Performance of Ad Hoc Wireless Networks under Coexistence Scenario: A Case Study

Abstract

Owing to the possibility of interference, signal contention, and performance degradation, coexisting IEEE 802.11 (Wi-Fi) and IEEE 802.15.4 (Zigbee, 6LoWPAN) technologies in the 2.4 GHz ISM band presents considerable issues. More packet loss, delay, and decreased throughput for low-power networks can arise from IEEE 802.11\'s larger bandwidth, higher transmission power, and higher data rates overpowering IEEE 802.15.4\'s lower power and narrower bandwidth transmissions. This work explores the main facets of their coexistence, emphasising the effects of interference on performance measures including throughput, latency, and energy efficiency and frequency overlap. Dynamic frequency selection and channel allocation algorithms are only a few of the interference reduction techniques that are examined in the analysis. This research offers valuable insights into the more harmonious coexistence of these two wireless technologies in shared surroundings, enabling dependable operation for low-power IoT networks and high-speed Wi-Fi applications. These insights are gained through simulation and experimental validation.

Introduction

The 2.4 GHz ISM band is used by many wireless communication standards, notably IEEE 802.11 (Wi-Fi) and IEEE 802.15.4 (used in low-power, low-data-rate protocols like Zigbee and 6LoWPAN). These technologies coexist in the same frequency range, but this creates challenges, as Wi-Fi's high transmission power and bandwidth can interfere with IEEE 802.15.4's low-power communications, leading to performance issues. The problem is most noticeable in environments such as smart homes, industrial automation, and IoT networks where both technologies are active.

Key Issues:

• Interference: Wi-Fi's higher transmission power, wider bandwidth, and frequent transmissions can cause packet collisions, increased delays, reduced throughput, and energy inefficiencies for IEEE 802.15.4 networks.

• Spectrum Sharing: The crowded 2.4 GHz frequency spectrum causes interference, particularly in urban areas with dense networks of both technologies.

• Medium Access Control (MAC) Protocols: Both Wi-Fi and IEEE 802.15.4 use Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), but they have different backoff algorithms and criteria for accessing the channel, which complicates coexistence.

The Need for Effective Spectrum Sharing:

As the number of IoT devices and wireless networks grows, ensuring smooth coexistence between these technologies has become increasingly crucial. The performance of IEEE 802.15.4 networks can degrade significantly due to Wi-Fi interference, which is a problem for battery-operated devices in settings that require low power and low data rates.

Research Focus:

The text reviews existing research on the performance of IEEE 802.11 and IEEE 802.15.4, specifically the issues that arise from their coexistence. Researchers are exploring ways to minimize interference, including adjusting MAC protocols, using adaptive backoff mechanisms, and frequency hopping. Several strategies, such as channel allocation, dynamic switching, and clear channel assessment, have been proposed to improve spectrum sharing.

Literature Survey:

Numerous studies have focused on various aspects of coexistence:

• Channel Access: Methods to reduce interference and improve packet delivery rates in IoT setups.

• Backoff Mechanisms: Some research proposes modifying backoff strategies for better coexistence.

• Interference Models: Studies have developed mathematical models and simulations to analyze interference patterns, such as Markov chains and queuing theory.

• Adaptive Solutions: Solutions like adaptive channel access and time-slot coordination are explored to minimize the impact of interference from Wi-Fi networks.

Technology Overview:

• IEEE 802.11 (Wi-Fi): Supports high-speed wireless communication and has evolved through versions like 802.11a/b/g/n/ac/ax to meet the growing demand for faster and more reliable wireless communication.

• IEEE 802.15.4 (ZigBee): Designed for low-power, low-data-rate applications, often used in IoT, sensor networks, and smart home devices. Its performance can suffer when coexisting with Wi-Fi.

Coexistence Strategies:

• Channel Allocation: Assigning non-overlapping channels for Wi-Fi and 802.15.4 can help reduce interference.

• Temporal Separation: Scheduling transmission times to avoid simultaneous broadcasts.

• Dynamic Switching: Using frequency hopping or adjusting the transmission power to avoid busy channels.

• Cross-Technology Communication (CTC): Exchanging information about transmission schedules to avoid interference.

System Model:

To evaluate cross-technology interference (CTI) between IEEE 802.11 (Wi-Fi) and IEEE 802.15.4 (ZigBee), the text describes a simulation scenario using the OMNET++ INET simulator. The model involves:

1. Wi-Fi and ZigBee nodes configured with specific power levels.

2. Examining the interference impact by selecting suitable channels.

3. Analyzing key performance metrics such as throughput, delay, and packet delivery ratio.

Conclusion

The coexistence of IEEE 802.15.4 and IEEE 802.11 networks results in improved packet reception rates and throughput. By reducing collisions, this study demonstrates how their application of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) increases throughput for both systems. IEEE 802.15.4 may efficiently occupy spectrum segments due to its narrower bandwidth, which reduces interference with IEEE 802.11 channels that are more widely used. This results in lower congestion for IEEE 802.11 hosts and fewer packet collisions for WPAN devices, which improves delivery success. By restricting airtime usage, WPAN devices\' low-duty cycle promotes coexistence even more. By optimising transmission patterns, adaptive techniques like frequency hopping and clear channel assessments help both standards.The study\'s findings basically show that these networkssupportive properties improve spectrum efficiency and performance. Advanced coexistence techniques, such as machine learning for dynamic channel allocation, should be investigated in future research to improve wireless communication systems even more. These advancements may help meet the growing need for dependable connectivity in a variety of applications.

References

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Copyright

Copyright © 2025 Gangaprasad Guntupalli, Janakiram Kottnana. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.