JP-7855717-B2 - A method for optimizing frequency allocation to cells in a mobile communication network.

JP7855717B2JP 7855717 B2JP7855717 B2JP 7855717B2JP-7855717-B2

Inventors

ゲイツ，マルク
ホルシュケ，オリヴァー
クリザン，クリスティーネ
ミュンヒ，クリスティアン
シンケル，フリッツ
エンゲル，セバスティアン

Assignees

フジツウテクノロジーソリューションズゲーエムベーハー
ドイチェテレコムアーゲー

Dates

Publication Date: 20260508
Application Date: 20230404
Priority Date: 20220412

Claims (14)

A computer-implemented method for optimizing the allocation of frequencies to cells in a mobile communications network, wherein the cells are distributed for communication within the mobile communications network, and the method is: The steps include: specifying a set of unplanned cells in the aforementioned mobile communication network; For each unplanned cell, the step is to specify the set of frequencies that are potentially allocated to that unplanned cell; A step of calculating the frequency interference probability of selected cell pairs, wherein each cell pair defines the relationship between an unplanned cell and another cell in the mobile communication network; The step of formulating terms of the stress function, wherein each term relates the calculated frequency interference probability of each cell pair to the frequency relationship between the cells of that cell pair; The process includes the step of determining an optimized frequency assignment by using a quantum-inspired processor, which involves selecting a subset of frequencies from the respective sets of frequencies for each unplanned cell such that the stress function is minimized, The method in question is: A step of specifying frequency variables, each frequency variable being associated with a cell in the mobile communication network and a frequency of that cell; The steps include: formulating the frequency relationship in the stress function term as a combination of selected frequency variables; The further step of using the quantum-inspired processor to calculate the terms of the stress function and set the frequency variable such that the stress function is minimized, method .
The method according to claim 1, wherein in the stress function term, only calculated frequency interference probabilities below a predetermined threshold are considered.
The method according to claim 1, wherein the method is performed considering a frequency demand condition that each subset of frequencies allocated to an unplanned cell has a specified number of frequencies, one frequency defined as a control channel frequency and the other frequencies defined as traffic channel frequencies.
The method according to claim 1, wherein the method is performed considering a frequency combination distance condition such that, for each unplanned cell, a forbidden frequency relationship is defined such that the frequencies of the subset of frequencies assigned to that cell have a frequency relationship with a certain channel distance.
The method according to claim 1, wherein the method is performed considering a cell neighborhood condition in which a prohibited frequency relationship is defined between cells having a determined neighborhood relationship.
The method according to claim 1, wherein the method is performed considering a frequency interference probability condition in which a forbidden frequency relationship is defined between cells of a cell pair whose frequency interference probability exceeds a predetermined threshold.
The aforementioned frequency relationships distinguish between same-channel frequency relationships and adjacent-channel frequency relationships. The same-channel frequency relationship is formulated for the frequencies of the same channel, and the adjacent-channel frequency relationship is formulated for the frequencies of adjacent channels. The method according to claim 1.
The method according to claim 1, wherein the frequency relationship distinguishes between the control channel frequency and the traffic channel frequency.
A step of specifying frequency variables, each frequency variable being associated with a cell in the mobile communication network and a frequency for that cell; The steps are: formulating the frequency relationships of each condition as terms of the selected frequency variable; The quantum-inspired processor further includes the steps of calculating the frequency relationships of each condition and setting the frequency variables such that each frequency relationship becomes zero. The method according to claim 4 .
The calculated frequency interference probability for each cell pair distinguishes between same-channel frequency interference probability and adjacent-channel frequency interference probability. The same-channel frequency interference probability is calculated for the frequencies of the same channel between the cells of each cell pair, and the adjacent-channel frequency interference probability is calculated for the frequencies of the adjacent channels between the cells of each cell pair. The method according to claim 1.
The steps include: specifying a subset of unplanned cells from the aforementioned set of unplanned cells; The steps include: performing the method with respect to the subset of unplanned cells; The steps include updating the cells in the subset to planned cells with determined optimized frequency assignments; The further step includes sequentially iterating the method for the remaining unplanned cells in the set of unplanned cells until all unplanned cells in the set of unplanned cells have been processed. The method according to claim 1.
A quantum-inspired processor, particularly a digital annealing unit or a quantum annealing unit, configured to perform the steps of the method described in claim 1.
A computer program having instructions, wherein, when the program is executed by one or more processors, the instructions cause each of the one or more processors to execute the method described in claim 1.
An interface device comprising one or more interfaces to cells of a mobile communications network, wherein the cells are distributed for communication within the mobile communications network, and the interface device is configured to automatically deploy an optimized frequency allocation determined by the method described in claim 1 to the cells of the mobile communications network.

