The invention discloses a heterogeneous network pre-switching method based on mobile prediction, belonging to the technical field of mobile communication. The invention discloses the heterogeneous network pre-switching method based on mobile prediction, which is characterized by determining the coordinates of a mobile terminal at the network switch time through predicating the speed of the mobile terminal, and calculating the pre-switching threshold value, thus the threshold value calculation mode is improved. The heterogeneous network pre-switching method based on mobile prediction provided by the invention has the beneficial effects that the mobile distance of the terminal is predicated through a mobile predication algorithm in the pre-switching process, the pre-switching threshold value is calculated more accurately, thus the packet loss rate of the terminal in the switching process is reduced, and the resource utilization ratio of the current network is improved.

Heterogeneous network pre-switching method based on mobile prediction

Method, apparatus, and system for switching

The invention discloses a maximizing and speed rate pre-coding method for a simultaneous wireless information and power transfer system. The maximizing and speed rate pre-coding method for the simultaneous wireless information and power transfer system includes that acquiring all the channel state information through a base station, and building an optimizing model aimed to optimize information users and speed rate. The operation for the iterative optimization of pre-coding matrix includes steps that (1) initializing, to be specific, converting a target function into a convex function through first approximation, wherein at the moment, the information user maximization and speed rate problem is a convex problem under the constraints of sending power and energy user receiving power; setting a sending signal covariance matrix as a zero matrix to solve the problem; (2) iterating, to be specific, substituting the sending signal covariance matrix obtained through solving the optimization problem into the target function, and continuing to solve till realizing information user and speed rate convergence. The theory proves that the maximizing and speed rate pre-coding method for the simultaneous wireless information and power transfer system is globally optimal in performance, compared with an existing method, the maximizing and speed rate pre-coding method for the simultaneous wireless information and power transfer system converts the problem into the convex problem through gradual convex approximation to solve. By means of the pre-coding method, the information user and speed rate of the simultaneous wireless information and power transfer system can be effectively improved.

Maximizing and speed rate pre-coding method for simultaneous wireless information and power transfer system

The invention discloses configuring method and device for handover parameters. The configuring method includes determining TTT (time-to-trigger) value of a cell according to a change characteristic of difference between RSRP (reference signal receiving power) of an abnormal cell and that of a source cell measured by UE (user equipment) before handover is launched by the UE in an abnormal scene handover area,; launching a probability model according to the determined TTT value and handover, adjusting K coefficient and CIO (cell individual offset) of the abnormal cell, replacing handover parameter combinations among normal cells, and allowing handover performance among the normal cells to be equal to original configuration. By the use of the configuring method and device for handover parameters, handover robustness and effectiveness can be guaranteed, and handover failure times of the cells are reduced.

Configuring method and device for handover parameters

The invention discloses a low-complexity precoding method, combining a CG (conjugate gradient) method and a JC method (Jacobi iterative method), for a large-scale multi-antenna system, and belongs to the technical field of wireless communication. The method mainly comprises four steps: firstly employing a diagonal approximate initial solution, and improving the rate of convergence; secondly employing the CG method with the characteristics of rapid convergence for two times, so as to provide a precise searching direction for the subsequent low-complexity JC iteration; thirdly employing a mixed iteration idea, the principles of the CG method and the results of the CG methods of the former two times to reduce the complexity of first JC iteration; and finally completing a subsequent iteration process through employing the JC iteration. Compared with a conventional approximate matrix inversion method for the precoding of the large-scale multi-antenna system, the method is higher in convergence speed, and can obtain a lower system error rate through a smaller number of iteration times and lower complexity.

Low-complexity precoding method for large-scale multi-antenna system

Method for selecting handover trigger time of user based on auto-regressive (AR) model prediction

The invention discloses an MIMO (multiple input multiple output) interference alignment algorithm based on a Stiefel manifold upper conjugate gradient method, mainly aiming at solving the problem that the traditional interference alignment method cannot well improve the overall rate of a network. The method concretely comprises the steps of (1) initializing a precoding matrix Vl (l=1, L, K) at a user transmission terminal; (2) building an optimal object with the maximal speed; (3) working out decoding matrix Uk (k=1, L, K); (4) after the decoding matrix Uk is obtained, acquiring the precoding matrix Vl; (5) enabling the steps (3) and (4) to be carried out in a circulating way till convergence or maximum iterations. After the MIMO interference alignment algorithm is used, the overall rate of the network can be better improved; the MIMO interference alignment algorithm is used for the interference alignment coding design of users in the MIMO network environment, and can also be used for the precoding design for inhibiting the interference of the master user and the secondary user in cognitive radio.

MIMO (multiple input multiple output) interference alignment algorithm based on Stiefel manifold upper conjugate gradient method

The invention discloses a channel estimation error network-based robustness beam forming design method, so that a problem that an uncertainty model can not carry out solving easily when a useful channel and an interference channel coexist can be solved Particularly, the method comprises the following steps: (1), initializing a to-be-designed user beam vector correlation matrix Q1 and constructing an optimization target equation with the highest rate; (2), converting the target equation into step-by-step iteration subproblems; (3), solving each subproblem; (4), carrying out the steps (2) and (3) by a cyclic way until obtaining an optimum correlation matrix Q1; and (5) carrying out decomposition on the optimum Q1 by using a rank one so as to obtain an optimum beam vector v1 According to the invention, self adaption of a channel state error can be realized; and the user rate can be effectively improved The method can be used for the design of transmitting terminal robustness beam forming under the circumstances that the channel estimation error and the interference coexist and for the design of a multi-user multi-input single-output (MISO) system robustness beam under the circumstances that an estimation error exists in a channel state

Channel estimation error network-based robustness beam forming design method

The invention discloses a multi-cell interference alignment algorithm based on interference suppression and capacity improvement and mainly solves the problem that a traditional interference alignment method can not improve the over-all speed of a network greatly The algorithm comprises the specific procedures of 1, initializing a pre-coding matrix V [l] (l=1, , L) of a base station in a cell; 2, establishing an optimization objective with the maximum speed, and obtaining a decoding matrix U [lk] (l=1, , L, k=1, , K); 3, after obtaining the decoding matrix U [lk], obtaining the pre-coding matrix V [l]; 4, repeating the step 2 and the step 3 circularly until convergence or the maximum iterations are achieved By means of the algorithm, the over-all speed of the network can be improved greatly, and the algorithm can be used for the design of a multi-cell interference alignment transmitter-receiver as well as the design of the transmitter-receiver of multiple-input-multiple-output communication system interference alignment

Multi-cell interference alignment algorithm based on interference suppression and capacity improvement

Method for configuring independent resources based on resource flow

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