Cooperative clustering for enhancing MU-massive-MISO-based UAV communication

• US 10,312,993 B2
• Filed: 10/28/2016
• Issued: 06/04/2019
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Original Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Inventors: Rupasinghe, Nadisanka, Guvenc, Ismail, Mohamed, Ahmed Salah Ibrahim
• Primary Examiner(s): Rego, Dominic E
• Application Number:
  US15/337,346
• Publication Number:
  US 20170126309A1
• Time in Patent Office: 949 Days
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 10/00 Type of UAV
• CPC Class Codes: B64U 10/13 Flying platforms
• CPC Class Codes: B64U 2101/20 for use as communications relays, e.g. high-altitude platforms
• CPC Class Codes: B64U 2201/102 adapted for flying in formations
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: 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
• CPC Class Codes: H04B 7/0452 Multi-user MIMO systems
• CPC Class Codes: H04B 7/0617 for beam forming
• CPC Class Codes: H04B 7/18506 Communications with or from aircraft, i.e. aeronautical mobile service

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

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 |Ω

_k,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 |Ω

_k,un|=2/N_t×

q and q≤

N_t−

1, wherein N_t 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 (y_n,z_n) based on the minimum distance to their intended user.

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

3. The method of claim 1, wherein the directional cosine separation for each grid point is determined by Ω

_k,un=cos Φ

_un−

cos Φ

_kn, which is the separation between directional cosines between the uth user and the kth user of the nth UAV-BS.

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

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

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

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

8. The method of claim 1, wherein if no grid points are found in the detecting all grid points (y,z) with directional cosine separation |Ω

_k,un|=2/N_t×

q and q≤

N_t−

1, the method further comprises selecting grid points with directional cosine separation closest to an integer multiple of 2/N_t that can satisfy the constraints in

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

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

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

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 |Ω

_k,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 |Ω

_k,un|=2/N_t×

q and q≤

N_t−

1, wherein N_t 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 (y_n,z_n) based on the minimum distance to their intended user.

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

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

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

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

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