Communications
This file contains the MAB algorithms for millimeter wave (mmWave) beamforming training (BT) in Indoor environment for both single beam and concurrent beams scenarios. The algorithms were developed using MATLAB software and they are making use of the following data set
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This dataset of 7200 channels is generated at different locations in the room area of 30x15x4 m3, where the locations are separated by 0.25m in both horizontal and vertical directions. Each AP uses 10 dBm TX power and 2D BF. In the concurrent mmWave BT scenario, all APs are operating, while in the single mmWave BT scenario, we consider a single AP fixed on the center of the room’s ceiling
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This dataset of 7200 channels is generated at different locations in the room area of 30x15x4 m3, where the locations are separated by 0.25m in both horizontal and vertical directions. Each AP uses 10 dBm TX power and 2D BF. In the concurrent mmWave BT scenario, all APs are operating, while in the single mmWave BT scenario, we consider a single AP fixed on the center of the room’s ceiling
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The files here support the research work presented in the paper submitted for IEEE Transactions on Antennas and Propagation, "Site-specific Radio Propagation Model for 5G Macrocell Coverage at Sub-6 GHz Frequencies", which is currently under revision.This paper proposes a hybrid radio wave propagation model for 5G macrocell coverage predictions in built-up areas for sub-6 GHz frequency band.
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 26 11:19:38 2020
@author: ali nouruzi
"""
import numpy as np
import random
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As for the experiment results in the manuscript, we would like to provide the corresponding Transmitted, Measured and Processed data zipped in the folder “Transmitted_Measured_Processed_DATA”, for readers who are interest in the harmonic-based MIMO transceiver and want to reproduce the experiment results shown in the manuscript. All the parameters including sampling rate, modulation frequency, etc., are the same as those in Experiment part.
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Disclaimer
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The provided dataset computes the exact analytical bit error rate (BER) of the NOMA system in the SISO broadcast channels with the assumption of i.i.d Rayleigh fading channels. The reader has to decide on the following input: 1) Number of users. 2) Modulation orders. 3) Power assignment. 4) Pathloss. 5) Transmit signal-to-noise ratio (SNR). The output is stored in a matrix where different rows are for different users while different columns are for different transmit SNRs.
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This dataset is being used to evaluate PerfSim accuracy and speed against a real deployment in a Kubernetes cluster based on sfc-stress workloads.
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