Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
This paper presents a long-range experimental demonstration of multi-mode multiple-input multiple-output (MIMO) transmission using orbital angular momentum (OAM) waves for Line-of-Sight (LoS) wireless backhaul applications. A 4 × 4 MIMO system employing distinct OAM modes is implemented and shown to support multiplexing data transmission over a single frequency band without inter-channel interference. In contrast, a 2 × 2 plane wave MIMO configuration fails to achieve reliable demodulation due to mutual interference, underscoring the spatial limitations of conventional waveforms. The results confirm that OAM provides spatial orthogonality suitable for high-capacity, frequency-efficient wireless backhaul links. Experimental validation is conducted over an 100 m outdoor path, demonstrating the feasibility of OAM-based MIMO in practical wireless backhaul scenarios....
Wireless sensor networks (WSNs) are used in environmental monitoring, urban planning, healthcare, and industrial automation. These networks must transmit data to succeed. Energy usage, throughput, and latency in the shared wireless medium depend on the medium access control (MAC) layer resource distribution. Data transmission inside networks is vital to their efficiency and efficacy. An analytical research assesses the MAC protocols under consideration and compares their communication properties to WSN routing methods. This paper presents an analytical study of MAC and modeling development of a distributed estimator that addresses the challenges provided by noisy sensory measurements and loss rates in wireless communications. These protocols’ suitability for WSN applications is an important goal. Data transfer from sensor nodes to a central sink or gateway requires WSN routing. Proactive, reactive, and hybrid routing approaches are compared for packet delivery ratio, end-to-end latency, communication, and energy economy. Routing protocols are affected by dynamic network characteristics such as node failures and movement in this research....
This paper proposes a wireless sensor network (WSN)-based next-generation battery management system (BMS) architecture for large-scale battery packs in electric vehicles (EVs) and energy storage systems (ESS). Traditional wired BMS offers high reliability but suffers from complex wiring, high installation costs, and maintenance difficulties. This study compares the characteristics of key wireless communication technologies such as Bluetooth Low Energy (BLE), Zigbee, LoRa, and Ultra-Wideband (UWB) to optimize wireless BMS design. Moreover, the performance and cost-effectiveness of wired and wireless BMS are compared based on existing literature and simulation data analysis. Technical measures to improve data reliability and security in wireless BMS environments are also proposed. The findings of this study can serve as a valuable reference for the commercialization and standardization of wireless BMS in EV and ESS applications....
To manage and optimize constantly evolving wireless networks, existing machine learning (ML)- based studies operate as black-box models, leading to increased computational costs during training and a lack of transparency in decision-making, which limits their practical applicability in wireless networks. Motivated by recent advancements in large language model (LLM)-enabled wireless networks, this paper proposes ProWin, a novel framework that leverages reinforced in-context learning to design task-specific demonstration Prompts for Wireless Network optimization, relying on the inference capabilities of LLMs without the need for dedicated model training or finetuning. The task-specific prompts are designed to incorporate natural language descriptions of the task description and formulation, enhancing interpretability and eliminating the need for specialized expertise in network optimization. We further propose a reinforced in-context learning scheme that incorporates a set of advisable examples into task-specific prompts, wherein informative examples capturing historical environment states and decisions are adaptively selected to guide current decision-making. Evaluations on a case study of base station power control showcases that the proposed ProWin outperforms reinforcement learning (RL)-based methods, highlighting the potential for next-generation future wireless network optimization....
With the essential increase in the use of wireless sensor networks, security is a major concern in every field. Intrusions have become frequent and present a significant challenge in today’s world. It is valuable to explore the feasibility of designing and rigorously assessing intrusion detection systems within network simulation environments. Wireless sensor network security risk prediction is a key aspect of wireless network security technology. Analyzing the current state of wireless networks, security is a crucial step in ongoing research in the field of network security. In this paper, we discuss how OMNET++ is used for intrusion detection for different types of attacks in wireless sensor networks, what frameworks and protocols are used in OMNET++, and why OMNET++ is used, along with a few security attacks in wireless networks....
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