An alternative to CMOS VLSI called Quantum Cellular Automata (QCA) is presently being researched. Although a few basic logical circuits and devices have been examined, very little, if any, research has been done on the architecture of QCA device systems. In the context of nano communication networks, data transmission that is both dependable and efficient is still critical. The technology known as Quantum Dot Cellular Automata (QCA) has shown great promise in the development of nano-scale circuits because of its extremely low power consumption and rapid functioning. This study introduces a unique nano-communication parity-based arithmetic circuit that is reversible, error-detecting, and error-correcting. The minimal outputs are needed for the proposed structure. Based on QCA technology, the proposed nano-communication network makes use of reversible logic gates. The performance increase of the suggested parity generator and checker circuit is significant in terms of clock delay, size, and number of cells.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.

The technological development and growth of the telecommunications industry have had a great positive impact on the education, health, and economic sectors, among others. However, they have also increased rivalry between companies in the market to keep and acquire new customers. A lower level of market concentration is related to a higher level of competitiveness among companies in the sector that drives a country’s socioeconomic development. To guarantee and improve the level of competition, it is necessary to monitor the concentration level in the telecommunications market to plan and develop appropriate strategies by governments. With this in mind, the present work aims to analyze the concentration prediction in the telecommunications market through recurrent neural networks and the Herfindahl-Hirschman index. The results show a slight gradual increase in competition in terms of traffic and access, while a more stable concentration level is observed in revenues.

Nowadays, international exchanges are becoming more and more frequent in the world. As a global language, English can establish a communication bridge between different countries and nationalities, and its importance is obvious. Since 2001, China has gradually added English education to the curriculum plan of primary schools in various regions. Later, with the deepening of the industry’s understanding of English teaching, the education reform has also followed up. It can be said that the level of educators and educates is rising spirally. However, there are still many restrictive factors in the current situation of primary school students’ learning English, among which the more prominent factors are the strength of English teachers and the evaluation mechanism for students’ learning achievements.

Through the research on the communication mode of rural youth e-commerce, the paper puts forward that there are some advantages and many problems in the e-commerce engaged in.

This paper studies the patent race problem of communication enterprises investing in communication technologies, and constructs a portfolio optimization model which considers the expected returns, investment risks, and replacement costs, in order to achieve the dual goals of maximizing the net investment income of backward enterprises and minimizing the expected investment risk. Through numerical experimental analysis, the optimal investment portfolio strategy under different risk levels and the impact of different risk levels on the net income of lagging company are obtained. The research results show that due to the backward research in the first stage of the backward enterprises, when their own investment decision-making power is relatively high, they can focus on the development of self-interested key technology areas in order to achieve the victory of the patent race.