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An Adaptive Network for Sparse Parameter Vector Estimation

An adaptive network and sparse parameter technology, applied in network topology, digital transmission system, baseband system components, etc., can solve the problems of slow convergence of sparse unknown parameter vectors, low steady-state imbalance, etc., and achieve low steady-state imbalance, fast The effect of convergence speed

Active Publication Date: 2018-10-12
苏州容润通信技术有限公司
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0005] Purpose of the present invention: provide an adaptive network for sparse parameter vector estimation, which solves the problem of slow convergence of sparse unknown parameter vector estimation using DAPA's adaptive network, and can also have low steady-state imbalance at the same time

Method used

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  • An Adaptive Network for Sparse Parameter Vector Estimation
  • An Adaptive Network for Sparse Parameter Vector Estimation
  • An Adaptive Network for Sparse Parameter Vector Estimation

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Embodiment

[0044] In order to better illustrate the objectives and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. The following sections further illustrate the above solutions in combination with specific embodiments. It should be understood that these embodiments are used to illustrate the present invention without limiting the scope of the present invention. The implementation conditions used in the examples can be adjusted according to specific applications, and implementation conditions not specified are usually conditions in routine experiments.

[0045] In this embodiment, the adaptive network using the VSS-DPAPA method (abbreviated as VSS-DPAPA) is used to identify an unknown parameter vector, and its performance is compared with the adaptive network using the DAPA method and the adaptive network using the DPAPA method (abbreviated as DAPA respectively). Compared with t...

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Abstract

The invention discloses an adaptive network used for estimation of a sparse parameter vector and belongs to the field of wireless sensor networks. Each node in the network comprises a wireless transceiver and an adaptive filter, wherein the wireless transceivers are used for receiving and sending data between nodes in neighborhoods, and the adaptive filters are used for estimating parameters through data received by the wireless transceivers; the adaptive filters included in the nodes in each neighborhood cooperate with a diffusion type variable-step-size proportion affine projection method to perform parameter estimation. Besides, for each network node, the time-variant step size of each adaptive filter is generated with noiseless priori error power and noise power, and higher convergence rate and lower steady-state maladjustment are obtained at the same time.

Description

Technical field [0001] The invention discloses an adaptive network used for sparse parameter vector estimation, and specifically relates to a variable step-length proportional affine projection distributed method for parameter estimation, belonging to the field of wireless sensor networks. Background technique [0002] An adaptive network is a communication network composed of multiple nodes scattered in an area, and data transmission between nodes usually takes place in a specific way. Each node is equipped with an adaptive filter for adaptive estimation of unknown parameter vectors. At present, the application of adaptive networks is very extensive, such as wireless sensor networks, wireless spectrum estimation, target tracking and other fields. [0003] The main indicators for measuring the performance of adaptive networks are convergence speed and steady-state imbalance. The speed of convergence determines the time required for the adaptive network to estimate the unknown par...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L25/02H04W84/18
CPCH04L25/0242H04W84/18
Inventor 倪锦根施娟
Owner 苏州容润通信技术有限公司