International Journal of Wireless and Microwave Technologies @ijwmt
Journal articles - International Journal of Wireless and Microwave Technologies
All articles: 648
A Density Control Algorithm For Wireless Sensor Network
Scientific article
If all nodes of a sensor network worked simultaneously, not only there would be a lot of redundant information, but also they would have great adverse impact on network throughput, bandwidth, latency, energy and network lifetime. Consequently, density control technology is necessary for sensor networks, because it can reduce the number of active sensor nodes under the precondition of ensuring network coverage and network connectivity. This paper proposes SNDC (Sensor Network Density Control), a location-free and range-free density control algorithm for wireless sensor network to keep as few as possible sensors in active state to achieve an optimal complete connected coverage of a specific monitored area by periodically sending three beacons of different transmission ranges. Inactive sensors can turn off sensing modules to save energy and sleep. Simulation results show that this algorithm can prolong the network lifetime and guarantee the small number of active nodes and complete network coverage.
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A Design Approach of GSM, Bluetooth and Dual band Notched UWB Antenna
Scientific article
In this paper, printed GSM Bluetooth dual band notch UWB antenna is presented. In this prototype corner cut patch for Bluetooth application and dual band notch characteristics of UWB antenna perform by inverting U- Slot in the radiation patch of antenna. With the enclosing of λ/4 stub in the patch of antenna for GSM (1.710-1.885 GHz) band operation. Simulation results show that the antenna yields an impedance bandwidth of 2.4-2.48 and 3-11 GHz with -10 dB reflection coefficients, except for the dual notched bands of 3.3-3.7 for Wi-MAX and 5.15-5.825 GHz for WLAN. The electrical characteristics in frequency domain show suitability of this antenna for use in UWB systems.
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A Design of Trust Degree Transfer Algorithm for P2P Network
Scientific article
The design of mechanism is used to calculate node reliability of incredible P2P network. The mechanism through matrix shows the trust relationship between nodes in the network, through matrix operation realizes the trust transfer process fast, and through a trusted server provides calculation service of trust degree for nodes in P2P network.
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A Discussion of a 60GHz Meander Slot Antenna for an RFID TAG with Lumped Element
Scientific article
In this paper, a novel approach to design an antenna for a transponder in radio frequency identification (RFID) is proposed. This approach is based on using a meander slot patch with a coplanar waveguide excitation (CPW). The RFID frequency chosen is the free 60 GHz band. The proposed circuit does not require complex package or bonding, thanks to the on-chip antenna, and it does not need battery. This technology is characterized by the low-cost, low-weight and low-area occupation. These particular specifications are important of this micro-RFID, especially if produced in large scale for the mass-market. Since the model of antennas in silicon technology is one of the main challenges, particularly for this proposal. The structure is simulated by using Computer Simulation Technology (CST). The antenna size is 1.95 * 1.99 mm2.This proposed antenna presents again which means a possibility to increase the readable range.
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A Group-oriented Access Control Scheme for P2P Networks
Scientific article
A group-oriented access control scheme is proposed for P2P (peer to peer) networks. In the proposed scheme, authentication control, admission control and revocation control are used in order to provide security services for P2P networks. Moreover, the proposed scheme can simply and efficient establish share key between two members without interactions, therefore it can perform secure communications with them. The analysis of security and performance shows that the proposed scheme not only can realize authentication and secure communication, but also can easily and efficiently add new group members and revoke malicious group members. Therefore, it is more efficient, and more practical protocol for P2P networks.
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A Hybrid MAS-CBR Framework with Optimization for Adaptive Supply Chain Design and Management
Scientific article
Global supply chains are increasingly characterized by complexity, uncertainty, and vulnerability to disruptions, creating a pressing need for intelligent, adaptive systems that support decentralized decision-making and real-time control. This paper develops a new framework that integrates Multi-Agent Systems (MAS) with Case-Based Reasoning (CBR) to address these challenges. The model leverages autonomous agents representing suppliers, manufacturers, distributors, retailers, and coordinators that negotiate through defined protocols while embedding CBR mechanisms to retrieve and adapt historical supply chain cases for enhanced responsiveness. An optimization layer, guided by both agent heuristics and case-driven initial solutions, targets key objectives such as cost minimization, lead-time reduction, and resilience improvement. Simulation experiments were conducted under both static and dynamid environments with disruptions including supplier failures and demand fluctuations. Results demonstrate that the proposed framework achieves convergence up to 34- 41% faster than heuristic-only baselines (p<0.05) and sustains solution quality with supply chain sizes increasing from 50 to 500 agents, indicating near-linear scalability. Comparative analysis further highlights adaptability in dynamic contexts and robustness under uncertainty. A case study illustrates practical deployment and validates its effectiveness. The findings provide evidence of a powerful synergy between MAS and CBR, with implications for next-generation supply chain intelligence.
