33results about How to "Premium quality of experience" patented technology

The invention relates to a mobile edge computing Brent-type time delay optimization method based on non-orthogonal multiple access in a multi-base station scenario, comprising the following steps: (1)there is one mobile user in the coverage area of BSs of an integrated edge server, and the optimization problem is described as a multi-variable non-convex optimization problem; (2) decomposing the problem (DM i) into two levels of optimization problems; (3) According to the bottom DM-I-E-Sub problem, a split-search method based on Lagrange multiplier is proposed to optimize the overall delay ofmobile subscriber i under the condition of the transmission time ti of mobile subscriber i. (4) For top-level DM-I-E-Top problem, Brent method is proposed to optimize the transmission time ti of mobile subscriber i. (5) The problem (DM i) is solved by iteration of the bottom problem and the top problem. The invention improves the transmission efficiency of the system, saves bandwidth resources, and obtains higher quality wireless network experience quality.

The invention discloses a non-orthogonal multiple access based mobile edge computing linear search type time delay optimization method in multiple base station scenarios. The method comprises the following steps: (1) describing the optimized problem as a problem of multi-variable non-convex optimization when 1 mobile user exists under the coverage range of BSs of an integrated edge server; (2) resolving the problem (DM-i) into a problem of two-level optimization; (3) proposing a Lagrange multiplier method based bi-search method according to a bottom level DM-i-E-Sub problem, to optimize an overall time delay of the mobile user i in the case of the mobile user i with a transmission time t; (4) proposing a linear search method aiming at a top level DM-i-E-Top problem, to optimize the transmission time t of the mobile user i; (5) finally solving the problem (DM-i) through an interactive iteration of the bottom level problem and the top level problem. According to the non-orthogonalmultiple access based mobile edge computing linear search type time delay optimization method in multiple base station scenarios, the system transmission efficiency is improved, the bandwidth resources are saved, and a better wireless network experience is obtained.

The invention relates to a non-orthogonal access uplink transmission time optimization method based on deep reinforcement learning, which comprises the following steps: (1) there are I mobile users intotal under the coverage of a base station; while a service quality that satisfies a mobile user is proposed, the uplink transmission time of the mobile user and the total energy consumption of all users are minimized in the situation that the uploading amount formula of the mobile user is given; (2) the ORRCM problem is to find the optimal overall radio resource consumption in the case that theuploading amount formula of the mobile user is given; the ORRCM problem is observed, and it is learned that the objective function thereof has only one variable t; (3) the optimal uplink transmissiontime t* is obtained through a reinforcement learning algorithm, so that the optimal overall radio resource consumption is obtained; (4) the iterative process is repeated until the optimal uplink transmission time t* is obtained, so as to obtain the optimal overall radio resource consumption.

The invention discloses a non-orthogonal access downloading transmission time optimization method based on deep reinforced learning. The method comprises the steps as follows: 1, there is one mobile user in total under the coverage range of a base station, the downloading transmission time and overall energy consumption of the base station are minimized under the condition that the downloading amount of the mobile user is given; 2, the optimal downloading transmission time T* is found through reinforcing the learning algorithm, and thus the optimal downloading resource consumption is achieved;and 3, the iteration process is continuously repeated until the optimal downloading transmission time t* is acquired, and thus the optimal downloading resource consumption is achieved. The inventionprovides the non-orthogonal access downloading transmission time optimization method based on deep reinforced learning that minimizes the downloading transmission time and the overall energy consumption of the base station.

