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In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE. [ABSTRACT FROM AUTHOR]

In this paper, we consider the non-orthogonal multiple access (NOMA) technique in the heterogeneous network (HetNET) consisting of a single macro base station (BS) and multiple small BSs, where the perfect successive interference cancellation is assumed for the NOMA signals. In this paper, we propose a deep learning-based user association and power allocation scheme to maximize the data rate in the NOMA-based HetNET. In particular, the proposed scheme includes the deep neural network (DNN)-based user association process for load balancing and the DNN-based power allocation process for data-rate maximization. Through the simulation assuming path loss and Rayleigh fading channels between BSs and users, the performance of the proposed scheme is evaluated, and it is compared with the conventional maximum signal-to-interference-plus-noise ratio (Max-SINR) scheme. Through the performance comparison, we show that the proposed scheme provides better sum rate performance than the conventional Max-SINR scheme. [ABSTRACT FROM AUTHOR]

In this paper, we propose a power control technique for D2D communication in the heterogenous network consisting of cellular and D2D communication systems. Although the transmit signal of D2D communication degrades the performance of cellular system by interfering the signal reception at CU in the conventional heterogenous networks without eavesdroppers, it can be utilized as jamming signal for preventing other devices from recovering the transmitted information if there are eavesdroppers in the network. The proposed power control technique maximizes the achievable rate of D2D communication while ensuring the target security performance of cellular communication system. Through simulation results, we validate the analysis results and compare the performance with the conventional D2D communication scheme that utilizes its full transmit power for maximizing the achievable rate regardless of the performance of cellular system. [ABSTRACT FROM AUTHOR]