Multicast video streaming over WiFi networks: Impact of multipath fading and interference

Abstract

Delivery of multimedia digital content through wireless networks poses non-trivial performance issues because of scarcity and volatility of the wireless medium. The goal of this study is to analyze the impact of multipath fading and interference on multicast video streaming in an indoor LOS (Line of Sight) wireless environment using off-the-shelf fixed WiFi equipment. Multipath fading experienced by the receivers is represented by empirically estimating ricean K-factor from packet traces captured at the receivers. Degradation in the video quality incurred during transmission is quantified by measuring video quality metric (VQM). To quantify the impact of channel interference, controlled traffic is generated on a channel adjacent to the selected channel. We use human movements to alter the depth of signal fading at the receivers. Our experiments show that packet loss increased two times in the face of multipath fading and almost three times in the face of channel interference. The measurements presented in this paper can help users to monitor and maintain the quality of their wireless networks and optimize the use of limited network resources.

Modelling the impact of interference on the energy efficiency of WLANs

“…21,22 The statistics of timestamps and received signal strength (RSS) of data packets obtained from the extra devices are sampled to characterize the interference impact on performance. In the work of Rehman et al, 25 the authors conduct six multicast video streaming experiments with varying interference and signal fading. In the work of Basso et al, 24 authors run a tool named network neutrality bot (Neubot) at application level to measure the round-trip time (RTT) and goodput for a fixed number of seconds to estimate the packet loss rate (PLR) over a TCP connection.…”

“…In the work of Basso et al, 24 authors run a tool named network neutrality bot (Neubot) at application level to measure the round-trip time (RTT) and goodput for a fixed number of seconds to estimate the packet loss rate (PLR) over a TCP connection. In the work of Rehman et al, 25 the authors conduct six multicast video streaming experiments with varying interference and signal fading. It is shown that interference has more impact on performance than signal fading, and adjacent-channel interference dominates.…”

Studi Eksperimen Pengiriman Sinyal Video Real-Time Dengan Aplikasi Skype Mobile Pada Jaringan Nirkabel 802.11 di Tengah Interferensi Kepadatan Lalu Lintas Manusia

“…Melalui kajian pustaka yang telah penulis lakukan, seperti yang telah dilakukan oleh beberapa penelitian sebelumnya [4], [32], [3], [33] hasil menunjukan bahwa pergerakan objek bergerak seperti manusia ditengah jaringan wireless seperti wifi dapat mempengaruhi propagasi gelombang elektromagnetik yang memberikan pengaruh pada link throughput jaringan. Analisa yang penulis lakukan dapat dilihat pada grafik 4-5 dibawah ini.…”

A new design of the IEEE 802.11 MAC layer to enhance the scalability of the DMS service

“…Thus this ACK policy guarantees the same unicast reliability level to multicast services on the cost of the bandwidth. Therefore DMS can be used to stream a standard multicast traffic to a limited group size, but does not scale well for High Definition (HD) streams like HDTV even using the high throughput 802.11n PHY layer since the effectively available bandwidth remains limited and variable [15,16] for three main reasons. 1) The channel bit error rate (BER).…”