Analysis of Performance Parameters in Wireless Networks by using Game Theory for the non Cooperative Slotted Aloha Enhanced by ZigZag Decoding Mechanism

TL;DR

This paper analyzes how combining ZigZag decoding with non-cooperative slotted Aloha improves wireless network performance by modeling the system with a Markov chain and using stochastic game theory.

Contribution

It introduces a novel analysis of non-cooperative slotted Aloha combined with ZigZag decoding using a Markov chain and stochastic game modeling.

Findings

Improved throughput and delay performance with the proposed approach

Enhanced system efficiency compared to simple slotted Aloha

Effective modeling of the system with a two-dimensional Markov chain

Abstract

In wireless communication networks, when the workload increases, sources become more aggressive at the equilibrium in the game setting in comparison with the team problem by using slotted Aloha mechanism. Consequently, more packets are in collision and are lost. To reduce these phenomena and to enhance the performance of the networks, we propose to combine ZigZag decoding approach with non cooperative slotted Aloha mechanism. This approach was introduced in our previous work based on the cooperative slotted Aloha mechanism. The obtained results showed that this approach has significantly improved the cooperative slotted Aloha mechanism and gave best results for the throughput and delay. In this paper, we analyze the impact of combining non cooperative slotted Aloha and ZigZag Decoding. We model the system by a two dimensional Markov chain that integrates the effect of ZigZag decoding. The states of the Markov chain describe the number of backlogged packets among the users. We use a stochastic game to achieve our objective; we evaluate and compare the performances parameters of the proposed approach with those of a simple slotted Aloha mechanism. All found results show that our approach improves the performance parameters of the system.