Mitigation of Environmental Temperature Variation Effects in OCDMA Networks Using PSO Power Control

Abstract

In this paper, a mitigation of environmental temperature variation effects in optical code division multiple access (OCDMA) networks based on power control is described. The temperature changes would adversely affect 2D wavelength-hopping time-spreading optical code by causing a reduction in the expected height of the autocorrelation peak. Environmental temperature variation is usually difficult to accurately determine and compensate for due to its dynamic nature and fluctuations. Furthermore, the power control strategy allows the regulation of the transmitted power in order to dynamically mitigate the effects of temperature variation. The particle swarm optimization (PSO) algorithm is evocated to solve the problem of power control based on the signal-to-noise plus interference ratio optimization to mitigate the environmental effects. Afterward, numerical results are discussed taking into account the code parameters, such as the code weight and spectral spacing.

Power Allocation in PON-OCDMA with Improved Chaos Particle Swarm Optimization

“…Let bp and vp denote a particle coordinates (position) and its corresponding flight speed (velocity) in a search space, respectively. In the PSO strategy, each power-vector candidate , with dimension , is used for the velocity-vector calculation in the next iteration [9]; in vector form, the K dimensional velocity-vector…”

“…The power allocation problem are related to not convex cost and constraint functions, therefore this problem in not straight to be solved [6] [7]. In this context, there are several approaches to solve the power allocation problem, such as analytical-iterative algorithms, matrix inversion, numerical procedures and meta-heuristic schemes [4] [7][8] [9]. The metaheuristics methods are very promissory approaches to perform the power allocation considering its performance-complexity tradeoff and fairness features regarding the previous cited approaches [9] [10].…”

“…In this context, there are several approaches to solve the power allocation problem, such as analytical-iterative algorithms, matrix inversion, numerical procedures and meta-heuristic schemes [4] [7][8] [9]. The metaheuristics methods are very promissory approaches to perform the power allocation considering its performance-complexity tradeoff and fairness features regarding the previous cited approaches [9] [10]. In addition, the bio-inspired meta-heuristics have been presented relevant results to solve the power allocation problem [6][9] [10].…”

Noncoherent Spectral Optical CDMA System Using 1D Active Weight Two-Code Keying Codes

“…Therefore, the PIIN, shot noise, and thermal noise all cause independent variance in the photocurrent and thus have independent influences on system performance. The photocurrent PIIN variance is shown in (13) and is defined as follows:…”

“…Encoding/decoding approaches are used to construct OCDMA systems and suppress the multiuser interference (MUI) [9][10][11] that arises when using shared channels with the same frequency spectrum. In addition, the OCDMA systems use photodiodes to shield them from the effects of phaseinduced intensity noise (PIIN) [12][13][14][15][16], a design feature of such systems.…”