A computing task shunting joint execution time and computing resource consumption optimization method based on non-orthogonal multiple access comprises the following steps that (1) arranging an intelligent terminal is arranged in the coverage range of a cellular network base station integrated with an edge computing server, and describing an optimization problem is described as an SCM problem; (2)transforming an SCM problem twice into a problem SCM-E2, and decompsing the problem SCM-E2 into two sub-problems (3), proposing SubBiSec algorithm and TopLS algorithm respectively for solution; converting the SCM problem into a problem SCM-twice; e2, a problem SCM-is solved; (3) respectively proposing a Sub BiSec algorithm and a TopLS algorithm to solve the two sub-problems; (4) using the SubBiSec algorithm is used for solving the problem through the logarithmic search under the given t condition; and (5) enabling the TopLS algorithm carries to carry out enumeration on the t meeting the constraint condition, and calling the SubBiSec algorithm is called for each enumeration t to calculate the minimum value in the extraction. According to the invention, the system transmission efficiency is improved, the total cost of bandwidth resources and edge server computing resources is saved, and higher wireless network experience quality is obtained.

A non-orthogonal access uplink transmission time optimization method based on linear search comprises the following steps: (1) on the basis of a total of I mobile users under the coverage of the basestation, providing a problem that minimizes the uplink transmission time of the mobile users and the total energy consumption of all the mobile users while satisfying the service quality of the mobileusers, wherein the optimization problem is described as a non-convex optimization problem; (2) equivalently converting the ORRCM problem to the ORRCM-E problem; and (3) solving the algorithm ORRCM-Algorithm of the D1 problem, and proposing a D2 problem in order to judge whether the D1 problem is feasible under the given theta value; and based on the linear search method, optimizing the overall wireless resource consumption in the case that the upload volume (FORMULA referred) of the mobile users is given. The invention minimizes the uplink transmission time and the total energy consumption ofall the mobile users. The technical effects of the invention are mainly as follows: 1, for the uplink as a whole, the non-orthogonal access technology is used to greatly improve the system transmission efficiency; 2, for the uplink as a whole, the non-orthogonal access technology is used to greatly save bandwidth resources; and 3, for mobile users, the non-orthogonal access technology is used toobtain a better experience quality of the wireless network.

The present invention provides a non-orthogonal access optimal decoding ranking uplink transmission time optimization method based on bisearch. The method comprises the following steps of: (1) in a condition of giving decoding ranking [Pin]m, describing an optimization problem to a non-convexity optimization problem; (2) performing equivalent transformation of a (Pi-m) problem to a (P1-m-E) problem, and performing equivalent transformation of the (P1-m-E) problem to a (P2) problem, and proving a (P2-Sub) problem; (3) providing an algorithm P2-Algorithm based on bisearch, and optimizing the whole wireless resource consumption in a condition of giving an upload amount as shown in the description of an intelligent terminal; and (4) providing an algorithm OptOrder-Algorithm to find out an optimal decoding ranking, wherein an output result is global minimum whole wireless resource consumption and global optimal uplink transmission time. The non-orthogonal access optimal decoding ranking uplink transmission time optimization method improves the system transmission efficiency, saves the bandwidth resource and obtain better wireless network experience quality.

A non-orthogonal access downlink transmission time optimization method based on a depth deterministic policy gradient includes the following steps: (1) in the case that a total of I mobile users existin the coverage range of a base station, proposing a service quality that satisfies the mobile users, and minimizing the downlink transmission time of the base station and the total energy consumption of the base station in the case that the download amount formula (as shown in the original specification) of the mobile users is specified; (2) ensuring that a DDRCM problem is to find the optimal downlink resource consumption in the case that the download amount formula (as shown in the original specification) of the mobile users is specified, and observing the DDRCM problem to know that an objective function of the problem has only one variable t; (3) finding an optimal downlink transmission time t* through a depth deterministic policy method to ensure that the optimal downlink resource consumption (the downlink transmission time and the total energy consumption of the base station) exists; and (4) continuously repeating the iteration process until the optimal downlink transmission time t* is obtained, and further ensuring that the optimal downlink resource consumption exists. According to the scheme of the invention, the downlink transmission time and the total energy consumptionof the base station can be minimized.

