Abstract
In this paper, a detailed analysis of multi-input multi-output (MIMO) cross-layer secure communication algorithms in information-physical systems is investigated employing an interference strategy. A three-stage data-assisted channel estimation method is proposed in this paper for the acquisition of channel state information for complex jamming channels in large-scale MIMO two-layer systems. To implement the data-assisted scheme, assuming that there are no errors and no delay in the system, if the data detection and decoding data sequences are completed at a small cell base station, they are sent to the macro base station via a wired backhaul. Due to the sparsity of the channel at the macro base station after user grouping, a channel estimation algorithm based on optimal block orthogonal matching tracking(s) is proposed in the case where the downlink channel at the macro base station utilizes the decoded uplink data and known training sequences. The simulation results show that the data-assisted method proposed in this paper is effective in improving channel estimation accuracy. A machine learning algorithm is directly used to classify the channel difference or channel matrix to obtain the authentication results. In this paper, the scheme is first simulated using channel data from dynamic communication scenarios, its feasibility is analyzed, and the parameters in the scheme are compared, and the optimal scheme is the bagging tree authentication scheme using a 128-dimensional channel matrix as input. To address the interference problem caused by the dense arrangement of SAPs in heterogeneous networks and the unbalanced network load, large-scale MIMO techniques are introduced to reduce the downlink interference caused by the microcell boundary expansion in heterogeneous networks.
Highlights
Today, with the dramatic increase in the number of user terminals and the diversification of terminal devices, modern communications are becoming increasingly complex, and both individuals and enterprises are inseparable from the communications services provided by wireless communication networks [1]
The interference situation in a large-scale multi-input multi-output (MIMO) double-layer network will be more complicated: firstly, compared with the macro base stations deployed after strict planning, the location of small base stations in the network is somewhat random, and the irregular deployment of a large number of small base stations will cause the interference characteristics of largescale MIMO double-layer network is very complicated; besides, with the increase in the density of small base stations, the inter-layer interference of small base stations to the macro base stations and the interference of small base stations to the cell edge users will be more complicated
Previous work in reference has addressed the effects of frequency-guide training during channel estimation due to frequency-guide contamination in downlink and uplink transmissions of large-scale MIMO systems
Summary
With the dramatic increase in the number of user terminals and the diversification of terminal devices, modern communications are becoming increasingly complex, and both individuals and enterprises are inseparable from the communications services provided by wireless communication networks [1]. The interference situation in a large-scale MIMO double-layer network will be more complicated: firstly, compared with the macro base stations deployed after strict planning, the location of small base stations in the network is somewhat random, and the irregular deployment of a large number of small base stations will cause the interference characteristics of largescale MIMO double-layer network is very complicated; besides, with the increase in the density of small base stations, the inter-layer interference of small base stations to the macro base stations and the interference of small base stations to the cell edge users will be more complicated. Intra-layer interference between different femtocells is bound to become increasingly serious, which will severely limit the quality of service (QoS), especially for users at cell boundaries, whose performance cannot be guaranteed [7]
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