# US 10,312,993 B2 · Cooperative clustering for enhancing MU-massive-MISO-based UAV communication

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- Number: US 10,312,993 B2
- Document ID: US10312993B2
- Status: Granted
- Kind: B2
- Application number: 15/337,346
- Filed: 2016-10-28
- Published: 2017-05-04
- Granted: 2019-06-04
- Earliest claimed: 2015-10-30
- Assignees: The Florida International University Board of Trustees
- Applicants: Nadisanka Rupasinghe; Ismail Guvenc; Ahmed Salah Ibrahim Mohamed
- Inventors: Nadisanka Rupasinghe; Ismail Guvenc; Ahmed Salah Ibrahim Mohamed
- Web page: https://patentgrep.com/patent/US10312993B2

## CPC

- H04B 7/18506: {Communications with or from aircraft, i.e. aeronautical mobile service}
- B64U 10/00: Type of UAV
- G05D 1/104: {involving a plurality of aircrafts, e.g. formation flying (traffic control systems for aircraft G08G5/00)}
- H04B 7/024: Co-operative use of antennas of several sites, e.g. in co-ordinated multipoint or co-operative multiple-input multiple-output [MIMO] systems
- H04B 7/0452: Multi-user MIMO systems
- H04B 7/0617: {for beam forming}
- B64U 2101/20: for use as communications relays, e.g. high-altitude platforms
- B64U 2201/102: adapted for flying in formations
- H04B: TRANSMISSION
- B64U: UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES

## Abstract

Methods, apparatuses, and systems for organizing data delivering unmanned aerial vehicles (UAVs) are provided. Inter-cluster coordinators can organize data delivering unmanned aerial vehicle base stations (UAV-BSs). Various beamforming techniques (e.g., LZFBF and ZFBF) can be incorporated, and the inter-cluster coordinator can operate on a base station that serves as a controlling network node.

## Claims

### Claim 1

A method for identifying optimum hovering locations for unmanned aerial vehicle base stations (UAV-BSs) communications, the method comprising:
identifying user locations;
defining a hovering grid that includes the user locations;
determining an absolute value of directional cosine separation |Ωk,un| for each grid point, which is the separation between directional cosines between the uth user and the kth user of the nth UAV-BS;
detecting all grid points (y,z) with directional cosine separation |Ωk,un|=2/Nt×q and q≤Nt−1, wherein Nt is the number of antenna arrays for the nth UAV-BS and q is an integer;
calculating the distance from all grid points (y,z) to each user; and
assigning grid point (y,z) to the UAV-BSs (yn,zn) based on the minimum distance to their intended user.

### Claim 2 (depends on 1)

The method of claim 1, wherein the hovering grid is symmetric around two or more users.

### Claim 3 (depends on 1)

The method of claim 1, wherein the directional cosine separation for each grid point is determined by Ωk,un=cos Φun−cos Φkn, which is the separation between directional cosines between the uth user and the kth user of the nth UAV-BS.

### Claim 4 (depends on 1)

The method of claim 1, wherein the method is executed partially or entirely within one or more of the UAV-BSs.

### Claim 5 (depends on 1)

The method of claim 1, further comprising incorporating transmit (Tx) beamforming.

### Claim 6 (depends on 1)

The method of claim 1, further comprising incorporating linear zero-force (LZFBF) beamforming.

### Claim 7 (depends on 1)

The method of claim 1, wherein the method does not include sending channel state information.

### Claim 8 (depends on 1)

The method of claim 1, wherein if no grid points are found in the detecting all grid points (y,z) with directional cosine separation |Ωk,un|=2/Nt×q and q≤Nt−1, the method further comprises selecting grid points with directional cosine separation closest to an integer multiple of 2/Nt that can satisfy the constraints in
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.

### Claim 9 (depends on 1)

The method of claim 1, wherein the method further comprises incorporating linear single user beamforming (LSUBF).

### Claim 10 (depends on 1)

The method of claim 1, wherein the method further comprises incorporating zero-forcing beamforming (ZFBF).

### Claim 11 (depends on 1)

The method of claim 1, wherein the method includes millimeter wave communication technology.

### Claim 12

An inter-cluster coordinator for identifying optimum hovering locations for unmanned aerial vehicle base stations (UAV-BSs) comprising a processor, volatile and non-volatile memory, antennas suitable for communicating with the unmanned aerial vehicle base stations (UAV-BSs) and a non-transitory machine-readable medium with computer executable instructions stored thereon that when executed by a processor perform the method of:
identifying user locations;
defining a hovering grid that includes the user locations;
determining an absolute value of directional cosine separation |Ωk,un| for each grid point, which is the separation between directional cosines between the uth user and the kth user of the nth UAV-BS;
detecting all grid points (y,z) with directional cosine separation |Ωk,un|=2/Nt×q and q≤Nt−1, wherein Nt is the number of uniform linear antenna arrays for the nth UAV-BS and q is an integer;
calculating the distance from all grid points (y,z) to each user; and
assigning grid point (y,z) to the UAV-BSs (yn,zn) based on the minimum distance to their intended user.

### Claim 13 (depends on 12)

The inter-cluster coordinator of claim 12, wherein the inter-cluster coordinator is a UAV-BS.

### Claim 14 (depends on 12)

The inter-cluster coordinator of claim 12, wherein the method further comprises transmit (Tx) beamforming.

### Claim 15 (depends on 12)

The inter-cluster coordinator of claim 12, wherein the method further comprises linear zero-force (LZFBF) beamforming.

### Claim 16 (depends on 12)

The inter-cluster coordinator of claim 12, wherein the method does not include sending channel state information.

### Claim 17 (depends on 12)

The inter-cluster coordinator of claim 12, wherein the method includes incorporating millimeter wave communication technology.