Unmanned aerial vehicle base station communication resource allocation strategy prediction method based on noise optimization

A communication resource allocation and UAV technology, which is applied in the field of dynamic allocation of communication resources of UAV base stations, can solve the problem that the flexibility of bandwidth allocation needs to be optimized, prediction cannot be achieved, and UAV trajectory optimization cannot effectively combine various users, etc. problems, to achieve the effect of increasing the exploration space, improving the accuracy, and designing a reasonable design.

Active Publication Date: 2021-07-13
中国人民解放军火箭军工程大学
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Problems solved by technology

[0003] At present, the dynamic allocation of UAV base station communication resources is generally through UAV trajectory optimization, DDPG algorithm, and DQN algorithm. UAV trajectory optimization cannot effectively combine the dynamics of each user and cannot achieve prediction; DDPG algorithm only The motion and bandwidth allocation of UAVs are controlled; the DQN algorithm realizes that UAVs adapt to the movement of ground users while maximizing channel capacity. However, since each UAV can only allocate rated sub-channels to each user, the bandwidth allocation flexibility to be optimized

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  • Unmanned aerial vehicle base station communication resource allocation strategy prediction method based on noise optimization

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Embodiment Construction

[0072] like figure 1 The shown method for predicting the communication resource allocation strategy of UAV base station based on noise optimization includes the following steps:

[0073] Step 1, the establishment of the network model:

[0074] Step 101. Set the parameter of the Actor reality network as θ μ , the parameter of the critical reality network is θ Q , the parameter of Actor target network is θ μ ', the parameter of the Critic target network is θ Q ';

[0075] Step 102, set the noise model as s′=(μ ω +σ ω ×ε ω )s+μ b +σ b ×ε b ; where, s′ represents the state of the user relative to the drone after applying noise, s represents the state of the user relative to the drone, μ ω is the mean value of the first Gaussian noise, σ ω represents the first Gaussian noise variance value, μ b represents the second Gaussian noise mean, σ b represents the second Gaussian noise variance value, σ ω The initial value of is denoted as σ ω (0), and σ ω (0)=0, σ b The i...

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Abstract

The invention discloses an unmanned aerial vehicle base station communication resource allocation strategy prediction method based on noise optimization. The method comprises the following steps: 1, establishing a network model; 2, acquiring training data; 3, performing training iteration to obtain a network optimization parameter and a noise optimization parameter; 4, obtaining an optimized network model; 5, predicting an unmanned aerial vehicle base station communication resource dynamic allocation strategy. The method is simple in step and reasonable in design, the exploration space of the communication resource allocation strategy can be increased, the accuracy of the optimized network model is improved, and the method effectively adapts to the dynamic state of each user so as to predict and output the reasonable communication resource allocation strategy.

Description

technical field [0001] The invention belongs to the technical field of dynamic allocation of communication resources of unmanned aerial vehicle base stations, in particular to a method for predicting the allocation strategy of communication resources of unmanned aerial vehicle base stations based on noise optimization. Background technique [0002] In the future 5G / B5G mobile communication, cellular connection drones will be a crucial part. The UAV is equipped with a massive MIMO antenna array and a high-precision beamforming method, which can form a narrow beam with strong directivity and high gain, which can effectively overcome the practical problem of huge attenuation in the millimeter wave and above frequency bands while reducing neighbor interference. At the same time, with effective power control and bandwidth resource allocation strategies, the performance of the communication system can be improved under the condition of limited communication resources. Therefore, ...

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Application Information

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IPC IPC(8): H04W24/02H04W24/06
CPCH04W24/02H04W24/06Y02T10/40
Inventor 赵建伟贾维敏吴官翰金伟张聪崔亚龙何芳王连锋
Owner 中国人民解放军火箭军工程大学
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