2022 - The main objective of this paper is to understand the entropy of the mass/energy objects (Signals Information SI) wave functions. As the wave functions are complex, we computed a complex entropy that is equivalent to the Shannon one to calculate the deformation due to the space and time summation or the interferences or what we have demonstrated to be the Gravity effect. The imaginary part of this complex entropy has been shown to describe the spacetime curvature. In this paper we will prove that the real part of this entropy is the thermodynamical entropy effect one defined by the Hawking Radiation.

2022 - This paper gives a possible theoretical explanation for the gravity field creation from energy/matter object, and may also provides an explanation of how a wave function collapses. In our last paper "Spacetime curvature, a potential result of the quantum mass/energy Information Entropy" submitted to Foundation of Physics, We have defined that everything may be described by a time-dimensional signal-Information that travels certainly in time dimensions or in the Time paths but not necessarly in space. In each quantum field, thanks to the Heisenberg time-energy principle, virtual particles and antiparticles may exist in space during Delta t. However, in presence of a massive object, $\Delta t$ is transformed to a shorter Delta t' but only for the virtual particles and not for the virtual antiparticles that their creation duration remains Delta t. This duration time assymetry transformation is what we call the gravity effect. The Delta t is a time duration where all the signal-Information coming from the neighboring locations may be added. It is the duration threshold of signals summation or the interference threshold duration capacity. If Delta t is transformed to a quite shorter duration Delta t' in the presence of a high energetic/massive object, then the summation or the interference of the signals will probably reduced or even vanish: a real particle is created from a virtual one with no interference effect and hence makes waves function collapse.

2021 - This work proposes a possible proof on how the spacetime curvature is created by any object (mass/energy) and suggests a mathematical model that may conciliate quantum mechanics and general relativity. As each elementary particle is a fluctuation in its particular field in Quantum Fiel Theory and follows quantum mechanics properties, the wave function of each elementary particle of an object is deformed at each spacetime point in the presence of another massive object (set of particles). This comes from the fact that the wave functions of the particles of the two massive objects in their respective quantum fields may be aggregated and hence modifies in time and space the wave functions values. This could subsequently change the location of the object less massive as the probabilities of the presence of the elementary particles are getting higher next to the highly massive objects: the less massive objects are correlated to the highly massive one. In this study we suppose that between two nearest spatial points Nx and N2 there is an infinity of quantum-mechanically possible Time paths in quantum vacuum (or what we will call Time paths) as assumed in path integrals theory...

2021 - This work proposes a mathematical model about how a reaction is created in the human brain in response to a particular incoming Information/Event using quantum mechanics and more precisely path integrals theory. The set of action potentials created in a particular neuron N2 is a result of temporal and spatial summation of the signals coming from different neighboring neurons Nx with different dendrite-paths. Each dendrite-path of N2 is assumed to be determined by its respective synapse with its neurotransmitters and assumed to have an action S due to the neurotransmitter types (for example: excitatory or inhibitory). An external incoming signal information being initially modulated by receptor neurons (in eyes, ears...) travels through the neighboring neurons that are linked to the excited receptor neurons. A potential reaction responses are subsequently created thanks to a final deformed signal in the motor neurons by all the correlated neural paths. The total deformation at each neuron is created by different incoming dendrite-paths and their structures ...

2021 - Our work consists on showing that the Spacetime curvature introduced by Einstein in the Universe and also in the Brain is a result of the Information Entropy of different quantum Paths of elementary particles (leptons, bosons…) of path integrals model. We started by seeing the structure of how the incoming information is processed and then propagated in the brain and how the latter is deformed in each neuron to thus create a potential reaction response distorted or not. In quantum physics, and particularly in quantum field theory (QFT), the paths in path integrals have an equivalent role to paths between two neighboring linked neurons (synapses + neurotransmitters + dendrites). Using this modeling, we prove mathematically that the entropy of the Information coming from the paths could be equivalent to the Spacetime curvature in Universe as in Brain

2020 - This study develops a new way to model the emotional impact on a particular individual (person, group,...) that may have feelings, to any event or any information. The significance of an event or an information depends on the person undergoing it. Each person reacts emotionally differently to a same situation in terms of intensity and/or type of emotion. A particular same event is therefore perceived subjectively different by each individual. The reason is that each person has his own personality, his own experience, his own history, his own education and tradition ... In this study, we assume that all the Events / Information have common interpretable points relative to each individual: Who is in the event ?, What is done? When it is done? Where it is done? How often/much it is done? Why it is done? and How it is done?

