Search Results for author:
Found 8 papers, 4 papers with code
Tensor Learning-based Precoder Codebooks for FD-MIMO Systems
We find the best representation of the optimal precoder as a function of Kronecker Product (KP) of two low-dimensional precoders, respectively corresponding to the horizontal and vertical dimensions of the UPA, obtained from the tensor decomposition of the channel.
Learning on a Grassmann Manifold: CSI Quantization for Massive MIMO Systems
This paper focuses on the design of beamforming codebooks that maximize the average normalized beamforming gain for any underlying channel distribution.
Load on the Typical Poisson Voronoi Cell with Clustered User Distribution
In this letter, we characterize the distribution of the number of users associated with the typical base station (BS), termed the typical cell load, in a cellular network where the BSs are distributed as a homogeneous Poisson point process (PPP) and the users are distributed as an independent Poisson cluster process (PCP).
Information Theory Information Theory
Machine Learning meets Stochastic Geometry: Determinantal Subset Selection for Wireless Networks
In wireless networks, many problems can be formulated as subset selection problems where the goal is to select a subset from the ground set with the objective of maximizing some objective function.
Load Balancing in 5G HetNets with Millimeter Wave Integrated Access and Backhaul
With the goal of elucidating key design trends for this new paradigm, we develop an analytical framework for a two-tier HetNet with IAB where the macro base stations (MBSs) provide mm-wave backhaul to the small cell base stations (SBSs).
Information Theory Information Theory
Unified Analysis of HetNets using Poisson Cluster Process under Max-Power Association
Owing to its flexibility in modeling real-world spatial configurations of users and base stations (BSs), the Poisson cluster process (PCP) has recently emerged as an appealing way to model and analyze heterogeneous cellular networks (HetNets).
Information Theory Networking and Internet Architecture Information Theory
Enhanced Multiobjective Evolutionary Algorithm based on Decomposition for Solving the Unit Commitment Problem
The unit commitment (UC) problem is a nonlinear, high-dimensional, highly constrained, mixed-integer power system optimization problem and is generally solved in the literature considering minimizing the system operation cost as the only objective.
Multi-Agent Shape Formation and Tracking Inspired from a Social Foraging Dynamics
Principle of Swarm Intelligence has recently found widespread application in formation control and automated tracking by the automated multi-agent system.