Description

This invention relates to a computer-implemented method for optimizing the allocation of frequencies to cells in a mobile communications network, where cells are distributed for communication within the network. The invention also relates to a quantum-inspired processor configured to perform such a method, as well as a computer program implemented to perform such a method. Communication demands related to traffic on mobile communication networks are constantly increasing. A growing number of devices and applications are pushing mobile communications to new peaks. Furthermore, the increasing demand for digitized and decentralized mobile work, as well as the rise in streaming demand, are other major factors contributing to this trend. The increasing demand for network capacity, coupled with the growing volume of data transported through mobile communication networks, presents significant challenges for service providers. Mobile communication networks, particularly mobile phone networks, such as 2G networks like GSM® or TETRA, include a topology of distributed “cells” for transmitting, receiving, and forwarding mobile communication traffic and control data within the network via radio frequency communication. Each cell acts as a mobile communication node covering a certain area for the mobile communication network, thereby using one or more communication frequencies. Mobile communication participants, such as cell phones and other cellular or wireless communication devices, connect to their respective cells for mobile communication with other participants in the communication network. Depending on the location and characteristics of the cell's surroundings (e.g., urban or rural area), and the number and density of participating devices, cells have different sets of frequencies allocated to them to ensure they can handle the volume and amount of communication traffic. Frequencies are used for data or conversation transmission, control channels, etc. Therefore, to avoid congestion and degradation of the user experience in mobile communication networks, mobile phone providers are interested in making the best possible use of the available frequency spectrum. The capacity of a mobile communication network can be increased by densely allocating frequencies from the mobile network operator's frequency spectrum to cells. However, this can have the drawback of neighboring cell frequencies exceeding the required distance requirements. For example, if neighboring or related cells have frequencies equal or adjacent in the frequency spectrum, they will interfere with each other. This can lead to signal interference, degradation of communication quality, or communication failure. One possible solution to the frequency allocation problem in cellular communication networks involves a two-step approach. The first step involves a preliminary allocation based on conditions that must be met (hard constraints), such as conditions for neighboring cells. The second step consists of sequential, iterative brute-force local optimization of unsaturated cells. For each such cell, the ring of directly neighboring cells is replanned. If a satisfactory solution is not found, the procedure can be repeated from the first step of ring generation using a wider ring, which is the union of all cells from the ring of directly adjacent cells. This ring-based cell acquisition procedure can be performed recursively. However, such conventional approaches have drawbacks: local optimization in unsaturated cells exacerbates interference in other cells within the network, or even leads to certain cells not being allocated the required number of frequencies or only being allocated insufficiently. Furthermore, such conventional approaches have the drawback that the optimization techniques applied so far rapidly reach their limits. The present invention will be further described below with reference to several drawings and with consideration to several implementations. This shows an exemplary configuration of a communication network having multiple cells. Figure 1 shows an example of frequency allocation to one cell in the network. Figure a shows an exemplary schematic diagram of cell neighborhood conditions between exemplary pairs of cells in the network according to Figure 1. Figure b shows an exemplary schematic diagram of cell sector conditions between exemplary cells in the network according to Figure 1. Figure 1 shows an illustrative schematic diagram of the frequency interference probability conditions between exemplary pairs of network cells. This section presents an exemplary mathematical formulation of a partial optimization problem. This section presents an exemplary mathematical formulation of a partial optimization problem. This section presents an exemplary mathematical formulation of a partial optimization problem. This section presents an exemplary mathematical formulation of a partial optimization problem. This section presents an exemplary