Low-computation-complexity and high-reliability coding and decoding algorithm for distributed process monitoring information source

Abstract

The invention discloses a low-computation-complexity and high-reliability coding and decoding algorithm for a distributed process monitoring information source. For the problem that the computation complexity is high due to the fact that a random observation matrix is used at a coding end, a sparse binary observation matrix is used at the coding end in the invention; multiplication in non-correlated linear measurement is changed into additive operation; therefore, the coding computation complexity is reduced; the energy consumption of the algorithm is reduced; the algorithm is very suitable for a sensor node to perform independent coding; for the problem that the decoding reliability is low due to the fact that a decoding end excessively depends on one side information, a distributed decoding recovery algorithm based on multiple side information is provided in the invention; the main solution is as follows: the multiple side information is used; the side information is sorted according to the priority through two indexes including the inter-signal difference estimated sparsity and the recovery residual error; the decoding accuracy rate is increased by using the optimal side information; when the optimal side information cannot be obtained, the sub-optimal side information is used; and, by parity of reasoning, the decoding reliability is improved.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a codec algorithm with low computational complexity and high reliability for distributed process monitoring information sources. Background technique [0002] Distributed information sources can be divided into two types: distributed real-time information sources and distributed process information sources in terms of monitoring requirements. Distributed real-time monitoring sources refer to sources that require high real-time information, such as gas, wind speed, negative pressure, etc. These sensor nodes need to output a sampling value and transmit it regularly in a short period of time, requiring real-time encoding and decoding . Distributed process monitoring sources refer to sources that do not require high real-time information, such as coal mine goaf temperature, channel waves, microseismic, etc. These sensor nodes do not need real-time transmission, and can be collected ...

AI Technical Summary

Problems solved by technology

However, the algorithm relies too much on one side information, which will lead to low decoding reliability and effectiveness. When the side information sensor communication is interrupted, no side information will be available. When the side information has little correlation with the signal to be recovered, the decoding will be successful. very low rate

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