khachoang1412 / AoI_slottedALOHA_energyHarvesting

Matlab codes for the paper [1] K.-H. Ngo, G. Durisi, A. Munari, and F. Lazaro, and A. Graell i Amat, "Timely status updates in slotted ALOHA networks with energy harvesting," submitted to IEEE Transactions on Communications, Apr. 2024, and its Globecom-2023 short version.

Timely status updates in slotted ALOHA networks with energy harvesting

This repository contains the Matlab numerical routines of the paper:

[1] K.-H. Ngo, G. Durisi, A. Munari, and F. Lazaro, and A. Graell i Amat, "Timely status updates in slotted ALOHA networks with energy harvesting," submitted to IEEE Transactions on Communications, Apr. 2024. URL: https://arxiv.org/pdf/2404.18990

and of a simplified setting reported in its short version presented at Globecom 2023:

[2] K.-H. Ngo, G. Durisi, A. Graell i Amat, A. Munari, and F. Lazaro, “Age of information in slotted ALOHA with energy harvesting,” in IEEE Global Communications Conference (Globecom), Kuala Lumpur, Malaysia, Dec. 2023. URL: https://arxiv.org/pdf/2310.00348.

Please cite the aforementioned papers if you use this code.

Content of the repository

This repository contains the following main files used for [1]:

1. exact.m: evaluate the exact average age of information (AoI) via a first-order Markov analysis.
2. simulation.m: evaluate the average AoI, AVP, and throughput via a simulation of the protocol.
3. approximation.m: evaluate approximations of the average AoI, AVP, and throughput obtained via the phase-type distribution.
4. optimize_ptx.m: optimize the transmission probabilities to minimize the average AoI, minimize the AVP, or maximize the throughput.

The folder simplified_setting contains the corresponding files used for the setting in [2].

The folder helpers contains the following supplementary functions:

1. compute_w_capture.m: evaluate the successful decoding probability for each device when the decoding is with capture.
2. interger_partitions.m: partition a given interger into multiple integers.
3. uniqueperms.m: generate all unique permutations of elements in a vector.
4. randi_distr.m: generate a matrix with random entries distributed according to a specified discrete distribution.
5. randfixedsum.m: generate random values lying in the interval and summing to a given value.
6. fminsearchcon.m: optimization using the Nelder-Mead method; extension of FMINSEARCHBND in Matlab with general inequality constraints.

The functions interger_partitions, uniqueperms, and fminsearchcon were written by other people. The references are provided in the files.