Over the years, advancements such as increased bandwidth, new modulation and coding schemes, frame aggregation, and the use of multiple antennas have been employed to enhance Wi-Fi performance. Nonetheless, as network density and the demand for low-latency applications increases, contention delays and retransmissions have become obstacles to efficient Wi-Fi deployment in modern scenarios. The introduction of Orthogonal Frequency-Division Multiple Access (OFDMA) in the IEEE 802.11 standard allows simultaneous transmissions to and from multiple users within the same transmission opportunity, thereby reducing the contention. However, the AP must efficiently manage the resource allocation, particularly in uplink scenarios where it lacks prior knowledge of users' buffer statuses, thus making polling a critical bottleneck in networks with a high number of users with sporadic traffic pattern. This paper addresses the polling problem and introduces the A2P algorithm, designed to enable scalable and efficient polling in high-density OFDMA-based time sensitive Wi-Fi networks. Simulation results show that A2P outperforms the alternative schemes by maintaining significantly lower delay and packet loss in dense time-sensitive teleconferencing scenario.

In a modern conference room, various of video and audio devices are provided to ensure efficient communications. This is commonly referred to as a conferencing system. Compared to wired conferencing systems, wireless systems require less deployment effort, but may become unreliable when the selected radio spectrum is highly occupied. This demo focuses on improving the quality of service of a commercial wireless conferencing system using dynamic channel selection based on real-time spectrum sensing. The proposed solution is verified in a large-scale wireless testbed, and the result shows that the link of the conferencing system is indeed more robust against interference when cognitive solution is applied.