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A Hybrid Mimo Technique for Better Ber in High Data Rate Wireless Communication System
Scientific article
The need for high data rate and better quality of service in wireless communications has become imperative in the past few years judging by user demand. Obtaining these requirements has become very challenging for wireless communication systems due to the problems of channel multi-path fading, higher power and bandwidth limitations. One of the most promising solutions to this problem is the Multiple Input Multiple Output (MIMO) system. This paper proposed a combined spatial multiplexing MIMO scheme with beamforming for high data rate wireless communication. The proposed transmission scheme combines the benefits of both techniques resulting in the system ability to transmit parallel data streams as well as provide beamforming gain. Actually, these diverse techniques, share the same requirement of multiple antenna elements, but differ in the antenna element spacing necessary for the different schemes to work. Thus, smart antenna arrays were proposed as a possible solution and were adopted at both the transmitter and the receiver. The proposed hybrid technique provides better Bit Error Rate (BER) performance than the conventional MIMO, spatial multiplexing or beamforming technique alone under the same simulation environment.
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A Hybrid Selection Approach Based on Advanced Antenna Technologies for Cellular LTE-A
Scientific article
While addressing cellular network performance issues, resolving problems with coverage and capacity is critical. The coexistence of cellular networks and smaller femtocells working within the macrocell area is among the alternative solutions. The simultaneous functioning of macrocells and femtocells, however, introduces new technical challenges that pose serious concerns about the efficiency of cellular networks. Therefore, this work proposes a hybrid approach based on variant advanced antenna technologies including MIMO methods and antenna systems for the deployment of femtocells and macrocells. To accomplish this, three distinct LTE-A network models with and without femtocells are set up with different architectures for high-density areas. The models further cover tri-sector and omnidirectional antenna systems to analyze the relevant effects on the performance of the LTE-A macrocells as well as femtocells. Also, to extend the analysis, integration of different MIMO methods for the models is provided. The networks are implemented and the link performance evaluation is carried out with regard to spectral and energy efficiency, cell and user throughputs, fairness, and SINR. The results contribute to determining the performance gains and energy saving of the LTE-A femtocells as well as macrocells by employing different advanced antenna technologies.
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Scientific article
Financial fraud presents a major challenge to financial establishments, with Nigerian banks losing over ₦685 million to digital fraud in 2023. Traditional rule-based detection systems have high false-positive rates and limited adaptability; meanwhile, existing machine learning models are generally trained on non-localized datasets that ineffectively represent African fintech ecosystems. This study proposes a Hybrid Stacked Ensemble framework for fraud detection that improves detection accuracy, robustness, and explainability in localized financial environments. The proposed framework combines Random Forest, Gradient Boosting, and Extra Trees as base learners with XGBoost as the meta-classifier and integrates SHAP for model explainability. Performance was evaluated using the Kaggle credit card fraud dataset (284,807 transactions; 0.17% fraud) and a newly curated Nigerian synthetic dataset (150,000 transactions; 1.12% fraud) incorporating localized fraud patterns such as POS, USSD, mobile money, and rural–urban transaction disparities. Class imbalance was addressed using SMOTE oversampling, random undersampling, and cost-sensitive learning. On the Kaggle dataset, the Hybrid Ensemble achieved 99.96% accuracy, 97.14% precision, 79.70% recall, an F1-score of 0.880, and an AUC-ROC of 0.986, outperforming the best individual classifier in recall and AUC-ROC. On the Nigerian dataset, where individual classifiers achieved recall below 3.1%, the proposed framework attained 64.10% recall, an F1-score of 0.460, and an AUC-ROC of 0.866, representing improvements of 106.77% in recall and 488.57% in F1-score over XGBoost. Ablation studies and paired t-tests (p < 0.001) confirmed the effectiveness of the stacking strategy. The study contributes a localized Nigerian fraud dataset, a hybrid stacked ensemble architecture that exploits classifier diversity for improved fraud detection, and an explainable AI framework that enhances transparency, accountability, and regulatory compliance. Deployment as a containerized Streamlit application with JWT authentication demonstrates the framework's practicality as a scalable, explainable, and deployment-ready solution for fraud detection in Nigeria and similar African financial ecosystems.
