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 exploit 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.
Our work consists on showing that the Spacetime curvature introduced by Einstein in the Universe is a result of the quantum Information Entropy of different quantum Time Paths of elementary particles and also of the virtual particles and antiparticles present in quantum vacuum that may appear in spacetime dimensions thanks to time-energy incertitude principle. In quantum physics, and particularly in quantum field theory (QFT), the paths in path integrals is in the spacetime dimensions, in this paper, the paths are over the Time dimensions or the quantum vacuum i.e. the paths between the two nearest spatial points Nx and N2. Using this modeling, we prove mathematically that the Information entropy, an entropy similar to the Shannon entropy, of these Time paths-Information could be equivalent to the Spacetime curvature in Universe.
The aim of this paper 1 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 α-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.
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 (SINR) or rate maps provided by a Radio Environment Map (REM). 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 [1]. 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. a
The aim of this paper a 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.
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