Browsing by Author "Rehman, Gohar"
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Item Economical and sustainable power solution for remote cellular network sites through renewable energy(IEEE, 2017) Kabir, Asif; Kitindi, Edvin J.; Jaffri, Zain ul Abidin; Rehman, Gohar; Ubaid, Faisal Bin; Iqbal, M. ShahidMobile network operators (MNOs) are always striving to enhance the network coverage and for provision of services to remote rural areas. However, power supply to the infrastructures is a main challenge to the MNOs especially in terms of sustainability, economic optimum and green energy in developing countries like Pakistan for the growth of cellular networks. Renewable energy (RE) based solutions for cellular operators not only provide numerous profits but it also reduces the overall CO2 emissions. This paper presents the idea of the PV-Solar system along with grid power to provide economic and environmental friendly energy model for the remote base station and community. Feasibility of the proposed system is checked via HOMER software. Analysis and simulation results shows that the proposed model is optimal and energy efficient solution for next-generation cellular network (5G) in context with different scenarios.Item The role of caching in next generation cellular networks: A survey and research outlook(Wiley, 2019) Kabir, Asif; Rehman, Gohar; Gilani, Syed Mushhad; Kitindi, Edvin J.; affri, Zain Ul Abidin J; Abbasi, KhurrumMustafaMobile applications and social networks tend to enhance the needs for high-quality content access. To address the expeditious growing demand for data services in 5G cellular networks, it is important to develop distribution techniques and an efficient content caching, aiming to significantly reduce redundant data transmission and, thus, improve the efficiency of the networks. In modern communication systems, caching has emerged as a vital tool for reducing peak data rates. It is anticipated that energy harvesting and self-powered small base stations are the fundamental part of next-generation cellular networks. However, uncertainties in energy are the main reason to adopt energy efficient power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using the edge cooperative caching such as energy efficient design can also be achievable, which reduces the usage of the capacity limited SBSs backhaul and the energy consumption. To support the huge power demand of cellular network, renewable energy harvesting technologies can be leveraged. In addition to this, power supply to the infrastructures is themain challenge to the mobile network operators (MNOs) especially in terms of economic optimum, sustainability, and green energy in developing countries for the growth of cellular networks. Renewable energy–based solutions for MNOs not only reduce the overall carbon dioxide emissions but also provide numerous profits.Item User aware edge caching in 5G wireless networks(IJCSNS, 2018) Kabir, Asif; Iqbal, M.Shahid; Jaffri, Zain ul Abidin; Rathore, Shoujat Ali; Kitindi, Edvin J.; Rehman, GoharWireless technology has become an ultimate weapon in today’s world. Caching has emerged as a vital tool in modern communication systems for reducing peak data rates by allowing popular files to be pre-fetched and then stored at the edge of the network. Caching at small cell base stations has recently been proposed to avoid bottlenecks in the limited capacity backhaul connection link to the core network. For predicting the popularity of the content, we need to analyze the behavior of the user, understanding collectively the behavior beneficial for content trend forecasting and improve network performance. The proposed model predicts the intensity of human emotions through social media (Twitter) and the classifier evaluates the features which are related to user behaviors and, finally, values of features are pushed to the user profile. We further demonstrate how emotions extracted from Twitter can be utilized to improve the forecasting, describing things in a new way which can further be exploited as an optimization basis for network performance enhancement.