The imminent wireless technologies are demanding fusion of several networks with diverse technologies. A convenient user device for such an environment is the multihomed host, which is capable of making use of simultaneous multiple connections of heterogeneous networks and smartly distributing/receiving data among them. The aim of this work is to develop a mechanism for assessing the multihoming concept and to propose a system model for increasing its applicability. The proposed model provided a novel user-centric scheme for multihoming for multi-radio access technologies (multi-RAT). It is considered an evolution of traffic offloading for gaining more capacity, higher data rates, and real-time services. This work assumes data classifications, evaluates and ranks the available connections, and utilizes the application data in an unequal load balance scheme. This is achieved by analyzing the performance of three of the most widely used alternative-choice for multiple attributes decision making (MADM) methods. The analytical hierarchy process (AHP), along with a utility equation, is applied to the system model for unequal load balance solution. The proposed model is targeting an energy efficient mechanism which satisfies application needs. Moreover, it reveals an efficient transmission mechanism for a better quality of service, traffic management, and availability solutions. The simulation results show that the proposed system surpassed its former counterparts.

The major problem of Orthogonal FrequencyDivision Multiplexing (OFDM) is its High Peak-to-AveragePower Ratio (PAPR). The High PAPR increases the complexityof Analogue to Digital (A/D) and Digital to Analogue (D/A)converters and also reduces the efficiency of Radio FrequencyHigh Power Amplifier (RF HPA). In this paper, we presentDiscrete Fourier Transform (DFT), Discrete HartleyTransform (DHT) and Zadoff-Chu Transform (ZCT)precoders for both clipping and clipping and filtering to reducePAPR. The DFT precoder provides better PAPR comparedwith clipping, clipping and filtering OFDM. In addition toimprove the bit error rate (BER) this has also been taken as aperformance evaluation parameter. The DFT precoded systemis better than ZCT precoder by about 1.2 dB and better thanDHT precoder by about 1.5 dB at the same ComplementaryCumulative Distribution Function (CCDF) value. The DFTprecoder is better than clipping by 1dB and better thanclipping and filtering technique by about 6dB for OFDMsystem at the same parameters. The DFT Precoded system isbetter than other precoder as well as it improvement in BERperformance of the original OFDM by about 1 dB at the sameBER

Smart agricultural systems are continually evolving to provide high-quality planting and defend against threats such as climate change, which necessitate improved adaptation and resource allocation. IoT technology offers a cost-effective approach to monitoring and managing system performance. However, this approach faces challenges, including connectivity issues and complex decision-making. While researchers have studied these problems individually, no fully automated solution has addressed them simultaneously. There is still a need for an offline solution that manages multiple processes and reduces human error. This paper introduces an AI-powered edge computing system that serves as an early-warning solution for climate impacts. This system enables autonomous management through an Agentic AI model that observes, predicts, decides, and adapts. It provides a low-cost AIoT platform for data forecasting, classification, and decision-making, converting sensor data into actionable insights. The system integrates forecast evaluation with real-time data comparisons to optimize scheduling, efficiency, sustainability, and yields. Moreover, this solution is totally autonomous and independent of internet connectivity. Demonstrating its superior performance, it reduced errors by 50% and achieved an R-squared value of 0.985.

In this paper, Discrete Fourier Transform Precoded Orthogonal Frequency Division Multiplexing Multilayer Interleave Division Multiple Access (DFT P OFDM ML IDMA) communication system has been proposed. Chip by Chip (CBC) iterative receiver is used to recover the data in each layer. Also, different precoding techniques has been applied with and without clipping in the proposed P OFDM ML IDMA. Simulation results confirm that the DFT precoder provides better PAPR reduction compared with other precoded methods with and without clipping. BER and PAPR simulation results shows that the proposed DFT P OFDM ML IDMA brings about 7 dB PAPR reduction and 0.5 dB BER improvement compred with OFDM ML IDMA. The Simulations for the proposed DFT P OFDM ML IDMA with 2 - 6 layers shows that the variation is 3.4 to 8.2 dB for the PAPR and 7.8 to 8.7 dB for the BER. So, the adaptive modulation can be simply realized by the proposed DFT P OFDM ML IDMA

The smart agriculture system requires high efficiency to automatically maximize crop yields and minimize losses. Wireless sensor networks (WSNs) are essential for maintaining system sustainability through sensing and connectivity. However, they encounter challenges related to cost, interoperability, and reliability. Efforts have been made to expand sensing capabilities while managing costs and addressing variability in sensor communication and power consumption. Despite these efforts, a comprehensive solution—especially for orchard fields—remains undeveloped. This study introduces a coordinated WSN design to optimize sensing and connectivity in agricultural fields. We employ an integrated sensing and connectivity (ISAC) strategy to create a complete solution. Our hybrid approach combines graphical computation with distance-vector algorithms for reliable, cost-effective deployment. Additionally, resilient connectivity is achieved through effective channel modeling and adaptive beamforming. The proposed method, combined with quantitative heterogeneous network selection using MLR-AHP, addresses interoperability issues and improves network resilience. Results indicate improved sensor placement and wireless ranking, even with only 5 nodes. The solution extends sensor battery life, maintains 99% coverage, and empirical tests validate its effectiveness for designing and deploying WSNs in orchard fields.