The potential of fifth‐generation (5G) and beyond wireless connectivity is to deliver higher data rates, much lower latency, more frequent increase in channel capacity, and significant improvements in Quality of Service (QoS), compared to the current Long Term Evolution (LTE) networks. The continued growth of smart devices, the introduction of trending multimedia applications, and the dramatic increase in demand and use of wireless data communication are already causing a significant load on current mobile networks. 5G wireless networks, with enhanced user data rates, delays, capacity and QoS, are anticipated to solve many of the existing problems of mobile networks. In this study, we review the emergent wireless LTE‐A and 5G networks to provide an overview of the challenges and the solutions suggested in recent literature towards forthcoming 6G networks. We first discuss the new structural changes associated with the Radio Access Network (RAN) design, heterogeneous network and LTE or LTE‐Advanced (LTE‐A) network. To understand the challenges and research gaps in 5G and beyond networks, the paper reviews the outstanding features of the new QoS and Self‐Organization Networks (SON) related to the emerging 5G networks. Data rates, bandwidth and coverage have been given significance throughout this review because these are some major challenges towards 6G networks. Since understanding the present state of 5G usage is critical to its adoption, the paper also discusses related field tests, trials, and simulation tests. Finally, we identify existing major research problems and outline potential research areas.

Bangladesh’s economic development is largely dependent on the power sector, which promotes sustainability and growth. The country’s future energy security, however, is seriously threatened by the natural gas reserves running out by 2028. As a result, the current energy mix has to be modified right away to ensure Bangladesh’s sustained economic growth. This research paper offers a thorough analysis of Bangladesh’s power sector’s current state. With a focus on important metrics like installed capacity, electricity generation, and distribution infrastructure, the study seeks to provide insights into the sector’s opportunities, challenges, and strengths. The research highlighting the importance of energy security and forecasting the projected energy demand in Bangladesh. The study also looks at current projects and advancements that have shaped Bangladesh’s power industry. This research also provides an ideal energy option that supports Bangladesh's sustainable growth. This analysis offers significant insights into the dynamics of the power industry in Bangladesh, elucidating it is present trajectory, the challenges it encounters, and the potential avenues for achieving a more sustainable and resilient energy future.

Cellular networks are moving towards increasing heterogeneity by deploying more small cells into macro base station (MBS) to meet rapidly growing traffic demands. To leverage the advantages of these small cells, mobile users should be offloaded onto small base stations (BSs), which will typically be lightly populated and can give a higher data rate by presenting the mobile users with many more channels than the MBS. Likewise, a more balanced cell association will lessen the pressure on the MBS, allowing it to serve its remaining users more effectively. This paper addresses the cell association challenge for Quality of Service (QoS) provisioning in terms of throughput and load-balancing for 5G and future generation networks. This problem is quite challenging because BSs have varying backhaul capacities and users have varying QoS needs. Most of the previous studies are based on reference signal received power (RSRP), signal to interference and noise ratio (SINR) or its variants and most importantly majority of them are not load-aware. Therefore, a modified load-aware biased cell association scheme based on distance is proposed to attain better QoS provisioning in terms of throughput and load-balancing. Simulation results depict that the proposed load-aware-based method outperforms conventional cell association schemes based on RSRP and its variants, and in terms of throughput and load-balancing. Furthermore, the algorithm’s complexity has been assessed through a comparison and analysis of computational time, demonstrating better performance compared to state-of-the-art techniques.

Efficient energy demand forecasting is pivotal for addressing energy challenges in remote areas of Bangladesh, where reliable access to energy resources remains a concern. This study proposes an innovative approach that combines linear regression analysis (LRA) and inverse matrix calculation (IMC) to forecast energy demand accurately in these underserved regions. By leveraging historical energy consumption data and pertinent predictors, such as meteorological conditions, population dynamics, economic indicators, and seasonal patterns, the model provides reliable forecasts. The application of the proposed methodology is demonstrated through a case study focused on remote regions of Bangladesh. The results showcase the approach's effectiveness in capturing the intricate dynamics of energy demand and its potential to inform sustainable energy management strategies in these remote areas. This research contributes to the advancement of energy planning and resource allocation in regions facing energy scarcity, fostering a path towards improved energy efficiency and development. These techniques can be applied to estimate short-term electricity demand for any rural or isolated region worldwide.

The escalating demand for data in wireless communication systems has posed significant challenges in recent years. This trend is predicted to continue, with explosive data usage and evolving quality of service demands from mobile users. The rapid increase in traffic demand, combined with the intricate nature of heterogeneous network (HetNet) scenarios, has significantly heightened the challenges confronting mobile network operators. These challenges encompass service quality, load distribution, coverage, and the overall user experience. Conventional approaches that prioritize maximum received power in the cell association mechanism tend to sustain network imbalances within the HetNets, making it difficult to cater for the diverse traffic requirements of mobile users. In this study, instead of focusing solely on enhancing individual user downlink rates, we maximize the number of users whose downlink needs are satisfied by integrating a cell range extension (CRE) technique with an ant colony optimization algorithm. Our proposed method considers both the workload of base stations and the signal to interference-plus-noise ratio of user devices to formulate an objective function aimed at calculating specific CRE bias values for individual small base stations. A comparative analysis of the proposed approach with existing techniques demonstrates its effectiveness. Simulation results underscore the success of our proposed strategy in meeting users’ throughput needs while reducing network imbalances and call drop rates.

The goal of deploying LTE‐Advanced heterogeneous networks is to meet the growing need for Quality of Service (QoS), high data rates, and more coverage. Load balancing is one of the biggest problems, especially when User Equipment (UE) uses received signal strength to connect to different transmission power network tiers. Spectrum for small cells has not been used to its full potential. While all the cells are using the same frequency spectrum and the small cells overlap the Macro Cells, preventing interference is another big problem. The proposed Cell Range Extension (CRE) and Almost Blank Sub‐frame (ABS) provides a solution to overcome these challenges. The proposed ABS in this paper is novel because it is a partial muting one rather than the full muting ABS in recent research studies. In addition, the cell association method is by distance rather than conventional Reference Signal Received Power (RSRP). CRE‐ABS has been applied simultaneously to solve both load balancing and interference. Simulation results show that the proposed scheme achieves substantial throughput and Jain's Fairness Index (JFI).