Power-allocation-for-multi-user-OFDM-DCSK-system-in-frequency-selective-fading-channel

This project is related to the paper: "Power allocation for multi-user OFDM-DCSK system in frequency selective fading channel", Majid Mobini, M.Reza Zahabi, Physical Communication, 24, (2017), pp. 146–153. In this paper, we introduce a grouping approach for power allocation in the multi-user OFDM-DCSK (MU-OFDM-DCSK) system under the frequency selective fading channels. The suggested procedure is convenient also for the other comb-type non-coherent schemes with similar structure. Furthermore, we derive analytical bit error rate (BER) expression for the grouped scheme and offer an optimal power distribution policy for both the single- and multi-user scenarios. This power assignment strategy is formulated by a min–max problem with the target of the worst group BER minimization incorporating total power and interference constraints. Simulation results confirm the advantages of the proposed power allocation scheme.

A-Genetic-Algorithm-based-Rate-Splitting-Approach-for-Multi-user-MISO-systems-

In a Rate Splitting (RS) approach, each message is divided into a common message and private messages. This project is introduced based on the genetic algorithm (GA) to finding an optimal power ratio, suggesting a simple systematic method for power dividing. this solution may be more exact but since it is an iterative approach, increases the processing time of the transmission.

Life-Time-Optimization-in-a-Mobile-Wireless-Sensor-Network-with-Solar-Energy-Harvesting

In this project, mobile wireless sensors send the received solar recharge value and residual energy information to a Base Station (BS), and the BS dynamically optimizes the life time and guarantees a level of the throughput by assigning optimal transmission opportunity of the sensors.

Deep_chaos_synchronization

This code is an implementation for a deep learning based synchronization system , presented in the following paper: Deep Chaos Synchronization MAJID MOBINI AND GEORGES KADDOUM