Performance Analysis And Optimization For High Efficient WLAN In Multilevel Network

With the emergence and development of the mobile cloud compute,the mobile Internet as well as the Internet+,IEEE 802.11 wireless local area network(WLAN)has become one of the main network access technology for massive deployment scenario like high density hotpots,large office and etc.However,as network deployment intensifies,the traditional wireless access mechanism imposes restrictions on system capacity of WLAN.Therefore,a high efficiency access mechanism should be studied to improve transmission efficiency,which becomes an urgent problem that need to be solved.Meanwhile,due to the scarcity of the licensed spectrum,the operators put key eyes on the unlicensed band to improve the capacity of the cellular network.Then,LTE licensed-assisted-access(LAA)has been proposed to extend LTE system to unlicensed bands.The intrusion of the LTE makes the network environment of WLAN more complicated,and the fairness coexistence between WLAN and LTE in the unlicensed band is a critical issue to implement LTE-LAA in the unlicensed band.On the other hand,the integration of WLAN and cellular network is the trend of the future network architecture.But how operators allocate traffic reasonably between WLAN and cellular network to achieve the high fusion efficiency is a difficult technical problem.To deal with the problems above,we do some research on WLAN in performance analysis and optimization,including multiple nodes parallel transmission in WLAN,the fairness spectrum sharing in unlicensed band of WLAN/LTE-U network,and the mobile data offloading in heterogeneous wireless network between WLAN and LTE,which aim to improve the transmission efficiency,spectrum sharing efficiency and the network convergence efficiency in multilevel network.The main works and innovations can be summarized as follows.1)Performance analysis based on two-dimensional Markov chain of multi-users parallel transmission access mechanism in wireless LAN PerformanceTo deal with the inefficiency of MAC layer access technology in the existing WLAN,the multi-nodes parallel transmission mechanisms are proposed to improve the transmission efficiency.In theory,the modeling and analysis of the MAC layer protocol is the premise of optimization,but very little literatures on analysis model about the parallel transmission protocol.In view of this problem,we focus on the TXOP sharing mechanism of IEEE 802.11ac enhanced distributed channel access(EDCA)supported multi-user parallel transmission.We propose the two-dimensional Markov chain to model the access process of different priorities of users.Consequently we derive the transmission probability,collision probability and throughput taken the unsaturated condition into account.The simulation results show that our proposed analytical model can provide a close estimation of the network throughput and the TXOP sharing mechanism can improve the network capacity.2)Performance analysis and optimization based on time and space jointed Markov Chain of multi-APs parallel transmission access mechanismTo deal with the network capacity constrained by the access point with less antennas,the multiple dimensional carrier sensing based MAC access protocol is presented by researchers to support multiple independent APs to simultaneously communicate with their clients on the same channel.Based on this protocol,we develop an analytical model based on a jointed Markov Chain model of the time and space dimension to derive the probability matrix that each type of AP wins the medium in each dimensional carrier sensing.Then based on statistical signal processing theory,the effective SNR is used to compute the transmitted rate of each type AP under each dimensional carrier sensing.According to the above results,we derive the throughput and mean access delay of each type AP in heterogeneous multiple antennas WLAN.Meanwhile,the parameters are optimized to improve the performance.The simulation results verify that our proposed analytical model can provide a close estimation of the network throughput and mean access delay.Compared with the traditional access mechanism,multi-node parallel transmission mechanism can effectively enhance the transmission efficiency of WLAN.3)Analysis of unlicensed spectrum sharing based on collaborative clustering in WLAN/LAATo cope with the low sharing efficiency of WLAN/LAA on the unlicensed spectrum,a fair co-existence access mechanism based on collaborative clustering is proposed.Firstly multiple LAA SBSs adaptively form a cluster and each cluster is treated as a unit to content the channel using the listen before talk(LBT)mechanism.This greatly reduces the collision probability due to the decrease of the number of competing nodes in the coexisting network.The SBSs in the cluster transmit data simultaneously using cooperative beamforming when the cluster wins a transmit opportunity with LBT.Semi-orthogonal user selection(SUS)algorithm is adopted to identify adequate sets of users for a cluster to achieve high sum capacity in the cluster.Zero-forcing beamforming(ZFBF)is used to suppress inter user interference of the cluster.Based on the above access mechanism,we derive a closed-form expression to analytically predict the upper bound sum rate of the cluster.Finally,we derive the system throughput for WiFi and LTE based on Markov chain model.The results verify that our proposed analytical model can match well with the simulation results.And the simulation results also show that the proposed cooperative LAA is able to achieve up to 22%increase in overall system throughput,but also 30%improvement in fairness.4)Adaptive Mobile data offloading based on Attractor selection in WLAN/LTE heterogeneous networksTo cope with poor adaptability of the existing traffic offloading schemes,a bio-inspired attractor selection model is used to design the self-adaptive mobile data offloading strategies including traffic offloading ratio and associated AP in a time-varying environment conditions.Firstly,in view of the traffic offloading ratio selection decision problem,considered the sparse and non-overlapping coverage of WiFi,we design a mapping function that maps the throughput of WiFi and LTE to the activity of the attractor selection model,which indicates the goodness of the environment.Then the nonlinear differential equation is designed as the function of activity and traffic offloading ratio.The unstable equation solution can be regarded as the indicator to initiate the offloading ratio selection algorithm to adjust the offloading ratio until the equation solution becomes stability.We also design the mobile data offloading network based on software defined network to realize flexible and open network architecture.Secondly,as for associated network selection decision problem,we consider the scenario with multi-APs overlapping in dense WiFi network.Under this case,the offloading effectiveness and service delay are mapping to the activity.The associated probability of each APs in the area is defined as network control value.Then the nonlinear differential equation is designed as the function of activity and control value.Finally,to sovle the pingpang effect,we future design the network selection algorithm based on attractor selection,which enables users to dynamically select an appropriated APs according to the dynamic conditions of various available networks.This can achieve maximum offloading efficiency and ensure the QoS.Simulation results show that the proposed method can adaptively adjust the offloading strategy,such as offloading ratio and the associated AP,which can greatly improve the offloading performance as well as the network integration efficiency in the heterogeneous network.5)Performance analysis based on stochastic geometry and semi-Markov Chain in delayed mobile data offloading networkTo build the generalized analysis model in delayed mobile data offloading network,under the scenario with random deployment of WLAN,a stochastic geometry model and semi-Markov Chain is proposed,which aims to understand how the network parameters,such as network size,channel condition,affect the long term offloading potential in the dense WiFi scenarios.The deployment of WiFi is modeled as an independent Poisson point process(PPP)and the hard core point process is used to mimic the access mechanism based on CSMA/CA.Then we derive the coverage probability and mean data rate of each area taken the effect of interference into account.Then the semi-Markov process is used to model the user's movement taking the sojourn time into account.Based on user's coverage probability,mean data rate as well as mobile process,the potential offloading traffic can be obtained.Through above proposed analytical studies,the network providers can easily obtain a rough estimation on the average offloading performance from a given dense network.The simulation results show that the density of WiFi deployment and the channel condition have great influence on the offloading.The analytical results can also provide some ideas for subsequent optimization.