A mobile edge computing time delay optimization method based on non-orthogonal multiple access and cellular network user cooperation comprises the following steps of:(1) enabling two edge computing users and one cellular network user to exist in the coverage range of a base station, arranging an edge server near the base station, and describing the optimization problem as an OLM problem; 2) decomposing the OLM problem into an OLM-Top problem and an OLM-Sub problem, and equivalently converting the OLM-Sub problem into OLM-Sub-E; 3) providing an OLM-Algyration hm algorithm to solve the OLM-Top problem; and 4) calculating an OLM-Sub-E problem by an OLM-Algyration hm algorithm on the premise of giving (t, m) and [gamma] to obtain a target function value of the OLM problem. The method improvesthe system transmission efficiency, saves bandwidth resources and the total cost of edge server computing resources, and obtains higher-quality wireless network experience quality.

The invention relates to a non-orthogonal access uplink transmission time optimization method based on binary search. The method comprises steps that (1), I mobile users in total are under the coverage range of a base station, in the case that the service quality of the mobile users is satisfied, the uplink transmission time of the mobile users and the total energy consumption of all the mobile users are minimized, and an optimization problem is described as a non-convex optimization problem; (2), an ORRCM problem is equivalently converted to an ORRCM-E problem; and (3), the ORRCM-E problem isequivalently converted to a D1 problem, whether the D1 problem is feasible under the given value theta is determined, and a D2 problem is proposed; based on the binary search method, overall wirelessresource consumption (the uplink transmission time and the total energy consumption of all the mobile users) is optimized under the given uploading amount ( an expression described as in the specification) of the mobile users. The uplink transmission time and the total energy consumption of all the mobile users are minimized. The method is mainly advantaged in that 1, for the uplink as a whole, system transmission efficiency is greatly improved through the non-orthogonal access technology; 2, for the uplink as a whole, bandwidth resources are greatly saved through the non-orthogonal access technology; and 3, for the mobile users, the better wireless network experience quality is obtained through the non-orthogonal access technology.

The invention discloses a multi-access calculation shunting method with safety guarantee based on simulated annealing. The method comprises the following steps: (1) considering a certain mobile user i, within K base station service ranges, each base station is provided with an edge computing server which can provide computing offloading service for the mobile user i, and the uplink transmission total energy of the mobile user is minimized while the service quality of the mobile user is met and the transmission information security of the user is ensured; (2) decomposing the problem TECM into two layers of optimization problems; (3) aiming at a bottom layer problem, applying a Lagrangian constant method, carrying out linear enumeration on an overflow probability, and optimizing the total energy consumption of the system; (4) according to the top layer problem, adopting a simulated annealing algorithm, and further optimizing the total energy consumption of the system; and (5) through interactive iteration of the bottom-layer problem and the top-layer problem, finally solving the problem TECM. The safety and the reliability are relatively high.

A non-orthogonal access uplink transmission time optimization method, comprising the following steps: (1) there are 1 mobile users in total under the coverage of the base station, a kind of QoS that satisfies the mobile users is proposed, while the mobile users upload The problem of minimizing the uplink transmission time of mobile users and the total energy consumption of all mobile users when the amount is given; (2) ORRCM problem is to find the optimal overall wireless resource consumption under the given amount of upload by mobile users; ( 3) Find an optimal uplink transmission time t through a deep deterministic strategy method * , so that there is an optimal overall wireless resource consumption; (4) Repeat the iterative process until the optimal uplink transmission time t is obtained * , so that there is an optimal overall radio resource consumption. The present invention minimizes uplink transmission time and total energy consumption of all mobile users.