2018 - Technology evolutions make possible the use of Geo-Localized Measurements (GLM) for performance and quality of service optimization thanks to the Minimization of Drive Testing (MDT) feature. Exploiting GLM in radio resource management is a key challenge in future networks. The Forecast Scheduling (FS) concept that uses GLM in the scheduling process has been recently introduced. It exploits long term time and spatial diversity of vehicular users in order to improve user throughputs and quality of service. In a previous paper we have formulated the FS as a convex optimization problem namely the maximization of an α-fair utility function of the cumulated downlink data rates of the users along their trajectories. This paper proposes an extension for the FS model to take into account different types of random events such as arrival and departure of users and uncertainties in the mobile trajectories. Simulation results illustrate the significant performance gain achieved by the FS algorithms in the presence of random events.

2018 - Forecast Scheduling (FS) is a scheduling concept that utilizes rate prediction along the users' trajectories in order to optimize the scheduler allocation. The rate prediction is based on Signal to Interference plus Noise Ratio or rate maps provided by a Radio Environment Map. The FS has been formulated as a convex optimization problem namely the maximization of an α-fair utility function of the cumulated rates of the users along their trajectories. This paper proposes a fast heuristic for the FS problem based on two FS users' scheduling. Furthermore, it is shown that in the case of two users, the FS problem can be solved analytically, making the heuristic computationally very efficient. Numerical results illustrate the throughput gain brought about by the scheduling solution.

2017 - The concept of Forecast Scheduling (FS) has been introduced, where it is shown that the knowledge of the present and future rates along the users’ trajectories can be exploited by the scheduler in order to significantly improve the average user throughput. The throughput gain is achieved by exploiting long term time and spatial diversity along the users’ trajectory. The FS is posed as a convex optimization problem that can be solved using fast convex optimziation solvers. The randomness of the traffic, i.e. arrival and departure of communications on the one hand and randomenss in the user trajectories can be incorporated into the FS solution. This repport investigates the FS for the case of n = 2 users and derives closed form expressions for the FS allocation rules

2016 - In future networks, Radio Resource Management (RRM) could benefit from Geo-Localized Measurements (GLM) thanks to the Minimization of Drive Testing (MDT) feature introduced in Long Term Evolution (LTE). Such measurements can be processed by the network and be used to optimize its performance. The purpose of this paper ^a is to use GLM to significantly improve scheduling. We introduce the concept of forecast scheduler for users in high mobility that exploits GLM. It is assumed that a Radio Environment Map (REM) can provide interpolated Signal to Interference plus Noise Ratio (SINR) values along the user trajectories. The diversity in the mean SINR values of the users during a time interval of several seconds allows to achieve a significant performance gain. The forecast scheduling is formulated as a convex optimization problem namely the maximization of an α-fair utility function of the cumulated rates of the users along their trajectories. Numerical results for thee different mobility scenarios illustrate the important performance gain achievable by the forecast scheduler.

2016 - The aim of this paper is to study new antenna array technologies in order to manage efficiently heterogeneous, fixed and mobile traffic. Traffic light close to the cell edge is introduced to generate non stationary mobility pattern in the cell. A car following model is used to model the mobility behavior of the vehicles. A heterogeneous antenna system with different large antenna array technologies is considered: Virtual Small Cell (VSC), virtual small cell with Self-Organizing Network (VSC-SON) and beamforming with multilevel global codebook that manages the heterogeneous antenna system at the Base Station (BS). The first two technologies improve the cell performance due to the capability to focus the signal at the traffic concentration near the traffic light. The novel beamforming solution with global codebook can further and significantly improve performance due to the capability to focus the signal along the road and to implicitly balance the traffic between the different antennas. Numerical simulations illustrate the benefits brought about by the different antenna technologies.

2015 - The aim of this paper is to study resource allocation and control in a LTE-Advanced heterogeneous network with vehicular traffic in the presence of traffic light. A car following model is used to model the cars' speed and their interactions. A small cell is deployed near the traffic light to relieve periodic congestion and QoS degradation. Three resource allocation and control schemes are investigated: a full frequency reuse, a static and a dynamic frequency splitting algorithm that are optimized with respect to a throughput based alpha-fair utility. Through numerical simulations, it is shown that the frequency splitting algorithms outperform the full frequency reuse scheme in term of user throughput and file transfer time. Furthermore, it is shown that dynamic control scheme is of particular interest for non-stationary traffic as the one introduced by a periodic traffic light.