An Analytical Model for the Aggregate Throughput of IEEE 802.11ah Networks under the Restricted Access Window...

Area of Science:

• Computer Science
• Electrical Engineering
• Wireless Communication

Background:

• The Internet of Things (IoT) requires efficient wireless communication standards.
• IEEE 802.11ah offers enhanced support for IoT with its novel Restricted Access Window (RAW) mechanism.
• RAW aims to mitigate channel contention by assigning stations to specific time slots.

Purpose of the Study:

• To develop and validate an analytical model for evaluating IEEE 802.11ah network throughput.
• To assess the performance of the RAW mechanism under saturated traffic and ideal channel conditions.
• To compare the proposed model's accuracy against simulations and existing analytical models.

Main Methods:

• Development of a discrete-time Markov chain model.
• Modeling the behavior of an active station within its assigned RAW slot.
• Incorporation of RAW slot time completion during backoff operations.

Main Results:

• The proposed analytical model accurately evaluates average aggregate throughput for IEEE 802.11ah networks with RAW.
• Performance was studied across various numbers of RAW slots and stations.
• Numerical results showed close agreement with ns-3 based computer simulations.

Conclusions:

• The discrete-time Markov chain model provides a reliable method for analyzing IEEE 802.11ah network throughput.
• The model's accuracy is validated by its strong correlation with simulation data.
• This work contributes to understanding and optimizing wireless communication for IoT.