An equably distributed random number generator and its generation method

Abstract

The utility model relates to a generator of random number with even distribution, comprising an initialization model, a selector, an MAC and a retarder, which comprises a primary shifting model, a secondary shifting model, a primary adder, a third shifting model, a fourth shifting model and a secondary adder as well. The utility model also relates to a generating method of random number with evendistribution, the steps of which are as follows: firstly, the numerical value x0 is obtained, then a is multiplied by x0 and c is added to get z, with a and c are both nonnegative integers; secondly,z is shifted n digits to the right with the shifter to get zl; z1 is shifted n digits to the left to get z2, wherein, 2na+c<22n; thirdly, the sum of z and z1 minus z2 is y; fourthly, 1 is added to y and n digits are shifted to the right to get y1; y1 is shifted n digits to the left with the shifter to get y2; the sum of y and y1 minus y2 is xi+1, which is the random number generated; fifthly, xi=1 delays and is multiplied by c to get z, then the second step is returned to. The utility model has the advantages of reducing the calculated amount and enabling to satisfy the situations when the real-time generating and evenly distributed random number generator is needed.

Description

Technical field [0001] The present invention involves the field of information electronics, especially a uniform distribution random number generation method and a uniform distribution random number generator. Background technique [0002] Random numbers are widely used in the field of information electronics.For example, in the design of the mobile communication system, the various characteristics of wireless channels need to be simulated in the laboratory, and the performance or performance of the communication system algorithm under these channels will be simulated and evaluated.Test the communication system with channel simulation. Compared with the actual communication environment, the controllability and repeatability are strong, which can save a lot of manpower and material resources. [0003] The implementation method of channel simulation technology can generally be divided into software simulation and semi -solid simulation.The typical example of the former is to model ...

AI Technical Summary

Problems solved by technology

[0019] The technical problem to be solved by the present invention is to solve the problem that when the existing linear congruence method realizes a uniformly distributed random number generator, the amount of calculation is too large to meet the real-time requirements To solve the problem, provide a uniformly distributed random number generation method and system that can be easily and quickly implemented in fixed-point devices such as FPGA or DSP

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