Multihop Wireless Sensor Network Decision Fusion Under Scurviness Transmission Environment

Recently, with the development of wireless sensor and networking technology, the wireless sensor network decision fusion issues are attracting more attention and research. This paper focuses on the wireless sensor network decision fusion issues under scurviness transmission environment using distributed fusion mode. The decision fusion rules of wireless sensor network decision fusion systems using multihop information transmission mode under single-side Guassian fading channels have been deeply studied.Firstly, the basic concepts and research status of wireless sensor network decision fusion are briefly introduced, the existing problems of the current study on wireless sensor network decision fusion are also pointed out, and the work arrangement of the research on wireless sensor network decision fusion in this paper is given. Subsequently, a introduction of single-side Guassian fading channels is given, via which the decsion information is transmitted, and the main parts of wireless sensor network decision fusion system using multihop information transmission mode is also introduced. Then, a review of decision fusion rules of wireless sensor network decision fusion system using traditional information transmission mode based on single-side Guassian fading channels is made. Based on the existing results, the decision fusion rules of wireless sensor network decision fusion system using multihop information transmission mode are derived. The optimal decision fusion rule based on instantaneous channel state information and sub-optimal decision fusion rule based on channel statistics are obtained, respectively.In the end of the paper, with the introduction of the simulation method of decision fusion system, setting principle of simulation parameters and approaches for comparing the decision fusion rules, the simulation comparison and analysis performance of the proposed decision fusion rules are made. In the end, a summary of the contributions in this paper is made and the future of research on wireless sensor network decision fusion is also prospected.