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A Linear Polarized Coaxial Feeding Dual Band Circular Microstrip Patch Antenna for WLAN Applications
Scientific article
A dual band linear polarized micro-strip antenna is designed and simulated to obtain electronic circuit miniaturization of an antenna in high speed wireless local area networks (IEEE 802.11a standard). The proposed antenna contains a substrate layer (FR-4 lossy) with a dielectric constant of 4.4 and there is a circular patch on the upper layer of the substrate. The coaxial probe feed is used to excite the desired antenna which reduces the spurious radiation and hence obtained good efficiency. It is shown that using cavity model 20% excess bandwidth can be achieved while maintaining the lower size of the antenna. An 'E' shaped slot is introduced in the radiating patch to obtain dual band resonance frequency with maximum current distribution on the surface. Finally the simulated results using Computer Simulation Technology (CST) microwave studio 2009 in this design is compared with manual computation results which are found to be suitable for WLAN applications.
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A Low-Cost Noise Wave Correlator for Noise Parameters Extraction by Cold Noise Power Measurement
Scientific article
Conventionally, the noise parameters of a Device under Test (DUT) which generally characterize the noise performance of the DUT, are obtained via the impedance tuner technique. The authors have previously presented a technique which eliminates the need for impedance tuner, and rather employs an 8-port network that enables the extraction of the noise correlation matrix of a given DUT and thus its noise parameters. In this paper, we present a further simplification of the 8-port network technique, which also eliminates the need for a conventional external noise source. Cold noise powers emanating from a DUT are measured via a 6-port network with the aid of matched termination. The measured noise powers provide sufficient information for determining the noise wave correlation matrix of a DUT, which are then converted into the conventional 2-port noise parameters. The proposed technique is simple, fast and is verified to give a good estimation of the noise parameters of selected DUTs.
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A Method of Target Detection in Remote Sensing Image Captured based for Sensor Network
Scientific article
A refined energy constrained minimization method is developed for target detection in hyperspectral remote sensing images captured by unmanned aerial vehicles (UAVs) during their surveillance missions, which has been tested in the experiment under this paper. The experiment result proves, in the detection process, this method can effectively restrain noises so far as the spectral characteristics of any potential target are known, and find sub-pixel targets out effectively from the hyperspectral remote sensing image in unknown background spectrum.
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A Metric for Evaluating Security Models based on Implementation of Public Key Infrastructure
Scientific article
International security evaluation metrics are too general and not focused on evaluating security models implemented using Public Key Infrastructure (PKI). This study was conducted to develop the metric for evaluating security models based on implementation of PKI by using insights from literature. Literature review was done based on inclusion and exclusion criteria. The developed metric was tested using ranking attributes and ranking scales. The results reveal that the developed metric is applicable for evaluating security models based on implementation of PKI. This is verified by the tabular results indicating evaluation of selected security models based on implementation of PKI by using ranking attributes and ranking scales. This study contributes to the body of knowledge a metric for evaluating security models based on implementation of PKI.
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A Multi-UAV Planning Framework for Task Allocation, Route Optimization and Trajectory Smoothing
Scientific article
Coordinated mission planning for multiple unmanned aerial vehicles in cluttered static three-dimensional environments requires consistent treatment of obstacle-aware motion, fleet-level task allocation, route sequencing, and executable trajectory generation. In many existing approaches, these elements are optimized separately, or fleet-level decisions are made using simplified geometric distances that do not accurately reflect UAV-specific motion feasibility in obstacle-constrained space. This paper presents a Multi-UAV Planning Framework for Task Allocation, Route Optimization and Trajectory Smoothing for static environments with known obstacle geometry. In the first stage, an offline single-UAV planner based on a hybrid Differential Evolution and Enhanced Whale Optimization Algorithm computes feasible raw paths for all relevant ordered node pairs and constructs a UAV-specific directed travel-cost matrix. In the second stage, these planner-derived matrices are used for feasibility-aware balanced task distribution and route optimization with exchange-based refinement under a composite total-cost–makespan objective. In the third stage, the raw paths corresponding to the final selected routes are reconstructed and transformed into executable trajectories by adaptive cubic B-spline smoothing. Experimental evaluation was conducted at the local-planning, fleet-planning, and smoothing levels in known static environments. The hybrid planner generated high-quality pairwise obstacle-avoiding paths and exhibited favorable convergence behavior relative to standard WOA, PSO, DE, SOS, and GWO in the tested scenarios. At the fleet level, the full framework reduced makespan by 2.1–3.4% and the composite objective by 0.9–1.4% relative to balanced partitioning without exchange refinement on benchmark instances. In the smoothing stage, the adaptive cubic B-spline reduced path length by 8.5% and maximum curvature by 41.5% relative to the unsmoothed polyline representation. These results demonstrate that the proposed hierarchical formulation is computationally effective, physically consistent, and well suited to multi-UAV mission planning.