A non-orthogonal access uplink transmission time optimization method based on a particle swarm optimization comprises the following steps: (1) on the basis of a total of I mobile users under the coverage of the base station, providing a problem that minimizes the uplink transmission time of the mobile users and the total energy consumption of all the mobile users while satisfying the service quality of the mobile users, wherein the optimization problem is described as a non-convex optimization problem; (2) equivalently converting the ORRCM problem to the ORRCM-E problem; and (3) based on the particle swarm optimization, optimizing the overall wireless resource consumption (uplink transmission time and total energy consumption of all mobile users) in the case that the upload volume (FORMULAreferred) of the mobile users is given. The invention provides a non-orthogonal access uplink transmission time optimization method based on a particle swarm optimization that minimizes the uplink transmission time and the total energy consumption of all the mobile users. The technical effects of the invention are mainly as follows: 1, for the uplink as a whole, the non-orthogonal access technology is used to greatly improve the system transmission efficiency; 2, for the uplink as a whole, the non-orthogonal access technology is used to greatly save bandwidth resources; and 3, for mobile users, the non-orthogonal access technology is used to obtain a better experience quality of the wireless network.

The invention provides a non-orthogonal access downlink transmission time optimization method based on a binary search mode. The method comprises the following steps: (1) there are I mobile users within the coverage of a base station in total, while the quality of service of the mobile users is met, a downlink transmission time of the base station and the total energy consumption of the base station are minimized in the case that the downloading amounts (the formula is described in the specification) of the mobile users are given, wherein the optimization problem is described as a non-convex optimization problem; (2) a DDRCM problem is equivalently converted into a DDRCM-E problem, and the DDRCM-E problem is equivalently converted into a P1 problem; and (3) in order to judge whether the P1problem is feasible under given theta value, a P2 problem is proposed; based on the binary search method, the downlink resource consumption (the downlink transmission time and the total energy consumption of the base station) is optimized in the case that the downloading amounts (the formula is described in the specification) of the mobile users are given. By adoption of the non-orthogonal accessdownlink transmission time optimization method provided by the invention, the downlink transmission time and the total energy consumption of the base station are minimized.

A non-orthogonal access optimal decoding sorting uplink transmission time optimization method based on linear search, comprising the following steps: (1) given a decoding sorting π m Under the condition of , the optimization problem is described as a non-convex optimization problem; (2) convert the (P1‑m) problem into a (P1‑m‑E) problem equivalently; It is a (P2) problem; a (P2‑Sub) problem is proposed; (3) an algorithm P2‑Algorithm based on linear search is proposed to optimize the overall wireless resource consumption when the upload volume of the smart terminal is given; (4) the algorithm OptOrder is proposed ‑Algorithm finds the optimal decoding order, and the output results are the global minimum overall wireless resource consumption and the global optimal uplink transmission time. The present invention improves system transmission efficiency, saves bandwidth resources, and obtains better wireless network experience quality.

The invention provides a non-orthogonal access optimal decoding sorting uplink transmission time optimization method based on the depth deterministic strategy gradient. The method comprises the following steps: (1) the optimization problem is described as a non-convex optimization problem under the condition of given decoding sorting pim; the (P1-M) problem is to find the optimal overall wirelessresource consumption under the condition of the given intelligent terminal upload (which is described in the specification), and the (P1-M) problem is observed to know that its objective function hasonly one variable; in the steps (2) and (3), the optimal uplink transmission time is searched through the deep deterministic strategy method so that there is the optimal overall wireless resource consumption; and (4) the algorithm OptOrder-Algorithm is utilized to find the optimal decoding sorting and the global minimum overall wireless resource consumption and the global optimal uplink transmission time are finally outputted through combination of the deep reinforcement learning algorithm. The system transmission efficiency can be enhanced, the higher-quality wireless network experience quality can be obtained and the optimal overall wireless resource consumption is enabled to be possible.

A non-orthogonal access downlink transmission time optimization method based on deep reinforcement learning, comprising the following steps: (1) There are a total of I mobile users under the coverage of the base station, and a QoS that satisfies the mobile users is proposed, Minimize the downlink transmission time of the base station and the total energy consumption of the base station when the download amount of the mobile user is given; (2) find an optimal downlink transmission time t through the reinforcement learning algorithm * , so that there is an optimal downlink resource consumption; (3) Repeat the iterative process until the optimal downlink transmission time t is obtained * , so that there is optimal downlink resource consumption. The present invention provides a non-orthogonal access downlink transmission time optimization method based on deep reinforcement learning that minimizes downlink transmission time and total energy consumption of a base station.

