Refine the Ideal Rate Adaptation Algorithm to optimize Wi-Fi Networks
الموضوعات :
1 - گروه مهندسی برق،واحد فسا،دانشگاه آزاد اسلامی،فسا،ایران
الکلمات المفتاحية: Rate Adaptation Algorithm (RAA), MIMO Rate Adaptation (MRA), SNR-aware Intra-frame Rate Adaptation (SIRA), MAC Protocol Data Unit (MPDU), Frame Loss Rate (FLR), modulation and coding schemes (MMCS),
ملخص المقالة :
Several Rate Adaptation Algorithms have been proposed and implemented over the years, ranging from simple fixed-threshold methods to more complex machine learning based approaches. These algorithms employ different strategies to determine the optimal data rate, such as monitoring the number of successful or failed transmission attempts and estimating the channel conditions based on SINR or RSSI. In this paper, we evaluated four different Rate Adaptation Algorithms. The primary focus of this analysis was to determine their performance in terms of throughput and packet loss across various network conditions. These algorithms, which represented a range of approaches to rate adaptation, were tested to help us understand their relative strengths and weaknesses and select the most effective one. We then discuss the lessons learned from the results of this evaluation.
[1] Sushma. U. Bhover, Anusha Tugashetti, and Pratiksha Rashinkar. V2x communication protocol in vanet for co-operative intelligent transportation system. 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), pages 602–607, 2017.
[2] Wenli Yang, Xiaojing Wang, Xianghui Song, Yun Yang, and Srikanta Patnaik. Design of intelligent transportation system supported by new generation wireless communication technology. International Journal of Ambient Computing and Intelligence, 9:78–94, 01 2018.
[3] Haider Mahmood Jawad, Rosdiadee Nordin, Sadik Kamel Gharghan, Aqeel Mahmood Jawad, and Mahamod Ismail. Energy-efficient wireless sensor networks for precision agriculture: A review. Sensors, 17(8), 2017.
[4] Chamil Kulatunga, Laurence Shalloo, William Donnelly, Eric Robson, and Stepan Ivanov. Opportunistic wireless networking for smart dairy farming. IT Professional, 19(2):16–23, 2017.
[5] Kaveh Pahlavan and Prashant Krishnamurthy. Evolution and impact of wi-fi technology and applications: A historical perspective. International Journal of Wireless Information Networks, 2020.
[6] Saad Biaz and Shaoen Wu. Rate adaptation algorithms for ieee 802.11 networks: A survey and comparison. pages 130–136, 2008.
[7] Wei Yin, Peizhao Hu, Jadwiga Indulska, Marius Portmann, and Ying Mao. Mac-layer rate control for 802.11 networks: a survey. Wireless Networks, 2020.
[8] James Gross, Florian Schmidt, Oscar Punyal, Anwar Hithnawi, and Klaus Wehrle. A receiver based 802.11 rate adaptation scheme with on-demand feedback. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2012.
[9] Okhwan Lee, Jihoon Kim, Jong tae Lim, and Sunghyun Choi. Sira: Snr-aware intra-frame rate adaptation. IEEE Communications Letters, 2015.
[10] Ioannis Pefkianakis, Suk-Bok Lee, and Songwu Lu. Towards mimo-aware 802.11n rate adaptation. IEEE/ACM Transactions on Networking, 2013.
[11] Duy Nguyen and J. J. Garcia-Luna-Aceves. A practical approach to rate adaptation for multi-antenna systems. page 331–340, 2011.
[12] Lito Kriara and Mahesh K. Marina. Samplelite: A hybrid approach to 802.11n link adaptation. SIGCOMM Comput. Commun. Rev., 2015.
[13] Ioannis Selinis, Konstantinos Katsaros, Seiamak Vahid, and Rahim Tafazolli. Damysus: A practical ieee 802.11ax bss color aware rate control algorithm. International Journal of Wireless Information Networks, 2019.
[14] Weijie Yu and etl., Environment-Aware Rate Adaptation Based on Occasional Request and Robust Adjustment in 802.11 Networks, sensor,23(18), sep 2023.
[15] Tingpei Huang, Haiming Chen, Zhaoliang Zhang, and li Cui. Easira: A hybrid rate adaptation scheme for 802.11 mobile wireless access networks. IEEE Wireless Communications and Networking Conference, WCNC, 2012.
