12 results about "Geometric programming" patented technology

Disclosed in the present invention is a power allocation method based on a cell-free massive MIMO short-packet communication system. The method comprises: on the basis of a Rayleigh fading channel model under channel aging, deriving an expression for a downlink achievable rate of a cell-free massive MIMO short-packet communication system under user mobility; with the goal of maximizing a minimum user rate, proposing a downlink power allocation method; and on the basis of a successive convex approximation method and geometric programming, performing iterative solving, wherein an obtained solution is used as a final power allocation result for calculating the rate of each user. The present invention maximizes a minimum user achievable rate of users in a system, effectively solves the problem of uneven quality of service for the users, enhances system fairness, and also has a relatively high convergence rate.

The invention provides a parking path planning method. The method comprises the following steps: step 1, acquiring parking path planning information; 2, correcting the target position to obtain a corrected target position; step 3, planning a first section of parking path based on a mixed A star algorithm; 4, planning a second section of parking path based on a geometric programming algorithm; and 5, based on the first section of parking path and the second section of parking path, the vehicle is controlled to be parked. According to the method, the planning success rate can be ensured, and the overall planning efficiency can be improved.

The invention discloses a downlink spectrum efficiency and energy efficiency joint optimization method for a cellular-removed large-scale MIMO system, and the method mainly comprises the steps: obtaining an expression of downlink spectrum efficiency and energy efficiency of the system based on the cellular-removed large-scale MIMO system, and defining an expression of resource efficiency; according to the method, a resource efficiency maximization optimization problem is established, then a continuous convex approximation technology is utilized to convert an original problem into standard geometric programming, finally, an obtained geometric programming problem is solved based on golden search method iteration, and an optimal downlink transmission power distribution scheme is obtained. According to the invention, the downlink transmission power is optimized by using the channel statistical information, the spectrum efficiency and the energy efficiency of the decellular large-scale MIMO system are improved at the same time, the compromise between the spectrum efficiency and the energy efficiency is effectively realized, and the utilization rate of wireless resources in the decellular large-scale MIMO system is improved.

The invention relates to a parking control method and device, a vehicle and a storage medium, and the method comprises the steps: when the vehicle needs to be parked to an end parking space and the vehicle runs to a parking point of the end parking space, determining a target region for enabling the vehicle to turn around outside the end parking space, and carrying out the parking control of the vehicle on the basis of the parking point and the target region; the method comprises the following steps: determining a U-turn path set corresponding to a vehicle by using a geometric programming algorithm, and determining a target U-turn path corresponding to the vehicle from the U-turn path set, thereby controlling the vehicle to run from a parking point to a target parking point according to the target U-turn path so as to complete the U-turn of the vehicle; and determining a target parking path corresponding to the vehicle by using an A star algorithm, and controlling the vehicle to drive into the end parking space from the target parking point according to the target parking path to complete parking of the vehicle. The problem that the parking time is long due to the fact that the vehicle is parked in the end parking space only through the A star algorithm is solved, and the driving experience of a user is improved.

The invention discloses a pre-training visual language model-based cross-country scene unmanned vehicle auxiliary decision-making method, and belongs to the technical field of unmanned driving. Comprising the following steps: constructing a simulation data set for training a three-dimensional target detection network; carrying out cross-modal consistency fusion and cue word design; and generating and mapping driver element actions and decisions. According to the invention, by fusing a three-dimensional target detection network and a pre-trained visual language model, introducing a thinking chain type reasoning and selective spatial information injection mechanism, and combining a trigger type reasoning process and meta-action sequence generation, high-level understanding and auxiliary decision making of a cross-country scene are realized; therefore, the defects of a traditional geometric programming algorithm in an unstructured environment are overcome.

The invention discloses an energy efficiency optimization method for an active RIS auxiliary cell-free mMIMO system, and the method comprises the steps: firstly, building a downlink transmission data and system consumption total power model of the active RIS auxiliary cell-free mMIMO system, and giving a downlink rate and energy efficiency expression; then, designing a communication node downlink transmission power allocation scheme by formulating a multi-objective function optimization problem, including maximizing a downlink rate and minimizing the total consumed power of the system; in order to solve the non-convex optimization problem, a weighted sum method and an arithmetic mean inequality are used for converting the non-convex optimization problem into a generalized geometric programming problem, and then an iteration mode is adopted for solving the non-convex optimization problem; and finally, taking the obtained optimal solution as a final power distribution scheme and calculating the energy efficiency of the system. According to the method, the total power consumed by the system is reduced while the downlink rate sum is improved, the energy efficiency of the system is improved, and the operation cost of the system is reduced.

