CN105634583A - Satellite OFDM carrier wave optimizing configuration method based on binary particle swarm - Google Patents

Abstract

The invention discloses a satellite OFDM carrier wave optimizing configuration method based on a binary particle swarm, and relates to a self-adaptive transmission technology in the satellite communication field. Aiming at the characteristics that the OFDM multi-carrier wave configuration is complex and the whole configuration is not flexible in the satellite communication, a binary particle swarm optimization is integrated in a configuration algorithm, and the configuration performance of the multi-carrier wave parameter is improved by using the efficient and multi-objective optimization capacity of the binary particle swarm optimization. In comparison with the prior art, the binary particle swarm optimization is introduced in the OFDM multi-carrier wave configuration in the satellite communication. The global configuration and optimization capacity of the system to a carrier wave source can be improved, and the source usage and user needs are adapted. The satellite OFDM carrier wave optimizing configuration method based on the binary particle swarm is particularly suitable for solving the problem of carrier wave configuration and optimization in a multi-carrier wave satellite network.

Description

Satellite OFDM carrier wave based on scale-of-two population distributes method rationally

Technical field

The present invention relates to the satellite ofdm communication technology in satellite communication field, particularly relate to a kind of satellite OFDM carrier wave based on scale-of-two population and distribute method rationally.

Background technology

Along with the development of satellite communications technology, the development of all kinds of technology is round broadband, and the direction of self-adaptation constantly extends. OFDM technology obtains well application in terrestrial wireless communication can effectively promote frequency spectrum resource utilization rate, is the important technology of transportation level in radio communication from now on. Satellite communications is a typical resource-constrained application scene, in order to the high efficiency of the handiness and frequency spectrum resource that effectively improve carrier wave, OFDM technology is applied in satellite communications, utilisation technology and the scene of ground maturation can be used for reference, it is possible to greatly promote the flexible configuration ability of satellite carrier.

In order to better OFDM technology is applied in satellite communication system, it it is very crucial research direction to the adaptive configuration technology of carrier parameter, utilize binary particle swarm algorithm to parameters such as the power of satellite OFDM carrier wave, code modulation modes, carry out multiple-objection optimization configuration, can effectively promoting carrier wave volume flexible configuration ability, maximumization and target carry out adaptation.

Summary of the invention

What the present invention seeks to the fast and flexible in multiparameter of lifting satellite OFDM carrier wave distributes ability rationally, promotes the suitability of resource and target. The present invention introduces binary particle swarm algorithm in satellite OFDM ZAP, mainly utilize on this algorithm, advantage in speed of convergence, stability, overall situation optimum solution can be converged to efficiently, fast, the configuration needs of OFDM carrier wave on complex scene can be met preferably, and the road providing a solution across the repeater utilization of resources for system.

The technical solution used in the present invention is, based on the satellite communications OFDM carrier wave collocation of scale-of-two population, Binary Particle Swarm Optimization is utilized on OFDM transmission system, distribute rationally flexibly for adaptive tracking control and adaptive modulation system, it is characterised in that specifically comprise the following steps:

(1) according to the multiple goal parameter optimized in satellite OFDM carrier wave, multiple objective function is set up;

(2), after setting up multiple objective function, binary particle swarm algorithm is utilized to set up a scale-of-two random particles group and random particles is carried out initialize; Wherein, random particles is made up of multiple goal parameter coding; Initialize comprise the position of random particles, speed, from Studying factors, society's Studying factors, inertia weight and iteration number of times;

(3) fitness value of each random particles in scale-of-two random particles group is calculated by the multiple objective function of foundation, in order to judge the distance of each random particles position apart from globe optimum; Wherein, globe optimum is the most advantage of all particles by searching out after each binary particle swarm algorithm;

(4) according to the iterative formula of Position And Velocity of scale-of-two particle, upgrading the Position And Velocity of random particles, simultaneously every time in iteration, by following the tracks of, two extreme values upgrade oneself to each random particles; Two extreme values are the most advantage of individuality and globe optimum;

(5) maximum iteration time of setting is judged whether to reach, if then proceeding to step (6); Otherwise, return step (3);

(6) value of global point gbest is exported, as the configuration parameter of the OFDM carrier wave in satellite communication network;

Complete the satellite OFDM carrier wave based on scale-of-two population and distribute process rationally.

