Beamforming optimization method for online noma multi-antenna system based on Lyapunov algorithm
A technology of multi-antenna system and optimization method, which is applied in the directions of diversity/multi-antenna system, radio transmission system, transmission system, etc., to achieve the effect of improving the performance of safe transmission rate and expanding the usage situation
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Embodiment 1
[0045] 1. System model
[0046] The applicable communication system model of the present invention is made up of a base station and K users, such as figure 1As shown, each user has N antennas, the base station has M antennas, and the transmitter transmits information to K users using the energy receiving technology. It is assumed that the base station can fully know the channel state information (Channel State Information, CSI) of the entire network system. In the tth time slot, the channel response from the base station to the Kth user is expressed as H k (t), the channel response to the eavesdropper is denoted as H e (t), thus, the base station is able to properly allocate its beamforming matrix to improve the security and speed of the whole network.
[0047] 2. Problem description
[0048] According to the non-orthogonal multiple access (NOMA) technology protocol, the sending end adopts superposition coding technology, and the signal x(t) sent by the base station at the...
Embodiment 2
[0108] The effect of the present invention can be further illustrated by the following simulation experiment results, and the basic process of the simulation experiment is referred to Figure 4 .
[0109] for figure 2 and image 3 , set the number of users in the system K=2, the number of user antennas N=2, the number of base station antennas M=2, the channel response from the base station to the strong and weak users is an independent and identically distributed complex Gaussian random with a mean of 0 and a variance of 10dB and 0dB respectively variable, the channel response of the eavesdropper is an independent and identically distributed complex Gaussian random variable with a mean of 0 and a variance of 0dB, and the total transmit power of the base station is 5dB. The rate constraint for weak users is 0.5bps / Hz. Figure 2 considers the time-averaged rate of the system over 200 slots. The disturbance parameter is X=45, the maximum capacity of the battery is E_max=50, t...
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