.
In an unmanned aerial vehicle ad hoc network, 30 unmanned aerial vehicle nodes are randomly distributed in a square area of 1000m multiplied by 1000m, and ground equipment is located in the center of the area. Minimum transmit power per user in the system is pmin0.1W, maximum transmission power pmax1W, background noise power σ2＝2×10-13mW, interference factor mu between unmanned aerial vehicle nodes is 0.1, and channel gain hi＝K/εi κIn the model, K is 10-11The path attenuation at 1km is 110dB, k is 4, and the signal to interference plus noise ratio for correct demodulation reception is 8. The channel interval protection bandwidth alpha is 0.5MHz, the channel capacity can reach factor beta is 0.75, and the maximum frequency bandwidth w which can be used in the unmanned aerial vehicle ad hoc networkmaxIs 5MHz, the minimum frequency bandwidth w which can be used in the unmanned aerial vehicle ad hoc networkmin1MHz, the system requirement of the unmanned aerial vehicle ad hoc network is a probability threshold P of retransmitting at most twicethIs 0.99.
FIG. 1 shows that 30 unmanned aerial vehicle nodes are within a 1000m square areaAnd the unmanned aerial vehicle distribution situation is characterized in that one unmanned aerial vehicle node is randomly selected to communicate with the ground equipment, and the situation that the unmanned aerial vehicle node selects the transmitting power and the spectrum bandwidth when the unmanned aerial vehicle node transmits data with other unmanned aerial vehicle nodes simultaneously is analyzed. Fig. 2 shows a relationship curve of the optimized transmission power of the unmanned aerial vehicle node and the frequency bandwidth, and it is seen from the graph that when the set frequency spectrum bandwidth is increased from 1MHz to 2.2MHz, the slope of the increase of the optimized transmission power of the unmanned aerial vehicle node is larger, and then as the frequency spectrum bandwidth continues to increase, the increase of the optimized transmission power of the unmanned aerial vehicle node tends to be gentle and finally converges to the vicinity of the maximum transmission power of 1W. Fig. 3 shows a relationship curve between the optimized frequency bandwidth and the transmission power of the drone node, and it is seen from the graph that when the set transmission power is increased from 0.1W to 1W, the optimized frequency spectrum bandwidth of the drone node is correspondingly increased along with the increase of the transmission power, and the curvature is always relatively smooth. Substituting the relevant data of the figures 2 and 3 into an iteration process to solve the numerical value of the unmanned aerial vehicle ad hoc network, so as to obtain an optimized solution of the unmanned aerial vehicle node about the frequency spectrum bandwidth and the transmitting power after the whole unmanned aerial vehicle ad hoc network is in Nash equilibrium, namely wi4.4MHz and piConsidering that the drone node is at the edge of the drone ad hoc network coverage, it can be seen that such a configuration is appropriate for the network performance of other drone nodes and the overall system, while the distance of the drone node from the ground devices is relatively close, the optimal solution for the spectral bandwidth and transmit power should be low.
