In this paper, we investigate the reliability and security of cooperative dual-hop nonorthogonal multiple access (NOMA) for internet-of-thing (IoT) networks, in which the transceivers consider a detrimental factor of in-phase and quadrature-phase imbalance (IQI). The communication between the source and destination is accomplished through a decode-and-forward (DF) relay in the presence of an eavesdropper. In order to characterize the performance of the considered system, exact analytical expressions for the outage probability (OP) and intercept probability (IP) are derived in closed-form. Furthermore, to better understanding the performance of the considered system, we further derive the asymptotic expressions of OP in the high signal-to-noise ratio (SNR) regime and IP at the high main eavesdropping ratio (MER) region. A large number of analysis and Monte Carlo simulation results show that the existence of IQI usually increases the corresponding OP and reduces the IP, which means that reduces the reliability of the system and improves the security. In addition, the provided results provide useful insights into the trade-off between reliability and security of secure cooperative communication systems.

Accurate indoor positioning services have become increasingly important in modern applications. Various new indoor positioning methods have been developed. Among them, visual–inertial odometry (VIO)-based techniques are notably limited by lighting conditions, while ultrawideband (UWB)-based algorithms are highly susceptible to environmental interference. To address these limitations, this study proposes a hybrid indoor positioning algorithm that combines UWB and VIO. The method first utilizes a tightly coupled UWB/inertial measurement unit (IMU) fusion algorithm based on a sliding-window factor graph to obtain initial position estimates. These estimates are then combined with VIO outputs to formulate the system’s motion and observation models. Finally, an extended Kalman filter (EKF) is applied for data fusion to achieve optimal state estimation. The proposed hybrid positioning algorithm is validated on a self-developed mobile platform in an indoor environment. Experimental results show that, in indoor environments, the proposed method reduces the root mean square error (RMSE) by 67.6% and the maximum error by approximately 67.9% compared with the standalone UWB method. Compared with the stereo VIO model, the RMSE and maximum error are reduced by 55.4% and 60.4%, respectively. Furthermore, compared with the UWB/IMU fusion model, the proposed method achieves a 50.0% reduction in RMSE and a 59.1% reduction in maximum error.

This paper considers a discrete-time multiuser multiple-input single-output (MISO) Gaussian broadcast channel (BC), in which channel state information is available at both the transmitter and the receivers. The flexible and explicit design of a uniquely decomposable constellation group is provided based on pulse amplitude modulation and rectangular quadrature amplitude modulation constellations. With this, a modulation division (MD) transmission scheme is developed for the MISO BC. The proposed MD scheme enables each receiver to uniquely and efficiently detect their desired signals from the superposition of mutually interfering cochannel signals in the absence of noise. In our design, the optimal transmitter beamforming problem is solved in a closed-form for two-user MISO BC using max-min fairness as a design criterion. Then, for a general case with more than two receivers, we develop a user-grouping-based beamforming scheme, where the grouping method, beamforming vector design and power allocation problems are addressed by using weighted max-min fairness. It is shown that our proposed approach has a lower probability of error compared with the zero-forcing (ZF) method when the Hermitian angle between the two channel vectors is small in a two-user case. In addition, simulation results also reveal that for the general channel model with more than two users, our user-grouping-based scheme significantly outperforms the ZF, time division, minimum mean-square error, and signal-to-leakage-and-noise ratio-based techniques in moderate and high SNR regimes when the number of users approaches to the number of base station (BS) antennas and it degrades into the ZF scheme when the number of users is far less than the number of BS antennas in Rayleigh fading channels.

This letter concerns the constellation design problem in energy-based noncoherent massive single-input multiple-output (SIMO) systems over correlated channels. Thanks to the large number of receiving antennas, we approximate the detection error minimization problem by the maximization of the minimum Kullback-Leibler (KL) divergence of the received signal vectors corresponding to different transmitted symbols. However, the max-min KL divergence problem is still difficult to solve. This is because the KL divergence expression involves summations of nonlinear functions of the transmitted signal powers induced by the channel correlation. We then resort to the Szegö’s theorem on large Hermitian Toeplitz matrices to simplify the formulated problem, which subsequently can be optimally solved by a one-dimensional bisection search. Simulation results demonstrate that the constellation designed by our approach outperforms its counterpart without considering the channel correlation, and the performance gain enlarges as the degree of correlation increases.