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A Method for Integer Finite Field Compressive Sensing

A compressed sensing and finite field technology, applied in the field of information and communication, can solve the problems of code ring length limitation, changeability, and inability to apply modulation methods

Active Publication Date: 2020-07-07
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, using such a method makes the entire compressed sensing system suitable for relatively simple conventional compressed sensing systems, such as the most commonly used image perception field, but cannot be applied to the communication field where the modulation method is variable, and physical objects and complex numbers can be mixed, and so The method also has some restrictions on the encoding or parity check matrix used, such as the length limit of the code ring

Method used

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  • A Method for Integer Finite Field Compressive Sensing
  • A Method for Integer Finite Field Compressive Sensing
  • A Method for Integer Finite Field Compressive Sensing

Examples

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Embodiment 1

[0024] figure 1 An integer finite field compressive sensing method according to an exemplary embodiment of the present invention is shown. The method of this embodiment mainly includes:

[0025] Step 101, the sending end divides the information to be transmitted into fixed-length packets to obtain a first transmission signal;

[0026] Specifically, it is assumed that the digital signal to be transmitted is directly digitized by the information source without going through the information compression process in the information source coding. The terminal (transmitter) groups the information code stream in the form of an integer to be transmitted according to a certain number of symbols, and obtains the first transmission signal x;

[0027] Step 102, performing projection transformation on the integer field on the first transmission signal to obtain a second transmission signal;

[0028] Specifically, the first transmission signal x is precoded using the projection transforma...

Embodiment 2

[0060] figure 2 A schematic structural diagram of an integer finite field compressive sensing system according to an exemplary embodiment of the present invention is shown. The integer finite field compressed sensing system of the present invention specifically includes: a first communication device, which includes: a quantization grouping module, a projective transformation module, a modulation module, and a radio frequency transmitter; the second communication device (transmitter) includes: A radio frequency receiver, a carrier-to-noise ratio judgment module, a symbol selection module, a demodulation module, an equation solving module, and a compressed sensing reconstruction module.

Embodiment 3

[0062] Combine below figure 1 , figure 2 The compressed sensing algorithm based on the integer field provided by the present invention is described in detail. According to the aforementioned ideas, we can design a specific implementation scheme.

[0063] Assume that the original data to be transmitted can be grouped as x=[x 1 x 2 ... x N ] T , where N=15. Since the signal x is directly digitized from the source, it can be represented sparsely. A redundant dictionary Ψ can be constructed, and the signal x can be expressed as a sparse coefficient vector β of sparsity K in the Ψ domain. Use the integer matrix Σ (15×15 dimension) to carry out projection transformation processing on the code word x, and then get two 15-dimensional grouping signals y1 and y2 after modular division by two coprime integers such as (2, 3), and then After modulation is sent into the channel. The receiving end first judges the carrier-to-noise ratio, assuming that the carrier-to-noise ratio o...

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Abstract

The invention discloses an integer finite field compressed sensing method, which comprises the following steps: carrying out fixed-length grouping, projection transformation on an integer field, modular division operation and modulation on information needing to be transmitted to obtain a transmission signal, and sending the transmission signal; The receiving end receives the transmission signal and screens and demodulates the transmission signal; Obtaining a compressed sensing model based on the compressed observation value according to the demodulated signal and the corresponding integer modulus compressed observation value; And solving an original signal by using the compressed sensing model and a reconstruction algorithm. According to the invention, the compressed sensing processing isdirectly performed on the signal of the digital domain, and the digitized signal source symbol is directly processed at the signal source end, so that the process of compressing the information redundancy in the signal source coding is omitted, and the complexity of the signal source equipment end is reduced. Due to the fact that processing is directly carried out in a digital domain, the algorithm is achieved through a digital circuit, meanwhile, the function similar to channel error correction coding is achieved, and the anti-jamming capability of a communication system can be improved.

Description

technical field [0001] The invention relates to the field of information and communication technology, in particular to an integer finite field compressive sensing method. Background technique [0002] Reliable transmission of wireless communication in interference or noise environment can largely rely on forward error correction coding technology. However, error correction coding needs to increase the information redundancy for resisting channel interference. When it is applied in an actual system, in order to transmit efficiently, it is first necessary to perform source coding on the source first, and compress the information brought by the source itself. Information redundancy objectively increases the complexity of source equipment. [0003] On the other hand, compressed sensing technology directly utilizes the information redundancy of the source itself, which can reduce the sampling rate at the source end, thereby reducing the complexity of the source end equipment. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H03M7/30
Inventor 卓永宁
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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