Claims (1)
1. A resource allocation method meeting time delay constraint in an unmanned aerial vehicle ad hoc network is characterized in that:
(1) in an unmanned aerial vehicle ad hoc network with N unmanned aerial vehicles in total communicating with ground equipment, considering that each unmanned aerial vehicle in the unmanned aerial vehicle ad hoc network selects proper frequency bandwidth and transmitting power under the condition of satisfying time delay constraint condition within limited transmission times to enable the transmitting capacity of each unmanned aerial vehicle to achieve balanced optimization, thereby inhibiting each unmanned aerial vehicle from obtaining self transmitting capacity by simply and blindly increasing transmitting power and frequency bandwidth, avoiding interference to other unmanned aerial vehicles in the unmanned aerial vehicle ad hoc network and causing self energy waste, ensuring the network performance of each node of the unmanned aerial vehicle ad hoc network in the communication process, and constructing a mathematical model for resource distribution such as spectrum bandwidth and transmitting power based on non-cooperative game under the condition of satisfying retransmission time delay constraint condition in the unmanned aerial vehicle ad hoc network
Wherein u isi(wi,pi) The utility function of the unmanned plane node i in the unmanned plane ad hoc network based on the network transmission performance is shown, w belongs to [ w ∈ [ ]min,wmax],P∈[pmin,pmax]Policy space, P, for unmanned aerial vehicle node transmit power and spectral bandwidthn≥PthFor controlling the number of data frame retransmissions of the drone as a transmission delay constraint for the nodes of the drone, PthThe system of the unmanned aerial vehicle Ad hoc network requires that retransmission is carried out at most twice as a probability threshold of a time delay guarantee constraint condition, PnThe probability that the data frame of the unmanned plane node needs to be transmitted at most 2 times, and the average correct transmission probability of each frame is PfIncome function J of unmanned plane node ii(wi,pi) Is represented as follows:
wherein, alpha is the channel interval protection bandwidth, beta is the channel capacity reachable factor, piIndicating the transmission power of the ith drone, wiIndicating the frequency bandwidth, h, allocated to the ith droneiIndicating the channel gain, N, from the ith user to the terrestrial device0/2 is the additive white Gaussian noise power spectrum density, I, of the user receiving endiMu is interference factor of signal between nodes of the unmanned aerial vehicle for receiver interference of the unmanned aerial vehicle i, and corresponds to receiver signal-to-interference ratio of the unmanned aerial vehicle i
I cost function C of unmanned aerial vehicle nodei(wi,pi) Is represented as follows:
wherein, wmaxIs the maximum frequency bandwidth, p, available in the unmanned aerial vehicle ad hoc networkminTo the maximum usable transmission power, wminAnd carrying out self-organizing on the network for the unmanned aerial vehicle to obtain the minimum usable frequency bandwidth.
(2) Considering that a certain error probability exists when the unmanned aerial vehicle transmits data, which requires retransmission of the data until a receiver can correctly receive the data, controlling the retransmission times of the unmanned aerial vehicle can restrict the transmission delay of the unmanned aerial vehicle, therefore, when the ad hoc network of the unmanned aerial vehicle adopts M-ary differential phase shift keying as a modulation mode, the transmission power requirement of the ith unmanned aerial vehicle can be obtained by using the retransmission times of the data frame of the unmanned aerial vehicle controlled in a mathematical model based on resource allocation such as frequency spectrum bandwidth, transmission power and the like of a non-cooperative game as the transmission delay restriction condition of an unmanned aerial vehicle node i, and the requirement is expressed as follows:
where erfcinv (x) is the inverse of erfc (x),
c is the error correction capability per frame and L is the average length per frame in the communication.
(3) In a mathematical model of resource distribution such as frequency spectrum bandwidth and emission power based on a non-cooperative game under the condition of satisfying retransmission time delay constraint, the emission power and the frequency spectrum bandwidth of each unmanned aerial vehicle node finally reach an optimized solution of Nash equilibrium, and at the moment, each unmanned aerial vehicle in the unmanned aerial vehicle ad hoc network selects proper frequency bandwidth and emission power under the condition of satisfying time delay constraint in limited transmission times to enable the transmission capacity of each unmanned aerial vehicle to reach equilibrium optimization.
The optimized transmission power of the drone node i in the nash equilibrium state is represented as follows:
the optimized frequency bandwidth of drone node i in nash equilibrium is represented as follows:
wherein the content of the first and second substances,
Δ1＝-b2+3ac，Δ2＝2b3-9abc+27a2d，A＝b2-3ac，B＝-bc+9ad，C＝c2-3bd, and is required to satisfy Δ ═ B2-4AC > 0 conditions for presence of solid roots.
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| CN115276768B (en) * | 2022-07-22 | 2023-07-28 | 南京邮电大学 | Unmanned aerial vehicle time delay minimization method integrating interference mitigation and resource allocation |
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Application publication date: 20220412 |