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.
A large amount of electric vehicles (EVs) charging load will bring significant impact to the power system. An appropriate resource allocation strategy is required for securing the power system safety and satisfying EVs charging demand. This paper proposed a power coordination allocation strategy of EVs’ in distribution systems. The strategy divides the allocation into two stages. The first stage is based on scores assigned to EVs through an entropy method, whereas the second stage allocates energy according to EV’s state of charge. The charging power is delivered in order to maximize EV users’ satisfaction and fairness without violation of grid constraints. Simulation on a typical power-limited residential distribution network proves the effectiveness of the strategy. The analysis re- sults indicate that compared with traditional methods, EVs, which have higher charging requirement and shorter available time will get more energy delivered than others. The root- mean-square-error (RMSE) and standard-deviation (SD) results prove the effectiveness of the methodology for improving the balance of power delivery.
A novel method to improve the performance of the frequency band is cognitive radio that was introduced in 1999. Due to a lot of advantages of the OFDM, adaptive OFDM method, this technique is used in cognitive radio (CR) systems, widely. In adaptive OFDM, transmission rate and power of subcarriers are allocated based on the channel variations to improve the system performance. This paper investigates adaptive resource allocation in the CR systems that are used OFDM technique to transmit data. The aim of this paper is to maximize the achievable transmission rate for the CR system by considering the interference constraint. Although secondary users can be aware form channel information between each other, but in some wireless standards, it is impossible for secondary user to be aware from channel information between itself and a primary user. Therefore, due to practical limitation, statistical interference channel is considered in this paper. This paper introduces a novel suboptimal power allocation algorithm. Also, this paper introduces a novel bit loading algorithm. In the numerical results sections, the performance of our algorithm is compared by optimal and conventional algorithms. Numerical results indicate our algorithm has better performance than conventional algorithms while its complexity is less than optimal algorithm.