Comparison of Multi-Criteria Decision-Making Algorithms for Spectral and Energy Efficiency Trade-off in Massive MIMO Systems

The spectral and energy efficiency trade-off is a current issue in Massive MIMO (Multiple Input, Multiple Output) systems. It creates a multi-objective problem that can be solved using multi-objective optimization algorithms to find the Pareto Optimal Front. In the group of non-dominated alternatives, decision-makers can use MCDM (Multi-Criteria Decision-Making) algorithms to choose a single solution. MCDM algorithms are simple and efficient methods, but they still contain subjectivity in the assignment of criteria weights. This paper implemented and compared four different MCDM algorithms: SAW (Simple Additive Weighting), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), PROMITHEE (Preference Ranking Organization Method for Enrichment Evaluations) and VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje), which showed similar behavior. Among the analyzed algorithms, PROMITHEE had a stability issue, noticeable in the solutions chosen in the NSGA-2 (Non-dominated Sorting Genetic Algorithm-2) Pareto Optimal Front. Moreover, the algorithms did not perform well when different weights were assigned to the objectives, specifically when spectral efficiency which has higher values than energy efficiency, also had the highest weight. In this case, the algorithms always chose the alternative with the highest spectral efficiency possible. This shows that the algorithms are impacted by the order of values of the objectives despite the normalization methods that are included in them.