Research On The Measurement And Adaptive Channel Selection Algorithm For IEEE802.11n Wireless Network

In recent years, IEEE802.11protocol family has become the most important protocol in the areaof short-distance interconnection and there are many wireless network products(Wi-Fi products) basedon the IEEE802.11standard. Widely recognized by users,IEEE802.11standardis also in constantevolution and development. The most important trends is the multi-hop wireless mesh interconnectionwhose representative is IEEE802.11s and high-speed transmission represented by IEEE802.11n.Nowadays, under the ideal channel conditions, the transmission rate of IEEE802.11n has been up to300Mbps, which fully meets the level of Ethernet.In the wireless transmission conditions, channel interference is the main cause of rate limition.This paper analyzes the channel allocation and noise source problems for IEEE802.11n wirelessnetwork, and gives the effective SNR model for predicting the channel noise and interference. We alsobuild a real test platform for testing the index and analysis. Based on the effective SNR model, thispaper proposes an adaptive selection algorithm of channels in the framework of IEEE802.11DCF,and the simulation results show the effectiveness of the algorithm. The main tasks and innovations ofthis paper are as follows:First, we give a detailed analysis of the evolution and trends for IEEE802.11n wireless network.Combined with the Matlab simulation, we analyze the channel allocation and sources ofinterference.Because the direct detection of noise and interference has the problems of badinstantaneity, high costs and difficult realization, we design a non-direct way to detect noise andinterference for IEEE802.11n wireless network.The methodmeasures the channel state information inthe different sub-carriers and then calculates SNR values.Second, in order to predict the channel transmission conditions, this paper presents an effectiveSNR model based on the moving average. This model uses the idea of moving average, and for thegiven transceiver stations and the current transmission channel,it predicts the SNR in the next timeaccording to the estimation values and the measured values of the SNR in the first few moments.Meanwhile, with the method offered by the first point, we build a relevant test platform to completethe testing and analysis of the links’ performance for forecasting results of SNR.Third, by using the effective SNR model and the IEEE802.11DCF(Distributed CoordinationFunction) framework, we propose an adaptive channel selection algorithm based on the model. Thealgorithm could predict the real-time channel transmission conditions, and compare the effective SNRwith the channel SNR threshold, for selecting a channel(who has the corresponding transmissionrate) by four-times handshakes mechanism. Our simulation results show that the algorithm caneffectively avoid interference, improve the throughput, reduce transmission delay and achieve anoverall optimization.