Pseudorandom sequence contention algorithm for IEEE 802.11ah based internet of things network

Area of Science:

• Computer Science
• Electrical Engineering
• Wireless Communication

Background:

• IEEE 802.11ah networks utilize Distributed Coordination Function (DCF) with Binary Exponential Backoff (BEB) for medium access.
• The legacy BEB algorithm in DCF leads to high collision probabilities in Restricted Access Windows (RAW) with many stations.
• This limits the efficiency of wireless communication systems.

Purpose of the Study:

• To propose a novel backoff algorithm, the Pseudorandom Sequence Contention Algorithm (PRSCA), for IEEE 802.11ah.
• To mitigate the high collision probability issue inherent in the conventional BEB algorithm.
• To enhance overall network performance metrics.

Main Methods:

• Developed PRSCA, which replaces the exponential backoff sequence with a pseudorandom sequence for Contention Window (CW) size updates.
• Introduced a new CW freezing mechanism and backoff stage reset process within PRSCA.
• Formulated an analytical model using a discrete 2-D Markov chain to represent PRSCA.

Main Results:

• PRSCA effectively reduces the probability of data collisions in IEEE 802.11ah networks.
• The proposed algorithm demonstrates significant improvements in saturation throughput.
• Enhanced network throughput and reduced access delay were observed with PRSCA.

Conclusions:

• The Pseudorandom Sequence Contention Algorithm (PRSCA) offers a superior alternative to BEB for IEEE 802.11ah.
• PRSCA enhances wireless network efficiency by minimizing collisions and improving key performance indicators.
• This research contributes to optimizing medium access control in modern wireless standards.