System and method for detecting active user equipments

• US 9,735,931 B2
• Filed: 10/30/2014
• Issued: 08/15/2017
• 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:
  US14/528,911
• Publication Number:
  US 20160128100A1
• Time in Patent Office: 1,020 Days
• Field of Search: 370329
• 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 active user equipments in a random access transmission system, the method comprising:

receiving an aggregate signal containing a sum of active pilots transmitted over active resource units among a plurality of potential resource units via random access transmissions by the active user equipments;

detecting the active pilots from the received aggregate signal; and

respectively associating the active pilots with the active user equipments according to a pilot-to-user equipment mapping.

2. 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 for a plurality of potential pilots and a plurality of potential user equipments.

3. The method of claim 2 wherein the pilot-to-user equipment mapping includes mapping one pilot of the plurality of potential pilots to multiple user equipments of the plurality of potential user equipments, and wherein the respectively associating the active pilots with the active user equipments further comprises associating the one pilot according to a masked cyclic redundancy check (CRC) for a corresponding user equipment.

4. The method of claim 2 wherein the pilot-to-user equipment mapping includes mapping one pilot of the plurality of potential pilots to multiple user equipments of the plurality of potential user equipments, and wherein the respectively associating the active pilots with the active user equipments further comprises associating the one pilot according to payload header information for a corresponding user equipment.

5. The method of claim 2 wherein the pilot-to-user equipment mapping includes mapping each of the plurality of potential pilots to only one user equipment of the plurality of potential user equipments.

6. The method of claim 1 further comprising generating a list of the active user equipments according to the pilot-to-user equipment mapping.

7. The method of claim 2 wherein the random access transmissions use low-density signature (LDS) waveforms that further employ respective spreading signatures for the plurality of potential user equipments.

8. The method of claim 7 further comprising detecting inactive spreading signatures of the respective spreading signatures to reduce a quantity of potentially active user equipments in the plurality of potential user equipments.

9. The method of claim 2 wherein the random access transmissions use sparse code multiple access (SCMA) waveforms that further employ respective codebooks for the plurality of potential user equipments.

10. The method of claim 2 wherein detecting the active pilots includes:

estimating respective channels for the plurality of potential pilots respectively corresponding to the plurality of potential user equipments;

calculating respective powers for the respective channels, wherein the plurality of potential pilots includes 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.

11. The method of claim 2 wherein the detecting the active pilots includes solving a system formed by the aggregate signal, the active pilots transmitted over the active user equipments, and respective channels for the plurality of potential user equipments using a compressive sensing technique.

12. The method of claim 11 wherein the compressive sensing technique comprises an expectation-maximization (EM) technique.

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

14. An active user equipment detector, comprising:

a memory configured to store a plurality of potential pilots respectively corresponding to at least one potential user equipment of a plurality of potential user equipments; and

a pilot detector having a processor coupled to the memory and configured to;

receive an aggregate signal over a plurality of active resource units among a plurality of potential resource units, wherein the aggregate signal contains a sum of active pilots of the plurality of potential pilots, for respective random access transmissions by active user equipments, and

respectively associate the active pilots from the received aggregate signal to at least one corresponding active user equipment of the active user equipments.

15. The active user equipment detector of claim 14 wherein the aggregate signal comprises at least one low-density signature (LDS) waveform that further employs respective spreading signatures for the plurality of potential user equipments.

16. The active user equipment detector of claim 15 further comprising a signature decorrelator coupled to the pilot detector and configured to detect active spreading signatures of the respective spreading signatures for a plurality of active user equipments.

17. The active user equipment detector of claim 14 wherein the memory is further configured to store a pilot-to-user equipment mapping that maps the plurality of potential pilots to a plurality of potential user equipments.

18. The active user equipment detector of claim 17 wherein the pilot-to-user equipment mapping respectively maps each one of the plurality of potential pilots to at least one of the plurality of potential user equipments.

19. The active user equipment detector of claim 18 wherein the processor is further configured to respectively associate the active pilots to at least one active user equipment of the plurality of potential user equipments.

