Impact of Beamforming in terms of Capacity in Wi-Fi Networks

Subject Areas : Telecommunication

Farhad Bahadori-jahromi ^{1 *}

1 - گروه مهندسی برق،واحد فسا،دانشگاه آزاد اسلامی،فسا،ایران

Received: 2025-06-12 Accepted : 2025-08-14 Published : 2025-08-24

Keywords: Modulation and Coding Model (MCM), Signal to Interference and Noise Ratio(SINR), Access Points(AP), SNR-aware Intra-frame Rate Adaptation(SIRA), Missing Area(MA), NS3 software,

Abstract :

Our study focuses on the impact of beamforming in terms of capacity. Deploying Wi-Fi networks involves a range of techniques and considerations, including equipment selection and access point placement. In this paper, we discuss the different techniques for Wi-Fi deployment, our Wi-Fi deployment scenarios, and the factors involved in calculating the number of access points, taking into account capacity based on the application requirements. In this paper, we evaluate three different deployment models: data rate independent, data rate dependent, and edge deployment. We conduct our tests through simulation and derive an empirical model by offering a generalization of our approach for any field size and comparing it to simulation results.

In the context of autonomous robots for smart environment, we explored deployment strategies that utilize beamforming to enhance communication range and quality. Our strategy involved determining the required number of access points for different MIMO systems across two deployment types (grid and edge deployments). The deployment types took into account the challenges associated with deployment in specific fields. Additionally, we evaluated, through simulation, our deployments for different application requirements to emulate a control station taking control of a robot in the field. After gathering simulation results, we developed an empirical model to obtain results for any field size, and the simulation result demonstrated the accuracy of the model. Our study highlighted the trade-offs between deployment cost and complexity versus network performance by using NS3 software.

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