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A Multi-objective Fuzzy Logic based Multi-path Routing Algorithm for WSNs
Scientific article
Wireless Sensor Networks (WSNs) have included one of the major challenges as energy efficiency. The optimal routing is the better solution for tackling the energy-efficiency problem as the energy is consumed with massive amount by the communication of a network. The clustering technique is the reliable data gathering algorithm for achieving energy-efficiency. The data transmit to the cluster head (CH) by each node that belonging to the cluster for clustered networks. The data transmission towards the BS or SINK is occurred once all data is received by CH from all member nodes. In multi-hop environments, the data transmission happens via other cluster-heads. It leads to the earlier death of CHs that are nearer to the SINK because of the heavy inter-cluster relay, i.e. called as hot-spot problem. The existing methods of unequal clustering approaches have been used to resolve this issue. The algorithms generate the clusters with smaller sizes while approaching towards the sink for reducing the intra-cluster relay. These algorithms didn’t consider the hotspot problem very effectively. Therefore, in this work, we introduce a multi-objective fuzzy logic based multi-path routing solution (MOFL-MPR) to address the above said problem. The popular clustering algorithms have been evaluated the performance results and the MOFL-MPR is outperformed the existing algorithms based on the obtained experimental results in terms of stable CH selection, energy efficiency and better data delivery.
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A Multi-step Attack Recognition and Prediction Method Via Mining Attacks Conversion Frequencies
Scientific article
Massive security alerts produced by safety equipments make it necessary to recognize and predict multi-step attacks. In this paper, a novel method of recognizing and predicting multi-step attacks is proposed. It calculates attack conversion frequencies, and then mines the multi-step attack sequences. On this basis, it matches the new alert sequences dynamically, recognizes the multi-step attacks and predicts the next attack step. The result of experiment shows that the proposed method is effective and accurate.
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A Multicast Routing Mechanism in Mobile Ad Hoc Network Through Label Switching
Scientific article
Merging MPLS into multicast routing protocol in Mobile Ad hoc network is an elegant method to enhance the network performance and an efficient solution for multicast scalability and control overhead problems. Based on the Wireless MPLS technology, the mechanism and evaluation of a new multicast protocol, the Label Switching Multicast Routing Protocol (LSMRP) is presented in this paper.
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A New Framework of Honeypots Network Security Using Linear Regression Decision Algorithm
Scientific article
The expansion of the Internet and shared networks aids to the growth of records generated by nodes connected to the Internet. With the development of network attack technology, all Internet hosts have become targets of attack. When dealing with new attacks (such as smart ongoing threats) in a complex network environment, existing security strategies are powerless. Compared to existing security detection techniques, honeypot systems (IoT research) can analyze network packets or log files being attacked, and automatically monitor potential attack. Researchers can use this data to accurately capture the tactics, strategies, and techniques of threat actors to create defense strategies. However, for general security researchers, the immediate topic is how to improve the honeypot mechanism that attackers do not recognize and quietly capture their actions. Honeypot technology can be used not only as a passive information system, but also to combat zero-day and future attacks. In response to the rapid development of honeypot recognition with machine-learning technology, this paper proposes a new model of machine learning based on a linear regression algorithm with application and network layer characteristics. As a result of the experiment, we found that the proposed model was 97% more accurate than other machine learning algorithms.
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A New Half-blind Algorithm of Smart Antenna for Mobile Terminal
Scientific article
The core of smart antenna is its adaptive algorithm. For the characteristics of TD-SCDMA mobile terminal, we analyze the advantages and disadvantages of various algorithms and propose a semi-blind algorithm combining the NLMS algorithm and the CMA algorithm in this paper. The new semi-blind algorithm has strong robustness and low complexity. It is suitable for smart antenna of TD-SCDMA mobile terminals.
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A New Joint Antenna Selection Algorithm Based on Capacity
Scientific article
Antenna Selection in MIMO systems can increase the system capacity, reduce the MIMO system complexity and cost of radio links effectively. In this paper, a new joint antenna selection algorithm was presented which can adaptively change the number of the selected transmitting and receiving antenna number according to the channel station. It can obtain the similar system capacity with the optimal joint antenna selection algorithm in any correlation coefficient, but the calculated amount is far less than the optimal joint algorithm.
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