IP Library › Granted Patent US 12,745,097
Granted Patent B2
US 12,745,097 · App. 18/020,640 · Granted Sep 22, 2026

Method and system for design planning of a cellular network

Inventors: Antonio Albanese (Heidelberg, DE); Vincenzo Sciancalepore (Heidelberg, DE); Xavier Costa-Perez (Heidelberg, DE)
Assignee: NEC LABORATORIES EUROPE GMBH
H04W16/18H04W24/02
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Quick Facts
Patent No.
US 12,745,097
App. No.
18/020,640
Granted
Sep 22, 2026
Kind
B2
Abstract

A computer-implemented method is provided for optimizing positioning performance of a cellular network. The method includes: defining a target area; identifying a set(S) of base station deployment candidate sites (j) within the target area; obtaining, by executing a joint performance optimization routine that jointly optimizes network throughput and positioning performance, wherein a tuning parameter regulates a throughput-positioning ratio of the joint performance optimization routine, active candidate sites as a subset of the set(S) of base station deployment candidate sites (j); and determining the obtained active candidate sites as the sites at which base stations are to be deployed.

Claims (40)

1 . A computer-implemented method for optimizing positioning performance of a cellular network, the method comprising:

defining a target area;

identifying a set(S) of base station deployment candidate sites (j) within the target area;

obtaining, by executing a joint throughput-positioning radio planning problem formulated as a single max-min problem that uses a tuning parameter that regulates a throughput-positioning ratio for jointly optimizing network throughput and positioning performance, active candidate sites as a subset of the set(S) of base station deployment candidate sites (j), wherein the joint throughput-positioning radio planning problem takes as input the tuning parameter and the set(S) of the base station deployment candidate sites (j) and iteratively repeats until a convergence is reached that maximizes minimum network throughput experienced at test points (t) that sample the target area and minimizes a maximum position error bound (PEB) experienced at the test points (t), wherein the tuning parameter is a scalar factor that trades off between the network throughput and the positioning performance within the target area; and

determining the obtained active candidate sites as the sites at which base stations are to be deployed.

2 . The method according to claim 1 , wherein executing the joint throughput-positioning radio planning problem includes:

specifying a set (T) of the test points (t) that sample the target area; and

implementing decision variables x j ∈ {0,1} and a tj ∈ {0,1}, wherein x j indicates whether a base station is deployed at a candidate site, and wherein a tj indicates the maximum Signal-to-Noise-and-Interference-Ratio (SINR) association between a user experience (UE) at a test point and the candidate site.

3 . The method according to claim 2 , wherein a distribution of the test points (t) within the target area matches an expected distribution of cellular users within the target area.

4 . The method according to claim 1 , wherein the set(S) of base station deployment candidate sites (j) is derived from a pre-negotiation phase between operators and third parties in consideration of logistical and/or administrative constraints; or

wherein the set(S) of base station deployment candidate sites (j) is determined to be a superset of sites where LTE base stations have already been deployed; or

wherein the set(S) of base station deployment candidate sites (j) is determined as some random sampling of the target area.

5 . The method according to claim 1 , wherein executing the joint throughput-positioning radio planning problem determines a balance among the test points (t), with respect to the network throughput and positioning performance.

6 . The method according to claim 5 , wherein an objective function of the joint throughput-positioning radio planning problem contains the tuning parameter that regulates the throughput-positioning ratio.

7 . The method according to claim 1 , wherein executing the joint throughput-positioning radio planning problem includes:

solving a network throughput optimization sub-problem that maximizes the network throughput performance, while keeping the positioning performances below a configurable positioning performance threshold; and

solving a positioning optimization sub-problem that minimizes the PEB experienced at the test points (t), while keeping the network throughput performance above a configurable network throughput performance threshold.

8 . The method according to claim 7 , wherein the network throughput optimization sub-problem is formulated as a max-min problem that maximizes the minimum network throughput experienced at the test points t, and wherein the positioning optimization sub-problem is formulated as a min-max problem that minimizes the maximum PEB experienced at the test points (t).

