Developing Public Policy Options for Access to Drinking Water in Peripheral, Disaster and Polluted Rural Areas: A Case Study on Environment-Friendly and Conventional Technologies

Peripheral, disaster and polluted rural areas (PDP rural areas) are generally perceived as a “Cinderella” of water public policy measures, deepening the rural-urban cleavage in terms of opportunities for a decent life. The main goal of the study is to develop public policy options regarding the supply of safe drinking water in Romanian PDP rural areas. The main instrument to achieve it is an ex-ante policy analysis of three solutions: a conventional technology, based on chlorine, a green technology using an advanced oxidation process with bio-filter (O3BioFilter), and “do nothing”. Environment protection, social equity, technical performance, economic efficiency and political feasibility were the criteria selected for analysis, within a focus-group. Several qualitative and quantitative methods were used: evaluation matrix, weighted cost-effectiveness and break-even point. The results of the first two indicate that the O3BioFilter has the best score, but not much higher than the conventional alternative (10% higher), revealing a possible path-dependency to familiar technologies. This analysis is not a ready-made solution valid in any case, nor a direct indication of “the best choice”, but a decision tool in the adoption and implementation of sustainable water public policies

CSVAG: Optimizing Vertical Handoff Using Hybrid Cuckoo Search and Genetic Algorithm-Based Approaches

One of the primary challenges that wireless technology in the present generation is facing is always best connected (ABC) service. This is possible only when the wireless overlay networks follow a cooperative and coordinated process. Vertical handoff is one such process. Concerning this process, the main challenge is to develop algorithms that take care of optimal connection management with proper resource utilization for uninterrupted mobility. In this paper, we develop a new hybrid cuckoo search (CS) and genetic algorithm (GA) that maximizes the performance of heterogeneous wireless systems in terms of minimizing latency, handover failure probability, and enhancing the throughput. We focus on an optimized simulation framework to demonstrate the advantage of our hybrid model. It can be discerned from the simulation analysis that the proposed hybrid technique increases throughput by 17% and 8% compared to the cuckoo search and genetic algorithms applied individually. The performance of the proposed scheme is promising for applications wherein the handoff mechanisms have to be optimized to control frequent handoffs to further reduce the power consumption of user equipment

Multi-User Massive MIMO System with Adaptive Antenna Grouping for Beyond 5G Communication Network

Error-correcting codes with limited errors and higher spectral efficiency are the main concern for wireless communications. In the current situation, research is increasing daily to satisfy the growing demand for users with improved QoS. Adaptive Antenna Grouping (AAG) with a multilevel space–time trellis coding scheme in the Multi-User Massive MIMO system is the better option to provide flexible data transfer speeds, encoding gains, and gain in diversity with improved spectral efficiency and low decoding complexity, including the power optimization by reduced SNR at the same Symbol Error Rate/Frame Error Rate (SER/FER). The prior aim of maintaining spectral efficiency is achieved by using Massive MIMO. This paper presents the AAG according to the channel state information in the Massive MIMO scenario. The impact of the proposed model on standard ITU-R M.2135 scenarios is also demonstrated in this paper