20. The active user equipment detector of claim 17 wherein the pilot-to-user equipment mapping respectively maps each one of the plurality of potential pilots to one of the plurality of potential user equipments.

21. The active user equipment detector of claim 20 wherein the processor is further configured to respectively associate the active pilots to one active user equipment of the plurality of potential user equipments.

22. The active user equipment detector of claim 14 wherein the processor is further configured to:

receive respective channel estimations for the plurality of potential pilots;

calculate respective channel powers according to the respective channel estimations; and

eliminate at least one lowest-power pilot from a plurality of potentially active pilots according to the respective channel powers to identify the active pilots and corresponding active user equipments.

23. The active user equipment detector of claim 22 wherein the at least one lowest-power pilot has a channel power below a threshold.

24. The active user equipment detector of claim 22 wherein the at least one lowest-power pilot has a lowest channel power among the respective channel powers.

25. The active user equipment detector of claim 14 wherein the processor is further configured to solve a system formed by the aggregate signal, the plurality of potential pilots, and respective channels for the plurality of potential user equipments using a compressive sensing technique to identify and associate the active pilots with a plurality of active user equipments.

26. The active user equipment detector of claim 25 wherein the compressive sensing technique includes using an expectation-maximization (EM) technique.

27. The active user equipment detector of claim 25 wherein the compressive sensing technique includes using a focal underdetermined system solver (FOCUSS) technique.

28. A receiver for random access transmissions, comprising:

a memory configured to store;

a plurality of potential pilots that respectively correspond to at least one user equipment of a plurality of potential user equipments,

a pilot list of potentially active pilots, wherein the pilot list contains a subset of the plurality of potential pilots, and

a user equipment list of potentially active user equipments, wherein the user equipment list contains a subset of the plurality of potential user equipments; and

a processor coupled to the memory and configured to;

receive an aggregate signal containing a sum of active pilot signals for respective random access transmissions from active user equipments,

detect the active pilot signals from the received aggregate signal,

match the active pilot signals with the potentially active pilots in the pilot list,

associate the potentially active pilots with a narrowed set of respectively corresponding user equipments to identify potentially active user equipments,

estimate channels corresponding to the potentially active user equipments, and

receive and decode the aggregate signal according to the potentially active user equipments and respective corresponding channel estimations.

29. The receiver of claim 28 wherein the aggregate signal contains a plurality of low-density signature waveforms having respective active spreading signatures, each associated with at least one user equipment of the plurality of potential user equipments.

30. The receiver of claim 29 wherein the processor comprises a signature decorrelator module configured to detect the respective active spreading signatures and add an initial set of respectively corresponding user equipments to the user equipment list, wherein the narrowed set of respectively corresponding user equipments is a subset of the initial set.

31. The receiver of claim 28 wherein the aggregate signal contains a plurality of sparse code multiple access (SCMA) waveforms having respective active codebooks, each associated with at least one user equipment of the plurality of potential user equipments.

32. The receiver of claim 28 wherein the plurality of potential pilots respectively correspond to at least one active user equipment of the potentially active user equipments.

33. The receiver of claim 32 wherein each of the potentially active user equipments is in a cellular network.

34. The receiver of claim 28 wherein the processor is further configured to:

compute channel estimations corresponding to the plurality of potential pilots;

determine respective channel powers for the channel estimations;

remove at least one lowest-power pilot from the pilot list according to the respective channel powers; and

narrow the user equipment list by low-power user equipments respectively corresponding to the at least one lowest-power pilot.

35. The receiver of claim 28 wherein the processor is further configured to solve a system formed by the sum of active pilot signals, the plurality of potential pilots, and channels respectively corresponding to the plurality of potential user equipments using a compressive sensing technique to identify the potentially active pilots.

36. The receiver of claim 35 wherein the compressive sensing technique comprises a focal underdetermined system solver (FOCUSS) technique.

37. The receiver of claim 35 wherein the compressive sensing technique comprises an expectation-maximization (EM) technique.