In sixth-generation (6G) communication networks, ultrahigh-data rate and reliability are greatly vital for massive user connections and network sensors, such as Internet of Things (IoT) devices. Simultaneous wireless information and power transfer (SWIPT) has been evolved as an efficient strategy to enhance the reliability of wireless communication systems through prolonging the battery lifetime by harvesting energy from the received radio-frequency (RF) signals. Furthermore, cooperative relay sensors in IoT networks can extend the network coverage. In this article, we consider a massive multiple-input–multiple-output (MIMO) two-way relaying system, where the relay node splits the received RF signals into two power streams, one for information decoding (ID) and the other for energy harvesting (EH). Two classical and linear relay precodings, i.e., zero-forcing reception/zero-forcing transmission (ZFR/ZFT) and maximum-ratio combining/maximum-ratio transmission (MRC/MRT), are adopted to satisfy the requirements of high rate in this relay system. Different from prior work, the SWIPT technique and large-scale fading effects of MIMO channels are taken into account for deriving the asymptotic sum-rates of four prevalent power scaling cases when the number of relay antennas grows to infinity. Finally, the analytical results are evaluated by the presented simulation and numerical results.

We have developed a fast tabular technique for Boolean to fixed-polarity Reed–Muller logic conversion. The idea is derived from the popular tabular technique but the processes of generating new terms and cancelling pairs are vastly different. The feature of bit-by-bit operation in the tabular technique has also been changed. In our technique, an index table is used to capture the number of occurrences of initial and new terms. This instant updating process eliminates the time-consuming step of cancelling pairs and makes the method much more efficient than the tabular technique. In addition, the fast tabular technique possesses inherent parallelism since different minterms can be processed concurrently and added to the index table independently. Our method is applicable to any number of variables and is suitable for manual computations as well as computer programming. Some comparison results are given, and we believe our technique has achieved the best time and space complexities so far.

This research delves into an integrated sensing and communication (ISAC) system, which leverages a ship-based station to simultaneously offer maritime communication services and perform target detection. Through the establishment of a channel model that captures the complexities of the maritime environment and the analysis of the dynamic behavior of the ship-based station, this article introduces a unified signal processing framework for this ISAC system. This framework is tailored for various ship movement patterns through the integration of alternating optimization coupled with trust-region-based sequential convex approximation (SCA) techniques, with the goal of maximize the communication data rate without compromising the sensing performance. Simulation results corroborate the validity of the proposed model, laying a theoretical foundation for the advancement of maritime communication and perception systems, thereby anticipating enhanced support for future generations of integrated maritime applications.

Rate splitting multiple access (RSMA) has emerged in the integrated satellite-terrestrial networks (ISTNs). However, the satellite-terrestrial channel suffers serious shadow fading and cannot maintain stable communication links effectively. From the perspective of reliability, this correspondence takes the lead in focusing on the outage probability (OP) of ISTNs based on the combination of RSMA and hybrid automatic repeat request with chase combining (HARQ-CC). The lower and upper bounds of OP are derived firstly according to the inclusion-exclusion principle. Then, the diversity order is deduced, pointing out the conditions for full time diversity. Monte Carlo simulations confirm the accuracy of the theoretical results, and superior outage performance of HARQ-CC-aided RSMA is present compared with benchmarks.

In the radar array signal processing direction of arrival (DOA), the estimation of weak non-stationary signal is an important and difficult problem when both strong and weak signals are coexisting particularly because the weak non-stationary signals are often submerged in noise. In this paper, we proposed a novelty method to estimate the direction of arrival (DOA) of weak non-stationary signal in scenario for strong non-stationary interference signals and Gaussian white noise. The method utilizes spatial time-frequency distribution (STFD) of cross terms rather than suppressing cross terms in time-frequency analysis. The STFD of cross terms are introduced as an alternative matrix, which is similar to data covariance matrix in multiple signal classification (MUSIC), for the DOA estimation of a weak non-stationary signal. The cross-term amplitude of the strong and weak signals is usually above the noise and is easier to use than the auto-term of the weak signal. In the cross term, the information of the weak signal is included, and the auto-term of these weak signals is difficult to extract directly. The ability to incorporate the STFD of cross terms empowers information about a weak non-stationary signal for DOA estimation, leading to improved signal estimates for direction finding. The method based on the STFD of cross terms for DOA estimation of the weak non-stationary signal is revealed to outperform the time-frequency MUSIC and traditional MUSIC algorithm by simulation, respectively. This method has the advantages of the time-frequency direction finding method and also deals with the situation of weak signals. When the strong and weak signals exist at the same time and the two angles are similar, the cross-terms can be used to perform DOA estimation on the weak signal.