Fine-tuning of Cost-231 Hata Path Loss Model for LTE Network: The Case of 4 Kilo Area

In the paper, evolutionary optimization strategy, represented by the genetic algorithm (GA) is considered as a multiuser detection (MUD) method for a multiple-input multiple-output (MIMO) wireless system. With the aim to boost lacking GA convergence, Zero-Forcing (ZF) detection is proposed as an initial processing phase. Additionally, a multi-stage GA routine is considered as a method to make the search for data estimates more effective.

Genetic-Algorithm-Driven MIMO Multi-user Detector for Wireless Communications

Genetic Algorithm-Based Joint Channel Estimation and Data Detection For Multi-User Mimo

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Genetic Algorithm-Based Joint Channel Estimation and Data Detection For Multi-User Mimo