The application relates to a parking control method and device, a vehicle and a storage medium. The method comprises the following steps: when a vehicle needs to be parked in an end head parking space and the vehicle drives to a parking point of the end head parking space, a target area for realizing the U-turn of the vehicle outside the end head parking space is determined, a corresponding U-turn path set of the vehicle is determined by using a geometric programming algorithm based on the parking point and the target area, a target U-turn path corresponding to the vehicle is determined from the U-turn path set, the vehicle is controlled to drive from the parking point to a target parking-in point according to the target U-turn path, so that the U-turn of the vehicle is completed, and then a target storage path corresponding to the vehicle is determined by using an A-star algorithm based on the target parking-in point, the vehicle is controlled to drive from the target parking-in point to the end head parking space according to the target storage path, and the parking of the vehicle is completed. The application avoids the problem that the parking time is relatively long when the vehicle is parked in the end head parking space only by using the A-star algorithm, and improves the driving experience of the user.

The invention relates to a lateral parking method and device, electronic equipment and a storage medium. The method comprises the steps that parking state information of a to-be-parked vehicle is acquired; according to the position information of the vehicle and the position information of the parking space, determining a plurality of parking paths by using a geometric programming algorithm; determining a target parking path from the parking paths according to the obstacle position information; and according to the target parking path, the vehicle is controlled to be parked in the side direction. According to the method, a plurality of parking paths can be determined by using a geometric programming algorithm according to the position information of the vehicle and the position information of the parking space, and then the target parking path is determined from the parking paths according to the position information of the obstacle, so that the vehicle is controlled to be parked in the side direction according to the target parking path. The parking path is determined through the three-section path of the first arc, the straight line and the second arc, so that the parking requirement in a complex scene is met, the method is not limited to a standard parking lot, and the application range of the automatic parking function is widened.

Disclosed in the present invention is a power allocation method based on a cell-free massive MIMO short-packet communication system. The method comprises: on the basis of a Rayleigh fading channel model under channel aging, deriving an expression for a downlink achievable rate of a cell-free massive MIMO short-packet communication system under user mobility; with the goal of maximizing a minimum user rate, proposing a downlink power allocation method; and on the basis of a successive convex approximation method and geometric programming, performing iterative solving, wherein an obtained solution is used as a final power allocation result for calculating the rate of each user. The present invention maximizes a minimum user achievable rate of users in a system, effectively solves the problem of uneven quality of service for the users, enhances system fairness, and also has a relatively high convergence rate.

This application discloses a method and apparatus for cooperative containment guidance of aircraft, relating to the field of aircraft guidance and control. The method includes acquiring the position, velocity, heading angle, interception time, navigation ratio of the pursuing aircraft, position, velocity, heading angle of the defending aircraft, target position, and target heading angle of the pursuing aircraft; determining the coordinates of the containment point using a geometric programming method; and controlling the target and the defending aircraft using a cooperative guidance method based on the coordinates of the containment point, the navigation ratio of the pursuing aircraft, the position, velocity, heading angle of the pursuing aircraft, the position, velocity, heading angle of the defending aircraft, the target position, and the target heading angle of the defending aircraft, thereby achieving cooperative containment of the pursuing aircraft. This application improves the effectiveness of the cooperative containment guidance strategy and the interception efficiency of the pursuing aircraft.

The application discloses an active RIS-assisted cell-free mMIMO system energy efficiency optimization method, first, the downlink transmission data and system total power consumption model of the active RIS-assisted cell-free mMIMO system is established, and the downlink rate and energy efficiency expression is given; then, by formulating a multi-objective function optimization problem, including maximizing the downlink rate and minimizing the total system power consumption, a communication node downlink transmission power allocation scheme is designed; in order to solve the non-convex optimization problem, the weighted sum method and the arithmetic average inequality are used to convert it into a generalized geometric programming problem, and then an iterative method is used for solving; finally, the obtained optimal solution is used as the final power allocation scheme and the system energy efficiency is calculated, the application reduces the total system power consumption while improving the downlink rate and, improves the system energy efficiency, and reduces the system operation cost.

This invention investigates the offline one-dimensional resource allocation problem of maximizing the utility of a convex increasing function system within a given time frame, under both energy causality (hard) and energy saturation (soft) constraints. Utilizing the Karush-Kuhn-Tucher condition, a modified tunneling strategy based on geometric programming is proposed, considering only causal hard constraints and saturation soft constraints. A computational method for allocating energy to various time slots is presented. This method is particularly advantageous when the geometric allocation line simultaneously encounters either the upper or lower edge of the energy constraint. This invention solves the energy allocation problem of maximizing the utility of an increasing convex function system under causal hard constraints and saturation soft constraints.