Energy and spectral efficiency are the main challenges in 5th generation of mobile cellular networks. In this paper, we propose an optimization algorithm to optimize the energy efficiency by maximizing the spectral efficiency. Our simulation results show a significant increase in terms of spectral efficiency as well as energy efficiency whenever the mobile user is connected to a low power indoor base station. By applying the proposed algorithm, we show the network performance improvements up to 9 bit/s/Hz in spectral efficiency and 20 Gbit/Joule increase in energy efficiency for the mobile user served by the indoor base station rather than by the outdoor base station.
Non-Orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC) is one of the promising techniques proposed for 5G systems. It allows multiple users with different channel coefficients to share the same (time/frequency) resources by allocating several levels of (power/code) to them. In this article, a design of a cooperative scheme for the uplink NOMA Wi-Fi transmission (according to IEEE 802.11 standards) is investigated. Various channel models are exploited to examine the system throughput. Convolutional coding in conformance to IEEE 802.11a/g is applied to evaluate the system performance. The simulation results have been addressed to give a clear picture of the performance of the investigated system.
One of the crucial advancements in next-generation 5G wireless networks is the use of high-frequency signals specifically those are in the millimeter wave (mm-wave) bands. Using mmwave frequency will allow more bandwidth resulting higher user data rates in comparison to the currently available network. However, several challenges are emerging (such as fading, scattering, propagation loss etc.), whenever we utilize mm-wave frequency wave bands for signal propagation. Optimizing propagation parameters of the mm-wave channels system are much essential for implementing in the real-world scenario. To keep this in mind, this paper presents the potential abilities of high frequencies signals by characterizing the indoor small cell propagation channel for 28, 38, 60 and 73 GHz frequency band, which is considered as the ultimate frequency choice for many of the researchers. The most potential Close-In (CI) propagation model for mm-wave frequencies is used as a Large-scale path loss model. Results and outcomes directly affecting the user experience based on fairness index, average cell throughput, spectral efficiency, cell-edge user’s throughput and average user throughput. The statistical results proved that these mm-wave spectrum gives a sufficiently greater overall performance and are available for use in the next generation 5G mobile communication network.
Utilization of drones is going to become predominated in cellular networks as aerial base stations in order to temporary cover areas where stationary base stations cannot serve the users. Detecting optimal location and efficient number of drone-Base Stations (DBSs) are the targets we tackle in this paper. Toward this goal, we first model the problem using mixed integer non-linear programming. The output of the proposed method is the number and the optimal location of DBSs in a two-dimension area, and the object is to maximize the number of covered users. In the second step, since the proposed method is not solvable using conventional methods, we use a proposed method to solve the optimization problem. Simulation results illustrate that the proposed method has achieved its goals.