9 . The method according to claim 7 , wherein the positioning performance threshold and the network throughput performance threshold are configured by adaptively processing optimal values of each of the optimization sub-problems.

10 . The method according to claim 7 , further comprising solving the network throughput and positioning optimization sub-problems in a closed-loop fashion, including the steps of:

determining a first optimized network throughput performance value by solving the network throughput optimization sub-problem,

scaling the first optimized network throughput performance value and using the scaled value as network throughput performance threshold for solving the positioning optimization sub-problem, thereby obtaining a first optimized positioning performance value, and

scaling the first optimized positioning performance value and using the scaled value as the positioning performance threshold for solving the network throughput optimization sub-problem, thereby obtaining a second optimized network throughput performance value.

11 . The method according to claim 10 , further comprising:

iterating through the network throughput and positioning optimization sub-problems until convergence.

12 . The method according to claim 1 , wherein the target area encompasses a number of pre-deployed legacy base stations that provide a performance baseline for the joint throughput-positioning radio planning problem.

13 . The method according to claim 1 , wherein the tuning parameter is implemented in such a way that backward compatibility in a network deployment process is provided by setting the tuning parameter to 0.

14 . A system for optimizing positioning performance of a cellular network, in particular a 5G-NR network or beyond, the system comprising memory and one or more processors, the system configured to:

define a target area;

determine a set(S) of base station deployment candidate sites (j) within the target area;

set up a joint throughput-positioning radio planning problem formulated as a single max-min problem that uses a tuning parameter that regulates a throughput-positioning ratio for jointly optimizing network throughput and positioning performance; and

obtain, by solving the joint throughput-positioning radio planning problem, active candidate sites as a subset of the set(S) of base station deployment candidate sites (j) and determine the obtained active candidate sites as the sites at which base stations are to be deployed, wherein the joint throughput-positioning radio planning problem takes as input the tuning parameter and the set(S) of the base station deployment candidate sites (j) and iteratively repeats until a convergence is reached that maximizes minimum network throughput experienced at test points (t) that sample the target area and minimizes a maximum position error bound (PEB) experienced at the test points (t), wherein the tuning parameter is a scalar factor that trades off between the network throughput and the positioning performance within the target area.

15 . A non-transitory computer-readable medium having instructions thereon, which upon execution by one or more processors, alone or in combination, provide for execution of a method for optimizing positioning performance of a cellular network, the method comprising:

defining a target area;

determining a set(S) of base station deployment candidate sites (j) within the target area;

setting up a joint throughput-positioning radio planning problem formulated as a single max-min problem that uses a tuning parameter that regulates a throughput-positioning ration for jointly optimizing network throughput and positioning performance;

obtaining, by solving the joint throughput-positioning radio planning problem, active candidate sites as a subset of the set(S) of base station deployment candidate sites (j) and determining the obtained active candidate sites as the sites at which base stations are to be deployed, wherein the joint throughput-positioning radio planning problem takes as input the tuning parameter and the set(S) of the base station deployment candidate sites (j) and iteratively repeats until a convergence is reached that maximizes minimum network throughput experienced at test points (t) that sample the target area and minimizes a maximum position error bound (PEB) experienced at the test points (t), wherein the tuning parameter is a scalar factor that trades off between the network throughput and the positioning performance within the target area.

16 . The method according to claim 1 , wherein the cellular network is a 5G-NR network.

17 . The system according to claim 14 , wherein the cellular network is a 5G-NR network.

18 . The method according to claim 1 , further comprising sampling the target area by a set (T) of the test points (t), wherein a test point distribution of the test points (t) matches an expected distribution of cellular users in the target area.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 9, 2023
From: ALBANESE, ANTONIO; SCIANCALEPORE, VINCENZO; COSTA-PEREZ, XAVIER
To: NEC LABORATORIES EUROPE GMBH
Reel/Frame 062927/0456 →
Priority Claims (1)
EP 20191206 · Aug 14, 2020 · regional
Continuity (1)
Related Publication 20230308889A1 · Sep 28, 2023
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