This paper investigated the relationship between broadband penetration and economic growth in Nigeria. The secondary data for the study were collected from the World Bank and this includes data on Internet broadband usage and Gross Domestic Product while the primary data were generated from the questionnaire administered to the respondents. The descriptive statistics and the ordinary least square regression analytical method were used to examine the relationship between broadband penetration and economic growth. It was discovered that a per cent increase in broadband penetration will only increase output (Economic Growth) by 0.1 per cent in Nigeria. The data analysis showed a significant and positive relationship between broadband penetration and economic growth. The study thus recommended that efforts must be made towards the implementation of broadband policy and effective utilization of the broadband network. Also, better telecommunication reforms that will create enabling environment and encourage the inflow of broadband networks should be made.

Over time, higher demand for data speed and quality of service by an increasing number of mobile network subscribers has been the major challenge in the telecommunication industry. This challenge is the result of an increasing population of human race and the continuous advancement in mobile communication industry, which has led to network traffic congestion. In an effort to solve this problem, the telecommunication companies released the Fourth Generation Long Term Evolution (4G LTE) network and afterwards the Fifth Generation Long Term Evolution (5G LTE) network that laid claims to have addressed the problem. However, machine learning techniques, which are very effective in prediction, have proven to be capable of great importance in the extraction and processing of information from the subscriber’s perceptions about the network. The objective of this work is to use machine learning models to predict the existence of traffic congestion in LTE networks as users perceived it. The dataset used for this study was gathered from some students over a period of two months using Google form and thereafter, analysed using the Anaconda machine learning platform. This work compares the results obtained from the four machine learning techniques employed that are k-Nearest Neighbour, Support Vector Machine, Decision Tree and Logistic Regression. The performance evaluation of the ML techniques was done using standard metrics to ascertain the real existence of congestion. The result shows that k-Nearest Neighbour outperforms all other techniques in predicting the existence of traffic congestion. This study therefore has shown that the majority of LTE network users experience traffic congestion.

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Mobile number portability (MNP) is a telecommunication network property which allows subscribers to retain their mobile phone numbers when changing from one network provider to another. It serves as the yardstick for increasing competition and for improving quality of service among network providers, because subscribers have the freedom to migrate from one network provider to another. In the past, quality of service was poor due to low transparency from the end of the network providers but with the introduction of MNP, there will be check and balances among the network providers as each of them are trying to woo the subscribers to its network. This paper explores the benefits of MNP and some of its applications in the telecommunication industry. In this work, some arising issues concerning MNP were put together in a questionnaire and copies were administered to respondents of different sex, ages, locations and networks across six states in south west Nigeria. Thereafter, some hypotheses relevant to MNP were formulated for test based on some factors influencing the success of MNP. These hypotheses were later analyzed and tested using chi-square. The results of our analysis show that there is no significant impact of social influence on mobile number portability scheme among mobile users. That means there is skepticism of acceptance among the elite group users but with increase on quality of service and reduction in tariff thus this acceptability will ratio increase.