Throughput and PER estimates harnessing link-layer measurements for indoor 802.11n WLAN

The research work reported in this paper investigates if a Markov chain can model the throughput and packet error rate (PER) performance of off-the-shelf IEEE 802.11n wireless LAN network interface cards (NICs). We draw together uplink -downlink information from the NIC with a Markov chain to examine the performance of 802.11n within an indoor environment. Site measurements and point-estimates are taken and compared with the model predictions. Errors of less than 4% were recorded for the Markov model estimates while point-estimates recorded average errors of 9% both compared to site-measured throughput.

► A hybrid Markov model incorporating link-layer metrics is introduced.
► The model considers uplink–downlink SS changes to ascertain MCS transitions.
► Throughput and PER prediction improved by leveraging link-layer measurements.
► Reported results in this paper expand existing data on 802.11n performance.