Wherein, the mathematical expression formula of multiple objective function f (x) in step (2) is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\Σ}}{w}_i{f}_i$

Wherein, f_iIt is normalized to [0,1], w_iBeing the weight coefficient of i-th objective function, n is the number of multiple goal, W=[w₁,w_2,...,w_n],w_i��0,(1��i��m),

The present invention's tool compared with background technology has the following advantages

1. compared with prior art satellite OFDM carrier wave is configured problem, modeling becomes a global optimization problem, normalization method modeling means are utilized to set up unified objective function, and carry out multiple-objection optimization by means of binary particle swarm algorithm, the system that improves solves the ability of multiple goal configuration under complicated environment, improve frequency spectrum resource utilization rate, environment and demand intelligently can be carried out adaptation by system, by the configuration of carrier parameter.

2. it is fast that the binary particle swarm algorithm selected has optimal speed, the advantage that global optimization ability is good, is applicable to the rapid configuration of Complex multi-target parameter.

Accompanying drawing explanation

The satellite OFDM carrier wave that Fig. 1 is scale-of-two population distributes method composition frame chart rationally

Fig. 2 is scale-of-two population random particles coding figure

Fig. 3 is Binary Particle Swarm Optimization schema

Embodiment

Below, the invention will be further described for composition graphs 1, Fig. 2, Fig. 3.

A kind of satellite communications OFDM carrier wave collocation based on scale-of-two population, core thinking is as shown in Figure 1, unit is inputted from information code element, through channel encoding unit, string and convert unit, adaptive tracking control unit, Adaptive Modulation unit, IFFT unit, add circulation before suffix unit, low-pass filter unit, upconverting unit, enter satellite channel, complete OFDM transmission. Core introduces Binary Particle Swarm Optimization on the link, is used to guide adaptive tracking control unit and Adaptive Modulation cell operation.

Based on the satellite communications OFDM carrier wave collocation of scale-of-two population, Binary Particle Swarm Optimization is utilized on OFDM transmission system, it is optimized configuration, it is characterised in that specifically comprise the following steps: for adaptive tracking control unit and Adaptive Modulation unit

(1) according to the multiple goal parameter optimized in satellite OFDM carrier wave, multiple objective function is set up;

The mathematical expression formula of described multiple objective function f (x) is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\Σ}}{w}_i{f}_i$

Wherein, f_iIt is normalized to [0,1], w_iBeing the weight coefficient of i-th objective function, n is the number of target, W=[w₁,w_2,...,w_n],w_i��0,(1��i��m),Under given objective function and weight coefficient, self-adaptative adjustment parameter, makes total fitness reach maximum value, thus reaches the object of multiple-objection optimization. f_iIt is normalized to [0,1], w_iBeing the weight coefficient of i-th objective function, objective function is composed as follows in detail:

F (x)=w₁f_min-power+w₂f_min-ber+w₃f_{min-data-rate}

For different application scenes, different weight w is set_i, in (6) formula, w₁, w₂, w₃Embody in different application scene respectively, to the preference requirement of low-power consumption target, low bit error probability target, high data rate target.

(2), after setting up multiple objective function, binary particle swarm algorithm is utilized to set up a scale-of-two random particles group and random particles is carried out initialize; Wherein, random particles is made up of multiple goal parameter coding; Initialize comprise the position of random particles, speed, from Studying factors, society's Studying factors, inertia weight and iteration number of times;

As shown in Figure 2, one group of random particles quantity is M, wherein plans N number of subcarrier, and each subcarrier is made up of the coding of combinations of modulation and power combination, and carries out binary coding.

As shown in Figure 3, initialize speed:WhereinRepresent i-th particle, in kth time repeatedly, the speed of d dimension, initialized location: Represent the position of the d dimension of i-th particle, in the value that kth time iteration upgrades; From Studying factors it is: c₁, society's Studying factors is: c₂, inertia weight coefficient is: ��.

