Mohammad Dehghani Soltani

Access point selection in Li-Fi cellular networks with arbitrary receiver orientation

The cellular Light-Fidelity (Li-Fi) network is considered as a promising approach for high speed indoor data access. The conventional metric, based on which an access point (AP) is selected for each user, is signal strength. This metric offers the best channel quality for each user but does not guarantee the achievable data rate, since the resource of an AP is limited. In this paper, we propose a new metric for AP selection to improve the load balancing among APs by considering both the received signal-to-interference-plus-noise-ratio (SINR) and the traffic of AP. The orientation of mobile stations (MS) is also taken into account and its effect on users performance is evaluated. In reality, receivers have random angles with the coordinate axes. We consider three standard angles similar to those used in mobile devices to model the device orientation. Based on this model, the effect of arbitrary orientation on users throughput and satisfaction is investigated. Simulation results show that when the orientation of users is considered, the proposed AP selection metric outperforms the conventional metric.

On Limited Feedback Resource Allocation for Visible Light Communication Networks

Resource allocation in visible light communication (VLC) networks is crucial to maximize throughput and achieve fairness among users. While resource allocation can be enhanced significantly using the feedback information of users, increasing feedback data can reduce the overall throughput of the system as overhead increases. In this paper, a limited feedback resource allocation scheme is proposed for VLC networks employing orthogonal frequency division multiple access (OFDMA). Compared with radio frequency (RF) systems, the frequency selectivity of the channels for different users are more correlated in a VLC system. The proposed method takes into account this characteristic of the channel and considers users requested data rate in order to satisfy their quality of service (QoS). In this study, subcarrier assignment is realized through two commonly used approaches in OFDMA: proportional fair (PF) and maximum channel quality indicator (CQI) schedulers. Simulation results show that the limited feedback scheme can achieve data rates and QoS very close to the full information feedback scheme.

Handover Modeling for Indoor Li-Fi Cellular Networks: The Effects of Receiver Mobility and Rotation

Light-fidelity (Li-Fi) is an emerging technology for wireless networking based on visible light communication (VLC). As a licence free, high speed, bidirectional and secure wireless access solution, Li-Fi is a complementary building block for fifth generation (5G) heterogeneous mobile networks. By modulating data on the light intensity emitted by light emitting diode (LED) luminaires which already exist in indoor lighting infrastructure, Li-Fi cellular networks are formed. Such networks are termed optical attocell networks, where the optical attcells are smaller in size than the radio frequency (RF) femtocells. This paper focuses on the problem of handover for downlink in an indoor optical attocell network. A fundamental approach is proposed for handover modeling by taking into account the effects of both mobility and rotation for a connected user equipment (UE). By using a random waypoint (RWP) model for the receiver movement and a geometric model for the receiver orientation, the probability of handover and the handover rate are calculated. Novel insights are provided into the handover performance in indoor optical attocell networks using Monte Carlo simulations.

Secure and robust watermarking using arnold transform and Neyman-Pearson decoder

In this paper, we propose an adaptive multiplicative method to watermark binary data by scaling low frequency wavelet coefficients in the first level of decomposition. We decode message using hypothesis testing with optimum threshold value according to Neyman-Pearson test. We define a detection factor, k0, which is equivalent to Lagrange Multiplier and use PSO optimization algorithm to obtain optimum threshold value. To increase security, we impose Arnold transform with optimum iteration number both on the host image and logo before embedding data. The robustness of the method is analyzed against well-known Stir-Mark attack set and compared with similar methods. Experimental results confirm the imperceptibility of the proposed method and more robustness against attacks.

An intelligent approach for classification of GPS satellites based on neural network, genetic algorithm and particle swarm optimization

Geometric dilution of precision (GDOP) factor, which is broadly utilized in satellite navigation, denotes the additional multiplicative impact of navigation satellite geometry on positional measurement precision. This factor is frequently employed to select suitable satellites subsets from at least 24 orbited existing satellites. The GDOP calculation has a time burden including complicated transformation and inversion of measurement matrices. To tackle this shortcoming, neural network- (NN-) based methods using the back propagation (BP) training algorithm have been broadly used. However, there are several parameters for the NN-based approaches that ought to be chosen by many trials. To alleviate this problem and enhance the BP training algorithm, we propose an intelligent approach based on the improved NN training methods and evolutionary algorithms (EAs), including namely, genetic algorithm (GA) and particle swarm optimization (PSO), to classify global positioning system (GPS) satellites using the GDOP factor. The simulation results for the real GPS GDOP data indicate that both the GA and PSO enhance the classification ratios, although the GA leads to higher ratios. The highest classification ratio is obtained by Levenberg-Marquardt training algorithm with GA.

Multiuser orthogonal signal division multiplexing for doubly-selective fading channel in autonomous vehicular communications

Communication networks with highly mobile users are emerging rapidly. Autonomous vehicular communication is an interesting example of such systems. High mobility speed causes drastic change in channel states, and consequently a doubly selective fading scenario is a proper model for such channels. In this paper, by considering this proper model, we introduce a multiuser system based on orthogonal signal division multiplexing in a cognitive radio scenario. Carrier interferometry codes are also utilized in this system. By designing the transmitter and receiver, the performance of such system is investigated. We show that this system works properly when users are moving rapidly, and moreover the random delay of different users can be dealt with effectively.