Self-adaptation compression reconstruction method based on energy effectiveness observation in cognitive sensor network

Abstract

The invention discloses a self-adaptation compression reconstruction method based on energy effectiveness observation in a cognitive sensor network. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network comprises the steps that (1) a node carries out local detection and compression measurement on data which are actually sensed through an analog transcriber according to the characteristic that power consumption of the node of a cognitive sensor is limited, (2) a space-time relevance structure of sensing signals is used, sensing data are mapped to a wavelet orthogonal basis cascading dictionary to carry out sparse conversion and to carry out self-adaptation observation through a weighting energy subset function, appropriate observation values are obtained in an energy effectiveness mode, orthogonalization is carried out on selected observation vectors to construct a measurement matrix, (3) the sensing data after compression measurement are fed back to an aggregation node through a report channel, the aggregation node carries out self-adaptation reconstruction on the sensing data by using a gradient projection sparse reconstruction Barzilai-Borwein method based on a convex relaxation method, and effective compromise between reconstruction performance and energy consumption of the node is achieved. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network can carry out accurate reconstruction on the sensing signals, ensures energy effectiveness of the sensing node, and has actual application significance.

Description

technical field [0001] The invention belongs to the technical field of information and communication engineering, and relates to a wireless sensor network technology in a wireless communication system, a cognitive radio technology, and a convex-relaxation quadratic programming adaptive compression reconstruction method in the theory of compressed sensing, so as to realize the performance of perceptual signal reconstruction and An effective trade-off between energy consumption of network nodes, specifically an adaptive compression reconstruction method based on energy-efficient observations in cognitive sensor networks. Background technique [0002] Cognitive Radio (CR), also known as cognitive radio, can intelligently use a large amount of idle spectrum to satisfy secondary users (Secondary Users, SUs) without affecting the communication of Primary Users (PUs). Reliable communication of Cognitive Users (CUs), so as to improve the utilization of wireless spectrum and realize ...

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Problems solved by technology

However, it is difficult to construct a suitable observation matrix that satisfies the RIP characteristics from the signal spars

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