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This is a code package is related to the follow scientific article: Andrea Pizzo, Daniel Verenzuela, Luca Sanguinetti and Emil Björnson, "Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss," IEEE Transactions on Green Communications and Networking, Submitted to. The package contains a simulation environment, bas…
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README.md

README.md

Network-Deployment-for-Maximal-Energy-Efficiency-in-Uplink-with-Multislope-Path-Loss

This is a code package is related to the follow scientific article:

Andrea Pizzo, Daniel Verenzuela, Luca Sanguinetti and Emil Björnson, "Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss," IEEE Transactions on Green Communications and Networking, Submitted to. The package contains a simulation environment, based on Matlab, that reproduces all the numerical results and figures in the article. We encourage you to also perform reproducible research!

Abstract of Article

This work aims to design the uplink (UL) of a cellular network for maximal energy efficiency (EE). Each base station (BS) is randomly deployed within a given area and is equipped with M antennas to serve K user equipments (UEs). A multislope (distance-dependent) path loss model is considered and linear processing is used, under the assumption that channel state information is acquired by using pilot sequences (reused across the network). Within this setting, a lower bound on the UL spectral efficiency and a realistic circuit power consumption model are used to evaluate the network EE. Numerical results are first used to compute the optimal BS density and pilot reuse factor for a Massive MIMO network with three different detection schemes, namely, maximum ratio combining, zero-forcing (ZF) and multicell minimum meansquared error. The numerical analysis shows that the EE is a unimodal function of BS density and achieves its maximum for a relatively small BS densification, irrespective of the employed detection scheme. This is in contrast to the single-slope (distance-independent) path loss model, for which the EE is a monotonic non-decreasing function of BS densification. Then, we concentrate on ZF and use stochastic geometry to compute a new lower bound on the spectral efficiency, which is then used to optimize, for a given BS density, the pilot reuse factor, number of BS antennas and UEs. Closed-form expressions are computed from which valuable insights into the interplay between the optimization variables, hardware characteristics, and propagation environment can be obtained.

Content of Code Package

The package contains 3 folders which can be used to generate the 5 simulation figures as they appear in the article. The folder "ComputeULAvgErgodicSE" compute the uplink average ergodic spectral efficiency as seen in Theorem 2 in the article. The results obtained by running the main script in this folder are then saved in another folder called "SimulationResults". Finally, the scripts included in the folder "GenerateSimulationFigures" generate the figures in the article by using the simulation results computed beforehand.

See each script and function for further documentation.

License and Referencing

This code package is licensed under the GPLv2 license. If you in any way use this code for research that results in publications, please cite our original article listed above.

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