The invention discloses a non-orthogonal access downloading-duration transmission time optimization method based on linear search. The method comprises the following steps that (1), totally I mobile users exist in a coverage range of a base station, an optimization problem of minimizing the downloading-duration transmission time of the base station and the total energy consumption of the base station is provided under the condition that the service of quality of the mobile users is satisfied and the downloading quantity {S <req> } of the mobile users is preset, wherein the I is an elementof a set J, and the optimization problem is described as a non-convex optimization problem; (2), a DDRCM (Downloading-Duration Resource Consumption Minimization) problem is equivalently converted intoa DDRCM-E problem, and the DDRCM-E problem is equivalently converted into a P1 problem; and (3), in order to judge whether the P1 problem is feasible or not under the condition that a theta value ispreset, a P2 problem is provided, and on the basis of the linear search method, and under the condition that the downloading quantity {S <req> } of the mobile users is preset, the downloading-duration resource consumption is optimized, wherein the I is the element of the set J. According to the method, the downloading-duration transmission time and the total energy consumption of the base station are minimized.

A non-orthogonal access optimal decoding sorting uplink transmission time optimization method based on deep deterministic policy gradient, including the following steps: (1) in a given decoding sorting π m Under the condition of , the optimization problem is described as a non-convex optimization problem; the (P1‑m) problem is to find the optimal overall wireless resource consumption in the case of a given intelligent terminal upload volume, and the observation (P1‑m) problem knows its The objective function has only one variable; (2) and (3) use the deep deterministic strategy method to find the optimal uplink transmission time, so that there is an optimal overall wireless resource consumption; (4) use the algorithm OptOrder-Algorithm to find the optimal Decoding and sorting, combined with a deep reinforcement learning algorithm, finally outputs the global minimum overall wireless resource consumption and the global optimal uplink transmission time. The present invention improves system transmission efficiency, obtains better wireless network experience quality, and enables optimal overall wireless resource consumption.

A non-orthogonal access downlink transmission time optimization method based on a linear search formula, comprising the following steps: (1) there are 1 mobile users in total under the coverage of the base station, and a QoS that satisfies the mobile users is proposed, Minimize the downlink transmission time of the base station and the total energy consumption of the base station when the download amount of the mobile user is given; among them, the optimization problem is described as a non-convex optimization problem; (2) The DDRCM problem is equivalently transformed into DDRCM‑E problem, the DDRCM‑E problem is equivalently transformed into a P1 problem; (3) In order to judge whether the P1 problem is feasible under the given value of θ, a P2 problem is proposed; based on the linear search method, when the download volume of mobile users is given Downlink resource consumption is optimized. The invention minimizes the downlink transmission time and the total energy consumption of the base station.

A non-orthogonal multiple access-based computing task offloading joint execution time and computing resource consumption optimization method, comprising the following steps: (1) There is an intelligent terminal under the coverage of a cellular network base station integrating an edge computing server, the optimization problem Described as an SCM problem; (2) Transform the SCM problem twice into the problem SCM‑E2, and decompose the problem SCM‑E2 into two sub-problems (3) Propose the SubBiSec algorithm and the TopLS algorithm to solve it respectively; (4) SubBiSec The algorithm solves the problem by bisection search θ under the condition of given t; (5) The TopLS algorithm enumerates t that meets the constraint conditions, and calls the SubBiSec algorithm to calculate the minimum value for each enumeration t . The present invention improves system transmission efficiency, saves bandwidth resources and the total cost of edge server computing resources, and obtains better wireless network experience quality.

