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Summary In this paper, we consider the optimal control of unknown stochastic dynamical system for both the finite‐horizon and infinite‐horizon cases. The objective of this paper is to find an optimal controller to minimize the expected value of a function which depends on the random disturbance. Throughout this paper, it is assumed that the mean vector and covariance matrix of the disturbance distribution is unknown. An uncertainty set in the space of mean vector and the covariance matrix is introduced. For the finite‐horizon case, we derive a closed‐form expression of the unique optimal policy and the opponents policy that generates the worst‐case distribution. For the infinite‐horizon case, we simplify the Riccati equation obtained in the finite‐hozion setting to an algebraic Riccati equation, which can guarantee the existence of the solution of the Riccati equation. It is shown that the resulting optimal policies obtained in these two cases can stabilize the expected value of the system state under the worst‐case distribution. Furthermore, the unknown system matrices can also be explicitly computed using the adaptive dynamic programming technique, which can help compute the optimal control policy by solving the algebraic Riccati equation. Finally, a simulation example is presented to demonstrate the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

This paper considers a cooperative multiple access (CMA) scheme where two full-duplex sources simultaneously send their own messages to a common destination. As part of their cooperation, each of the two sources also receives and relays part of the message from the other source. This paper develops algorithms for computing the optimal power allocation to achieve the maximal network throughput subject to residual self-interference (RSI) at the non-ideal full-duplex sources. As a generalization of a time-division duplex (TDD) scheme, we consider a three-phase CMA (3P-CMA) scheme which treats the TDD scheme as a special case. The throughput of the 3P-CMA scheme consistently exceeds that of the TDD scheme regardless of the RSI power gain. Also shown in this paper is a semi-closed form of the optimal power allocation when the three-phases are constrained to be identical, i.e., resulting in a one-phase CMA (1P-CMA) scheme. The optimal power allocation of the 1P-CMA scheme takes much less time to compute, and its network throughout is close to that of the 3P-CMA scheme when the RSI power gain is low. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS), which consists of many low-cost reflecting elements, can enhance the reception of the desired signal and suppress the interference. Considering the above advantages, this paper investigates the RIS-assisted wireless communication in the presence of an interferer, where a receiver receives the desired signal and interference from a transmitter and an interferer, respectively, and the RIS is deployed to assist this system. First, an interference-limited channel capacity maximization problem is formulated, and a numerical algorithm based on the fraction programming and optimality conditions is proposed to obtain the optimal solution. Then, this paper shows the upper boundary of the maximal capacity with interference and discusses what kind of channel conditions can achieve the upper boundary and the corresponding optimal phase shifts. Next, this paper analyzes the asymptotic behaviors of the maximal capacity in the scenarios that some or all of the number of reflecting elements, antennas at the transmitter, and interferer go to infinity. Finally, this paper generalizes the above results to the multiple interferers scenario. [ABSTRACT FROM AUTHOR]