Research On Three Sensing Problems Based On Signal Propagation Features In Wireless Networks

With the continuous advancement of wireless network technologies,devices,and the increasing network coverage,wireless networks have evolved from a single communication system to a complex system that integrates both communication and sensing capabilities.The sensing capability could improve the performance of the wireless network in a directly or indirectly way,which has important theoretical and practical significance.Therefore,how to sense the information with the features of wireless network itself comes to one of the most important topics,which causes great widespread concern by domestic and foreign researchers.According to different design goals,information sensing problems are mainly divided into two categories: spatial domain and frequency domain information sensing.The design goal of spatial domain information sensing is to improve the performance of the wireless network directly by increasing the additional function of the wireless networks,while the goal of frequency domain information sensing is to improve the performance of wireless network indirectly by optimizing the spectrum utilization efficiency.In this paper,we focused on three significant sub-topics from both spatial domain and frequency domain information sensing area,and also analyzed how to use the wireless signal propagation features for these three subtopics respectively.These three sub-topics are: free space fading feature based location sensing problem,multipath fading feature based human gesture sensing problem and interference feature based subcarrier-level spectrum sensing problem.Specifically,our contributions are as follows:(1)For the first sub-topic,we proposed SULP model and CESILA algorithm respectively for resolving the low localization error rate and coverage rate issues for distancefree localization algorithms.The main contributions of SULP model(Scalable Uniform Localization Performance evaluation model)are to quantify the impact of the free space fading feature and other network parameters on the classical distance-free algorithms,and to optimize the algorithms by the quantified results;The main contributions of CESILA algorithm(Circle External Square Intersection based Localization Algorithm)is to optimize the traditional APIT algorithm according to the quantization result of SULP.The improved algorithm increases the localization coverage rate and accuracy,while reduces the location sensing overhead.(2)For the second sub-topic,we proposed and implemented rRuler model and rRulerHMM-based human gesture sensing system respectively for increasing the sensing accuracy of the coarse-grained multipath fading measurement based gestures sensing problem.The main contribution of the rRuler(rough Ruler could measure fine-grained information)model is the use of coarse-grained multipath fading measurements for fine-grained human gesture feature extraction.The main innovations of the rRuler model include multipath fading feature measurements.,The resolution enhancement strategy,the different gesture duration marking strategy,the time-frequency domain analysis strategy and the k-means based feature clustering strategy.Experimental results show that the accuracy of the feature extraction increased by 20-30% compared with traditional algorithms.The main contribution of rRulerHMM(rRuler and HMM-based Gesture Sensing System)is to further verify the accuracy of rRuler model.In this paper,the rRuler-HMM system has more than 90% accuracy in gesture sensing applications which meets the requirements the daily use.(3)For the third sub-topic,we proposed Subcarrier-Sniffer and CTCA algorithm respectively for further optimizing the spectrum utilization in the heterogeneous coexisting networks.The main contribution of Subcarrier-Sniffer algorithm is to propose a sub-carrier level spectrum sensing algorithm,which can further improve the spectrum utilization and promote the performance of heterogeneous coexistence network.Experimental results show that accuracy of the sub-carrier level spectrum sensing reaches 90% or more.Based on Subcarrier-Sniffer algorithm,we further propose CTCA algorithm for further improve the spectrum utilization of the WiFi/LTE coexsting networks.The main contribution of CTCA algorithm is to optimize the spectrum sensing and spectrum occupancy of WiFi and LTE devices according to network deployment density.Experimental results show that compared with the existing WiFi / LTE spectrum sharing algorithm,CTCA in the case of dense node deployment,the spectrum utilization rate of the spectrum,the use of the spectrum,Increased by 2.9 times.To summarize,in this paper,we use the free-space fading feature,multipath fading feature and interference feature of the wireless network to study the location sensing problem,the human gesture sensing problem and the sub-carrier level spectrum sensing problem.Experimental results show that the above model,algorithm and system can solve some theoretical and practical problems information sensing area,and can provide some reference for the research and application of the same kind.