A non-orthogonal access uplink transmission time optimization method based on the particle swarm optimization algorithm, comprising the following steps: (1) there are 1 mobile users in total under the coverage of the base station, and at the same time a quality of service that satisfies the mobile users is proposed, Minimize the uplink transmission time of mobile users and the total energy consumption of all mobile users. Among them, the optimization problem is described as a non-convex optimization problem; (2) the ORRCM problem is equivalently transformed into an ORRCM-E problem; (3) Based on the particle swarm optimization algorithm, the overall wireless network is optimized when the upload volume of mobile users is given. Resource consumption (uplink transmission time and total energy consumption of all mobile users). The invention provides a non-orthogonal access uplink transmission time optimization method based on particle swarm algorithm which minimizes uplink transmission time and total energy consumption of all mobile users. The technical effects of the present invention are mainly manifested in: 1. For the overall uplink, the use of non-orthogonal access technology greatly improves the system transmission efficiency; 2. For the overall uplink, the use of non-orthogonal access technology greatly saves bandwidth resources ; 3. For mobile users, better wireless network experience quality can be obtained through non-orthogonal access technology.

A non-orthogonal access optimal decoding sorting uplink transmission time optimization method based on deep reinforcement learning, including the following steps: (1) given a decoding sorting π m Under the condition of , the optimization problem is described as a non-convex optimization problem; the (P1‑m) problem is to find the optimal overall wireless resource consumption in the case of a given intelligent terminal upload capacity, and the observation (P1‑m) problem knows that The objective function has only one variable; (2) and (3) find an optimal uplink transmission time through the deep reinforcement learning algorithm, so that there is an optimal overall wireless resource consumption; (4) propose the algorithm OptOrder‑Algorithm to find the optimal Decoding and sorting, combined with a deep reinforcement learning algorithm, outputs the global minimum overall wireless resource consumption and the global optimal uplink transmission time. The present invention improves system transmission efficiency, obtains better wireless network experience quality, and enables optimal overall wireless resource consumption.

A non-orthogonal access uplink transmission time optimization method based on a binary search formula, comprising the following steps: (1) There are 1 mobile users in total under the coverage of the base station, and a method that satisfies the quality of service of the mobile users and simultaneously , to minimize the uplink transmission time of mobile users and the total energy consumption of all mobile users. Among them, the optimization problem is described as a non-convex optimization problem; (2) the ORRCM problem is equivalently transformed into the ORRCM‑E problem; (3) the ORRCM‑E problem is equivalently transformed into a D1 problem; Whether the D1 problem is feasible under the conditions, and the D2 problem is proposed; based on the binary search method, the overall wireless resource consumption (uplink transmission time and total energy consumption of all mobile users) is optimized when the upload amount of mobile users is given. The present invention minimizes uplink transmission time and total energy consumption of all users. The technical effects of the present invention are mainly manifested in: 1. For the overall uplink, the use of non-orthogonal access technology greatly improves the system transmission efficiency; 2. For the overall uplink, the use of non-orthogonal access technology greatly saves bandwidth resources ; 3. For mobile users, better wireless network experience quality can be obtained through non-orthogonal access technology.

A non-orthogonal access downlink transmission time optimization method based on deep deterministic policy gradients, comprising the following steps: (1) There are a total of I mobile users under the coverage of the base station, and a quality of service that satisfies the mobile users is proposed At the same time, the downlink transmission time of the base station and the total energy consumption of the base station are minimized when the download amount of the mobile user is given; (2) the DDRCM problem is to find the optimal downlink resource consumption when the download amount of the mobile user is given, Observe the DDRCM problem and know that its objective function has only one variable t; (3) Find an optimal downlink transmission time t through a deep deterministic strategy method * , so that there is an optimal downlink resource consumption (downlink transmission time and total energy consumption of the base station); (4) Repeat the iterative process until the optimal downlink transmission time t is obtained * , so that there is optimal downlink resource consumption. The invention minimizes the downlink transmission time and the total energy consumption of the base station.