A Comparison Study of PAPR Reduction in OFDM Systems Based on Swarm Intelligence Algorithms

Optimization algorithms have been one of the most important research topics in Computational Intelligence Community. They are widely utilized mathematical functions that solve optimization problems in a variety of purposes via the maximization or minimization of a function. The swarm intelligence (SI) optimization algorithms are an active branch of Evolutionary Computation, they are increasingly becoming one of the hottest and most important paradigms, several algorithms were proposed for tackling optimization problems. The most respected and popular SI algorithms are Ant colony optimization (ACO) and particle swarm optimization (PSO). Fireworks Algorithm (FWA) is a novel swarm intelligence algorithm, which seems effective at finding a good enough solution of a complex optimization problem. In this chapter we proposed a comparison study to reduce the high PAPR (Peak-to-Average Power Ratio) in OFDM systems based on the swarm intelligence algorithms like simulated annealing (SA), particle swarm optimization (PSO), fireworks algorithm (FWA), and genetic algorithm (GA). It turns out from the results that some algorithms find a good enough solutions and clearly outperform the others candidates in both convergence speed and global solution accuracy

Performance analysis and investigation of a grid-connected photovoltaic installation in Morocco

The paper present an evaluation of a grid-connected photovoltaic (PV) system installed on the roof of a government building located in Tangier, Morocco. The experimental data was recorded from 1st January 2015 to December 2015 based on real time observation. The aim is to encourage the use of solar PV system for government, commercial and residence building in Morocco based on the obtained results. The system is made up of 20 modules of 250 Wp and one inverter of 5 kW. The assessed parameters of the PV installation includes energy output, final yield, modules temperature, efficiency module, performance ratio (PR) and others. The PV park supplied the grid with 6411.3 kWh during the year 2015. The final yield (Yf) ranged from 1.96 to 6.42 kWh/kWp, the performance ratio (PR) ranged from 58% to 98% and the annual capacity factor was found to be 14.84%. The final yield of PV installation is compared with other final yields of solar PV systems located at other places. Finally various power losses are given through a diagram loss

PAPR Reduction Using Fireworks Search Optimization Algorithm in MIMO-OFDM Systems

The transceiver combination technology, of orthogonal frequency division multiplexing (OFDM) with multiple-input multiple-output (MIMO), provides a viable alternative to enhance the quality of service and simultaneously to achieve high spectral efficiency and data rate for wireless mobile communication systems. However, the high peak-to-average power ratio (PAPR) is the main concern that should be taken into consideration in the MIMO-OFDM system. Partial transmit sequences (PTSs) is a promising scheme and straightforward method, able to achieve an effective PAPR reduction performance, but it requires an exhaustive search to find the optimum phase factors, which causes high computational complexity increased with the number of subblocks. In this paper, a reduced computational complexity PTS scheme is proposed, based on a novel swarm intelligence algorithm, called fireworks algorithm (FWA). Simulation results confirmed the adequacy and the effectiveness of the proposed method which can effectively reduce the computation complexity while keeping good PAPR reduction. Moreover, it turns out from the results that the proposed PTS scheme-based FWA clearly outperforms the hottest and most important evolutionary algorithm in the literature like simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA)