Collaborative Beamforming (CB) based on Wireless Sensor Network (WSN) is a promising technology for low-power consumption, long-range data transmission. Due to the random distribution of nodes in WSN, unpredictable sidelobe may interfere with unintended direction. It is possible to control sidelobe level in unintended direction by selecting an appropriate combination of nodes. However, as the network scale increases, the complexity of node selection grows exponentially, requiring existing methods to spend significant computation time when addressing the node selection problem in large-scale WSN, which results in high computational delay. To tackle this challenge, we first formulate a nonlinear optimization problem that aims to reduce the sidelobe level by selecting collaborative nodes within a given time while minimizing delay. Then based on deep reinforcement learning (DRL), we propose a SAC-based node selection algorithm (SACNS) to solve this problem. Subsequently, we propose a potential CB implementation scheme to validate the performance of the SACNS. The simulation results show that, compared with the baseline method, the proposed SACNS algorithm can effectively reduce the sidelobe level in CB optimization and significantly shorten the computation time.

In this paper, we propose Virtual Machine (VM) allocation methods that provide continuous services even in the presence of failures in edge computing systems. On edge servers in edge computing systems, various services and applications requested by users are executed on VMs hosted on distributed edge servers. However, if a VM providing a specific service is hosted on only one edge server, the service becomes unavailable to users once the edge server fails. To address this problem, we design a VM allocation framework based on Mixed-Integer Programming (MIP) combined with Multiple Routing Configurations (MRC), which provides fast failure recovery for a single node or link failure. Although this approach achieves high-quality VM allocations, it suffers from high computational costs, making it impractical in large-scale environments. To overcome this limitation, this paper makes two additional contributions. First, we introduce a Simulated Annealing-based approach, which derives near-optimal solutions within a reasonable computation time. We then propose a variant of MIP that considers only failures of critical nodes identified by betweenness centrality, thereby improving scalability and practicality. These VM allocation methods achieve a better trade-off between solution accuracy and computational efficiency. We demonstrate the effectiveness of the proposed methods through simulation experiments.

With the fast developments of modern wireless communications, beamforming has become a key issue to increase the system throughput and performance within the limited resources. Actually, accurate Angle of Arrival (AoA) estimation is critical and dominant for the beamforming techniques. However, literature methods, such as MUltiple SIgnal Classification (MUSIC) is very computational intensively, while methods as Root-MUSIC is working properly only for the Uniform Linear Array (ULA) receiving structure. Its performance will be degraded if applying to the Non-Uniform Linear Arrays (NULAs). To address these challenges, this paper proposes a novel low computational complexity AoA estimation algorithm via adopting the principle of orthogonality to reduce the required computation complexity and can be applied directly to both the ULA and NULA. Results from computer simulations and indoor measurements demonstrate that the proposed method has better AoA estimation performance than the Root-MUSIC and Min-Max methods in the NULA scenarios. And its accuracy is comparable to the conventional MUSIC algorithm with the low computational complexity advantage.

Reflectarrays (RAs) have gained attention to reduce coverage holes. The RA is measured using a bistatic radar cross-section (RCS). However, bistatic RCS measurements are more complex than monostatic RCS measurements. To solve this problem, the monostatic-bistatic equivalence theorem (MBET) has been proposed. The MBET enables the estimation of the bistatic RCS from the monostatic RCS. However, to the best of our knowledge, an MBET with a target as RA has not yet been reported. This paper presents the validation of the MBET for estimating the bistatic RCS of RAs. Two types of RAs for a tilt beam and a dual beam are designed for the target to apply MBET. MBET for RA is validated through simulations and measurements.

In wireless communications, error-correction codes (ECCs) are commonly used to improve the transmission quality, and more recently, it has become important to enhance confidentiality. To address this problem, we have previously proposed chaos-coded modulation (CCM), which utilizes chaos theory and encrypts modulation. In addition, we have proposed a CCM system that concatenates ECC, such as convolutional codes or low-density parity-check codes, to enhance the channel coding gain. However, owing to the encryption in CCM, there is no correlation between the Hamming distance of the bit sequence and the Euclidean distance of the modulated symbol sequence. Therefore, the accuracy of the log-likelihood ratio (LLR) used for decoding the ECC deteriorates compared to when linear modulation is used, limiting the improvement in the bit error rate (BER). In this paper, we propose an adaptive bit labeling method in CCM that improves the accuracy of LLR by employing an approximation algorithm and introducing a correlation between the Hamming and Euclidean distances. Numerical results show that at BER = 10^-3, the proposed scheme achieves 3 dB gain over linear modulation and 1 dB gain over the conventional CCM.

A Multi-Link Operation (MLO) using multiple Radio Frequencies (RFs) simultaneously has been investigated as a function in next-generation wireless Local Area Networks (LANs). MLO can improve throughput and transmission delay time characteristics by forming multiple links with different frequency bands and transmitting packets on multiple links. The paper proposes a redundant communication scheme in which the same packet is transmitted over multiple links to utilize MLO. We developed a multi-link redundant communication prototype using Universal Software Radio Peripherals (USRPs), and the transmission characteristics are evaluated using a wired experimental system. The prototype using four USRPs can be the redundant transmission of up to four links. In this prototype, each USRP has different characteristics. It was found that increasing the number of links used improves the packet error rate and transmission delay time characteristics even under interference from other systems. Furthermore, experimental evaluation results show that the prototype can receive video images usually, even under interference conditions, by transmitting video images for object detection as an application.