System and method for detecting active resource units

• US 10,374,761 B2
• Filed: 07/20/2017
• Issued: 08/06/2019
• Est. Priority Date: 10/30/2014
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: Yi, Zhihang, Nikopour, Hosein, Bayesteh, Alireza
• Primary Examiner(s): Zhao, Wei
• Application Number:
  US15/655,362
• Publication Number:
  US 20170317799A1
• Time in Patent Office: 747 Days
• CPC Class Codes: H04L 27/0006 Assessment of spectral gaps suitable for allocating digitally modulated signals, e.g. for carrier allocation in cognitive radio for spectrum sharing between different networks H04W16/14
• CPC Class Codes: H04L 5/0016 Time-frequency-code
• CPC Class Codes: H04L 5/0048 Allocation of pilot signals, i.e. of signals known to the receiver

Abstract

Disclosed herein are an active resource unit detector and a method of use thereof. An embodiment method of detecting active resource units among a plurality of potential resource units includes receiving an aggregate signal containing active pilots transmitted over the active resource units via random access transmissions. The active pilots are then detected and respectively associated with the active resource units according to a pilot-to-resource unit mapping.

Claims

1. A method of detecting resource units in a random access transmission system, the method comprising:

receiving an aggregate signal containing a sum of active pilots transmitted over a shared time-frequency resource via random access transmissions by active user equipments;

detecting the active pilots from the received aggregate signal; and

respectively associating the active pilots with the resource units according to a pilot-to-resource unit mapping.

2. The method of claim 1, wherein the resource units comprise sparse code multiple access (SCMA) codebooks.

3. The method of claim 1, further comprising generating a list of the resource units according to the pilot-to-resource unit mapping.

4. The method of claim 1, further comprising respectively associating the active pilots with the active user equipments according to a pilot-to-user equipment mapping.

5. The method of claim 1, wherein the pilot-to-resource unit mapping includes a mapping of one pilot of the active pilots to more than one of the resource units, and wherein the respectively associating the active pilots with the resource units further comprises associating the one pilot according to a masked cyclic redundancy check (CRC) for a corresponding resource unit.

6. The method of claim 1, wherein the pilot-to-resource unit mapping includes a mapping of one pilot of the active pilots to more than one of the resource units, and wherein the respectively associating the active pilots with the resource units further comprises associating the one pilot according to payload header information for a corresponding resource unit.

7. The method of claim 1, wherein the pilot-to-resource unit mapping includes a mapping of each of the active pilots to only one of the resource units.

8. The method of claim 1, wherein the detecting the active pilots comprises:

estimating respective channels for a plurality of potential pilots respectively corresponding to a plurality of potential resource units;

calculating respective powers for the respective channels, the plurality of potential pilots including at least one lowest-power pilot;

eliminating the at least one lowest-power pilot from a plurality of potentially active pilots; and

repeating the estimating, the calculating, and the eliminating until a count of the plurality of potentially active pilots reaches a threshold.

9. The method of claim 1, wherein the detecting the active pilots includes solving a system formed by the aggregate signal, the active pilots transmitted by the active user equipments, and respective channels for a plurality of potential resource units using a compressive sensing technique.

10. The method of claim 9, wherein the compressive sensing technique comprises an expectation-maximization (EM) technique.

11. The method of claim 9, wherein the compressive sensing technique comprises a focal underdetermined system solver (FOCUSS) technique.

25. The method of claim 1, wherein the resource units comprise code domain spreading signatures.

26. The method of claim 25, wherein the code domain spreading signatures comprise low-density signature (LDS) signatures.

12. A communications controller for detecting resource units in a random access transmission system, the communications controller comprising:

a receiver configured to receive an aggregate signal containing a sum of active pilots transmitted over a shared time-frequency resource via random access transmissions by active user equipments;

a non-transitory memory storage comprising instructions; and

one or more processors in communication with the receiver and the memory storage, wherein the one or more processors execute the instructions to;

detect the active pilots from the received aggregate signal; and

respectively associate the active pilots with the resource units according to a pilot-to-resource unit mapping.

13. The communications controller of claim 12, wherein the resource units comprise sparse code multiple access (SCMA) codebooks.

14. The communications controller of claim 12, wherein the one or more processors further execute the instructions to generate a list of the resource units according to the pilot-to-resource unit mapping.

15. The communications controller of claim 12, wherein the one or more processors execute the instructions to respectively associate the active pilots with the active user equipments according to a pilot-to-user equipment mapping.

16. The communications controller of claim 12, wherein the pilot-to-resource unit mapping includes a mapping of one pilot of the active pilots to more than one of the resource units, and wherein the one or more processors executing the instructions to respectively associate the active pilots with the resource units comprises the one or more processors executing the instructions to associate the one pilot according to a masked cyclic redundancy check (CRC) for a corresponding resource unit.

17. The communications controller of claim 12, wherein the pilot-to-resource unit mapping includes a mapping of one pilot of the active pilots to more than one of the resource units, and wherein the one or more processors executing the instructions to respectively associate the active pilots with the resource units comprises the one or more processors executing the instructions to associate the one pilot according to payload header information for a corresponding resource unit.

18. The communications controller of claim 12, wherein the pilot-to-resource unit mapping includes a mapping of each of the active pilots to only one of the resource units.

19. The communications controller of claim 12, wherein the one or more processors executing the instructions to detect the active pilots comprises the one or more processors executing the instructions to:

estimate respective channels for a plurality of potential pilots respectively corresponding to a plurality of potential resource units;

calculate respective powers for the respective channels, the plurality of potential pilots including at least one lowest-power pilot;

eliminate the at least one lowest-power pilot from a plurality of potentially active pilots; and

repeat the estimating, the calculating, and the eliminating until a count of the plurality of potentially active pilots reaches a threshold.

20. The communications controller of claim 12, wherein the one or more processors executing the instructions to detect the active pilots comprises the one or more processors executing the instructions to solve a system formed by the aggregate signal, the active pilots transmitted by the active user equipments, and respective channels for a plurality of potential resource units using a compressive sensing technique.

21. The communications controller of claim 20, wherein the compressive sensing technique comprises an expectation-maximization (EM) technique.

22. The communications controller of claim 20, wherein the compressive sensing technique comprises a focal underdetermined system solver (FOCUSS) technique.

23. The communications controller of claim 12, wherein the resource units comprise code domain spreading signatures.

24. The communications controller of claim 23, wherein the code domain spreading signatures comprise low-density signature (LDS) signatures.