This letter focuses on the optimal sum secure degree of freedom (SDoF) in a two-way wiretap channel (TW-WC), wherein two legitimate full-duplex multiple-antenna nodes cooperate with each other and are wiretapped by a multiple antenna eavesdropper simultaneously. It aims to find the optimal sum SDoF pertaining to secret-key capacity for the TW-WC. First, we analyze the upper bound and lower bounds of the optimal sum SDoF by establishing their equivalence to the expression of the optimal SDoF corresponding to the secrecy rate for the TW-WC. Subsequently, in scenarios where the legitimate nodes are configured with an equal number of transmit and receive antennas, it is elucidated that the upper and lower bounds of the optimal SDoF converge. Furthermore, the findings suggest that a higher SDoF can be achieved than the existing works, thereby heralding an enhancement in secure spectral efficiency.

Integrated sensing and communication (ISAC) holds significant commercial potential in future 6G. The 3GPP technical report indicates that it is crucial to prioritize the sensing services of the ISAC system to ensure the efficient execution of critical services due to resource-constrained environments. Thus, this paper investigates priority-based resource allocation in ISAC systems, where an ISAC base station (BS) simultaneously serves a communication user (CU) and detects both a primary sensing target (PST) and a secondary sensing target (SST). First, A priority criteria for this ISAC system is proposed: 1) Above all, to ensure that the Cramer-Rao bound (CRB) for PST is maintained below a threshold; 2) Following this, the CRB of the SST should be optimized, while ensuring the communication spectral efficiency is preserved. Then, based on this criterion, three cases are derived, and for each case, a distinct resource allocation problem is formulated, yielding closed-form or semi-closed-form expressions of the optimal resource allocation for each problem. Furthermore, An algorithm is also proposed to determine the occurrence of each case and provide the corresponding optimal resource allocation. In addition, system performance under each case is analyzed based on these expressions. Finally, the simulation results demonstrate the impact of the priority strategy on performance, which is consistent with the previous performance analysis.

This article investigates the fixed-time distributed average tracking (DAT) problem for nonlinear multiagent systems with unity relative degree under external disturbances. A distributed control framework is developed to guarantee fixed-time convergence of all agents' outputs to the target trajectory, which is defined as the average of multiple nonlinear reference signals. The approach consists of three main components. First, a steady-state generator is introduced to reconstruct the desired trajectory. Using this generator, a distributed observer is designed to estimate the target trajectory while ensuring robustness against initialization errors. Subsequently, an observer-based output-feedback controller is developed to guarantee the convergence of each agent's output to its corresponding reference signal within a fixed time. Through rigorous theoretical analysis, it is proved that the proposed control architecture ensures fixed-time convergence to the target trajectory, effectively solving the fixed-time DAT problem. The effectiveness of the proposed method is validated through numerical simulations.

The advent of reconfigurable intelligent surfaces (RIS) introduces a novel paradigm to address mutual interference issues within radar-communication coexistence (RCC) systems. However, the predominantly discrete reflection coefficients (DRC) of most real-world RISs pose new challenges for the design of interference-mitigating reflection coefficients. This paper investigates a RIS-assisted RCC system with DRC. First, a radar SINR maximization problem under the constraints of communication signal-to-interference plus noise ratio (SINR) requirements is formulated to obtain feasible designs for the DRC and radar beamforming vectors. Then, an alternating optimization approach is applied, decomposing the original problem into two sub-problems. For the DRC optimization sub-problem, a design approach based on semidefinite relaxation (SDR) and Gaussian randomization is proposed. For the radar beamforming sub-problem, the closed-form expressions for the optimal radar beamforming vectors are obtained by the generalized Rayleigh quotient and the Karush-Kuhn-Tucker (KKT) conditions. Finally, it is demonstrated that within a communication-centric scenario, the RIS needs to maintain orthogonality between the interference channel and the radar-target channel in order to achieve the upper bound of the radar SINR. Based on this conclusion, a low-complexity approach is proposed to optimize the radar SINR in a communication-centric scenario.

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.

In this article, we consider an adaptive optimal output regulation problem for general linear systems. The purpose of the optimal output regulation problem is to guarantee the stability of the closed-loop system and disturbance rejection, as well by minimizing some predefined performance indices. It can be realized by using an optimal controller, in which both optimal feedback control gain and optimal feedforward control gain are included. First, an adaptive dynamic programming (ADP) technique is used to solve the optimal feedback control gain. Next, the unknown system matrices of the plant are explicitly computed. In addition, based on the property of the minimal polynomial, the coefficient of the exogenous disturbance in the expression of the regulated output can also be calculated. Finally, according to the regulator equation, an extra cost function is given, which aims to obtain the optimal feedforward control gain. The linear vector space optimization methods are used to solve the optimal problem. As a result, the linear optimal output regulation problem can be solved by the approximately optimal feedback and feedforward control gains.

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.

The reconfigurable intelligent surface (RIS), which consists of a large number of passive and low-cost reflecting elements, has been recognized as a revolutionary technology to enhance the performance of future wireless networks. This paper considers an RIS assisted multicast transmission, where a base station (BS) with multiple-antenna multicasts common message to multiple single-antenna mobile users (MUs) under the assistance of an RIS. An equivalent channel model for the considered multicast transmission is analyzed, and then an optimization problem for the corresponding channel capacity is formulated to obtain the optimal covariance matrix and phase shifts. In order to solve the above non-convex and non-differentiable problem, this paper first exploits the gradient descent method and alternating optimization, to approach the locally optimal solution for any number of MUs. Then, this paper considers a special case, which can obtain the global optimal solution, and shows the sufficient and necessary condition for this special case. Finally, the order growth of the maximal capacity is obtained when the numbers of the reflecting elements, the BS antennas, and the MUs go to infinity.

This article considers a two-way multiple-input multiple-output (MIMO) Rayleigh block fading wiretap channel with two full-duplex nodes (Alice and Bob) exchanging messages simultaneously and wiretapped by a $ {N}_{ {e}}$ -antennas eavesdropper (Eve). The channel state remains unchanged over a coherence interval T and is unknown to all terminals, including Alice, Bob, and Eve, at the beginning of the coherence interval. We first show the expression of the optimal signal waveform for Alice and Bob, which maximizes the sum secrecy rate, should be the products of independent random diagonal matrices and isotropically distributed unitary matrices. Then, conditioned on large T and small $ {N}_{ {e}}$ , the upper-bound for the secure degree of freedom (s.d.o.f.) of the two-way wiretap channel is derived, and a constant-norm-signaling (CNS) scheme is presented to achieve this theoretical bound. Finally, we formulate an optimization problem of the s.d.o.f. achieved by the CNS scheme for general cases with arbitrary T and $ {N}_{ {e}}$ , and solve this problem by exploring the monotonicity of the achievable s.d.o.f.. Our result shows that the optimal s.d.o.f. can be independent of coherence time T and becomes the product of the numbers of legitimate nodes's transmitter antennas (NLNTA) for large $ {N}_{ {e}}$ and small NLNTA.

This paper proposes a simple hybrid decode- compress- and-forward and compress-and-forward (DCF&CF) relay scheme for the coordinated multipoint (CoMP) uplink transmission. In particular, we consider a scenario that two mobile users (MUs) transmit signal to two access points (APs), which are linked to the central unit (CU) via lossless capacity-limited fronthaul. To characterize the achievable rate region of the considered system, a rate maximization problem is formulated and solved by exploiting the monotonicity and convexity of its objective function. Furthermore, maximum sum rate of the two MUs is obtained according to the maximized rate region boundary. Finally the analysis is validated by numerical results.