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RIS-Aided D2D Communications Relying on Statistical CSI with Imperfect Hardware

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... Moreover, the authors analyzed to underlay and overlay modes of D2D communication. Considering imperfect hardware including both hardware impairment at the transceivers and phase noise at the RISs, the authors optimized the phase shift to maximize the achievable rate for both continuous phase shifts and discrete phase shifts in [16]. With goal of maximizing the overall spectrum efficiency and energy efficiency of the network, the resource reuse indicators, the transmit power and the RIS's passive beamforming were optimized in [17]. ...
... Fig. 2 shows the OP comparison of V ϑ between OA and UA. Several observations are obtained: (i) the theoretical analyses (i.e., the curves with continuous and dash-lines) in (16) and (28) agreeably match with the simulation results (i.e., markers), corroborating the accuracy of our analysis. (ii) For the different locations of paired D2D users and fixed P 0 at 5 dBm in Fig. 2(a), we notice that the OP of V ϑ linearly decreases as P S ϑ increases and reduces significantly when paired D2D users are located near the RIS and descend at 6 VOLUME 4, 2022 This article has been accepted for publication in IEEE Access. ...
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... Recently, the joint beamforming and phase shift design was studied in a RIS-aided physical layer security system in [11]. Besides the transceiver hardware impairment, the authors of [12] further considered the impact of the phase noise at the RIS and derived the closedform data rate expression, based on which the genetic algorithm was adopted to solve the phase shift optimization problem. In [13], the RIS-aided communication system for serving a mobile user was studied, and the authors proposed an interesting algorithm to predict the positions of the user under HWI. ...
... Therefore, the k-th user's instantaneous signal-to-interference-plus-noise ratio (SINR) is given by (12) and (13) on the next page. Based on (12) and (13), the instantaneous data rate of the k-th user can be expressed as ...
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In this paper, we study a reconfigurable intelligent surface (RIS)-aided multiuser MISO system with imperfect hardware, where the transceiver design is based on the statistical channel state information (CSI). Considering the transceiver hardware impairments (HWI), we aim to maximize the minimum average user data rate, where the precoding matrices at the base station (BS) and the reflecting phase shifts at the RIS are jointly optimized. Since the problem is nonconvex and the objective function cannot be derived in closed form, we adopt the deep deterministic policy gradient (DDPG) algorithm to deal with this challenging optimization problem, where we generate a set of CSI vectors in an offline way, and then these data sets are used to train the neural networks. The simulation results demonstrate the rapid convergence speed of the adopted DDPG algorithm and also emphasize that it is crucial to consider the HWI when optimizing the transceiver.
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