(3) fitness value of each random particles in scale-of-two random particles group is calculated by the multiple objective function of foundation, in order to judge the distance of each random particles position apart from globe optimum; Wherein, globe optimum is the most advantage of all particles by searching out after each binary particle swarm algorithm;

(4) according to the iterative formula of Position And Velocity of scale-of-two particle, upgrading the Position And Velocity of random particles, simultaneously every time in iteration, by following the tracks of, two extreme values upgrade oneself to each random particles; Two extreme values are the most advantage of individuality and globe optimum; Binary particle swarm algorithm often is used to solve complicated optimization problem, and more new formula is as follows for speed:

$v_{id}^{k+1}={\mathrm{\ωv}}_{id}^k+c_1{r}_1({\mathrm{pbest}}_{id}^k-x_{id}^k)+c_2{r}_2({\mathrm{gbest}}_{gd}^k-x_{id}^k)$

Wherein, ${\mathrm{pbest}}_i^k=\[p_{i1}^k,p_{i2}^k,...,p_{iD}^k\]$ With ${\mathrm{gbest}}_g^k=\[p_{g1}^k,p_{g2}^k,...,p_{gD}^k\]$ Being the most advantage of particle individuality and particle globe optimum respectively, particle upgrades the position of oneself by these two most advantages. r₁, r₂Being produce the equally distributed arithmetic number between [0,1] at random in scale-of-two situation, in particle, the position of each dimension is restricted to 0 or 1, speed can be successive value, speed value is transformed between [0,1] by available Sigmoid function, and its size represents the probability getting 1:

$Sigmoid\left(v_{id}^k\right)=\frac{1}{1+\exp (-v_{id}^k)}$

Location updating formula is as shown in (10) formula, and wherein �� is the randomized number belonging to [0,1],Value, if very big, illustrate that the probability getting 1 is bigger, on the contrary then get 0 probability bigger.

$x_{id}^{k+1}=\left\{\begin{array}{cc}1& \mathrm{\ρ}\≤Sigmoid\left(v_{id}^{k+1}\right)\\ 0& \mathrm{\ρ}>Sigmoid\left(v_{id}^{k+1}\right)\end{array}\right.$

(5) maximum iteration time of setting is judged whether to reach, if then proceeding to step (6); Otherwise, return step (3);

(6) value of globe optimum gbest is exported, as the configuration parameter of the OFDM carrier wave in satellite communication network;

Complete the satellite OFDM carrier wave based on scale-of-two population and distribute process rationally. Complete satellite to lead to

OFDM carrier wave in communication network distribute process rationally.

Claims (2)

1. based on the satellite OFDM carrier wave collocation of scale-of-two population, Binary Particle Swarm Optimization is utilized on OFDM transmission system, distribute rationally flexibly for adaptive tracking control and adaptive modulation system, it is characterised in that specifically comprise the following steps:

(1) according to the multiple goal parameter optimized in satellite OFDM carrier wave, multiple objective function is set up;

(2), after setting up multiple objective function, binary particle swarm algorithm is utilized to set up a scale-of-two random particles group and random particles is carried out initialize; Wherein, random particles is made up of multiple goal parameter coding; Initialize comprise the position of random particles, speed, from Studying factors, society's Studying factors, inertia weight and iteration number of times;

(3) fitness value of each random particles in scale-of-two random particles group is calculated by the multiple objective function of foundation, in order to judge the distance of each random particles position apart from globe optimum; Wherein, globe optimum is the most advantage of all particles by searching out after each binary particle swarm algorithm;

(4) according to the iterative formula of Position And Velocity of scale-of-two particle, upgrading the Position And Velocity of random particles, simultaneously every time in iteration, by following the tracks of, two extreme values upgrade oneself to each random particles; Two extreme values are the most advantage of individuality and globe optimum;

(5) maximum iteration time of setting is judged whether to reach, if then proceeding to step (6); Otherwise, return step (3);

(6) value of global point gbest is exported, as the configuration parameter of the OFDM carrier wave in satellite communication network;

Complete the satellite OFDM carrier wave based on scale-of-two population and distribute process rationally.

2. the satellite communications OFDM carrier wave collocation based on scale-of-two population according to claim 1, it is characterised in that: the mathematical expression formula of multiple objective function f (x) in step (2) is:

$f\left(x\right)=\underset{i=1}{\overset{n}{\Σ}}{w}_i{f}_i$

Wherein, f_iIt is normalized to [0,1], w_iIt is the weight coefficient of i-th objective function, W=[w₁,w_2,...,w_n],w_i��0,(1��i��m),N is the number of multiple goal.