The design of the modern computing paradigm of heuristics is an innovative development for parameter estimation of direction of arrival (DOA) using sparse antenna arrays. In this study, the optimization strength of the flower pollination algorithm (FPA) is exploited for the DOA estimation in a low signal to noise ratio (SNR) regime by applying coprime sensor arrays (CSA). The enhanced degree of freedom (DOF) is achieved with FPA by investigating the global minima of highly nonlinear cost function with multiple local minimas. The sparse structure of CSA demonstrates that the DOF up to $O\left(MN\right)$ is achieved by employing $M+N$ CSA elements, where M and N are the numbers of antenna elements used to construct the CSA. Performance analysis is conducted for estimation accuracy, robustness against noise, robustness against snapshots, frequency distribution of root mean square error (RMSE), variability analysis of RMSE, cumulative distribution function (CDF) of RMSE over Monte Carlo runs and the comparative studies of particle swarm optimization (PSO). These reveal the worth of the proposed methodology for estimating DOA.

For the purpose of attaining a high degree of freedom (DOF) for the direction of arrival (DOA) estimations in radar technology, coprime sensor arrays (CSAs) are evaluated in this paper. In addition, the global and local minima of extremely non-linear functions are investigated, aiming to improve DOF. The optimization features of the cuckoo search (CS) algorithm are utilized for DOA estimation of far-field sources in a low signal-to-noise ratio (SNR) environment. The analytical approach of the proposed CSAs, CS and global and local minima in terms of cumulative distribution function (CDF), fitness function and SNR for DOA accuracy are presented. The parameters like root mean square error (RMSE) for frequency distribution, RMSE variability analysis, estimation accuracy, RMSE for CDF, robustness against snapshots and noise and RMSE for Monte Carlo simulation runs are explored for proposed model performance estimation. In conclusion, the proposed DOA estimation in radar technology through CS and CSA achievements are contrasted with existing tools such as particle swarm optimization (PSO).

Managing the users multimedia and long-range based demands, the radio over fiber (RoF) mechanism has been introduced recently. RoF mingles the optical and radio communication frameworks to increase mobility and offer high capacity communication networks (CNs). In this paper, a full-duplex RoF-based CN is investigated for the next-generation passive optical network (PON), utilizing wavelength division multiplexing (WDM) technology. The desolations on account of optical and electronic domains (OEDs) are addressed, using dispersion compensation fiber (DCF) and optical and electrical filters, including modulation scheme. The analytical and simulation models are analyzed in terms of phase error (PE), radio frequency (RF), fiber length and input and received powers. The performance of the proposed model is successfully evaluated for 50 km range, −40 to −18 dBm received power, −20 to 0 dBm input power, where below ${10}^{-6}$ bit error rate (BER) is recorded. Thus, this signifies that the presented model exhibits smooth execution against OEDs impairments.