IP Library Granted Patent US 10,355,887
Granted Patent B2
US 10,355,887 · App. 16/148,922 · Granted Jul 16, 2019

Iterative two dimensional equalization of orthogonal time frequency space modulated signals

Inventors: Ronny Hadani (Santa Clara, CA); Shachar Kons (Santa Clara, CA)
Assignee: Cohere Technologies, Inc.
H04L25/03012H04L1/005H04L1/0054H04L25/00H04L25/0208H04L25/03159H04L25/03178H04L25/03286H04L25/03318H04L25/08H04L27/2639H04L27/2647H04L25/0212
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,355,887
App. No.
16/148,922
Granted
Jul 16, 2019
Kind
B2
Abstract

An iterative two dimension equalizer usable in a receiver of orthogonal time frequency space (OTFS) modulated signals is described. In one configuration of the equalizer, a forward path generates, from received time-frequency domain samples and a channel estimate, estimates of data bits and likelihood numbers associated with the estimates of data bits, generated by delay-Doppler domain processing. In the feedback direction, the estimates of data bits are used to generate symbol estimates and autocorrelation matrix estimate in the time domain. In another configuration, a soft symbol mapper is used in the feedback direction for directly generating the feedback input symbol estimate without having to generate estimates of data bits.

Claims (69)

1. A wireless communication method for recovering information bits from a received signal, by performing iterative two dimensional equalization, comprising:

receiving, at an iterative equalizer, iteration inputs including a two dimensional estimate of a wireless channel over which the received signal is received, a stream of received symbols, a symbol estimate from a previous iteration, and an input autocorrelation matrix estimate from the previous iteration, and

computing, from the iteration inputs, a Wiener estimate of the stream of received symbols;

transforming the Wiener estimate to symbol estimates in a two dimensional delay-Doppler grid using a two-dimensional symplectic Fourier transform;

estimating likelihoods of the symbol estimates in the two dimensional delay-Doppler grid; and

generating estimates of information bits from the likelihoods.

2. The method of claim 1 , wherein the generating the estimates includes:

deinterleaving the likelihoods of the symbols; and

performing error correction on an output of the deinterleaving.

3. The method of claim 1 , further including, processing in a feedback direction, by generating a symbol estimate and an input autocorrelation matrix estimate for a next iteration.

4. The method of claim 3 , wherein the processing in the feedback direction includes:

performing soft symbol mapping using the likelihoods resulting in intermediate symbol estimates and an intermediate autocorrelation estimate; and

generating the symbol estimate and the input autocorrelation matrix estimate by transforming, using an inverse of the two-dimensional symplectic Fourier transform, the intermediate symbol estimates and the intermediate autocorrelation estimate.

5. The method of claim 1 , wherein the two-dimensional symplectic Fourier transform is a symplectic fast Fourier transform (SFFT).

6. The method of claim 1 , wherein the computing the Wiener estimate comprises:

receiving information about erased time-frequency resource elements from the received signal; and

using prior symbol estimates from a feedback direction as outputs of the computing the Wiener estimates.

7. A wireless communication method for recovering information bits from a received signal, by performing iterative two dimensional equalization, comprising:

receiving, at an iterative equalizer, iteration inputs including a two dimensional estimate of a wireless channel over which the received signal is received, a stream of received symbols, a symbol estimate from a previous iteration, an input autocorrelation matrix estimate from the previous iteration, and

computing, from the iteration inputs, a Wiener estimate of the stream of received symbols;

transforming the Wiener estimate to symbol estimates a two dimensional delay-Doppler grid using a two-dimensional symplectic Fourier transform; and

processing in a feedback direction, by generating a symbol estimate and an input autocorrelation matrix estimate for a next iteration.

8. The method of claim 7 , further including:

estimating likelihoods of the symbol estimates in the two dimensional delay-Doppler grid and

generating estimates of data from the likelihoods.

9. The method of claim 7 , wherein the generating the estimates includes

deinterleaving the likelihoods of the symbols; and

performing error correction on an output of the deinterleaving.

10. The method of claim 9 , wherein the processing in the feedback direction includes:

performing soft symbol mapping using the likelihoods resulting in intermediate symbol estimates and an intermediate autocorrelation estimate; and

generating the symbol estimate and the input autocorrelation matrix estimate by transforming, using an inverse of the two-dimensional symplectic Fourier transform, the intermediate symbol estimates and the intermediate autocorrelation estimate.

11. The method of claim 7 , wherein the two-dimensional symplectic Fourier transform is a symplectic fast Fourier transform (SFFT).

12. The method of claim 7 , wherein the computing the Wiener estimates comprises:

receiving information about erased time-frequency resource elements from the received signal; and

using prior symbol estimates from a feedback direction as outputs of the computing the Wiener estimates.

13. A wireless transceiver apparatus comprising a processor, transmission and reception circuitry and a memory, the apparatus configured to perform a method for recovering information bits from a received signal, the method comprising:

receiving, at an iterative equalizer, iteration inputs including a two dimensional estimate of a wireless channel over which the received signal is received, a stream of received symbols, a symbol estimate from a previous iteration, and an input autocorrelation matrix estimate from the previous iteration, and

computing, from the iteration inputs, a Wiener estimate of the stream of received symbols;

transforming the Wiener estimate to symbol estimates in a two dimensional delay-Doppler grid using a two-dimensional symplectic Fourier transform;

estimating likelihoods of the symbol estimates in the two dimensional delay-Doppler grid; and

generating estimates of information bits from the likelihoods.

14. The apparatus of claim 13 , further configured to:

deinterleave the likelihoods of the symbols; and

perform error correction on an output of the deinterleaving.

15. The apparatus of claim 13 , further configured to process in a feedback direction, by generating a symbol estimate and an input autocorrelation matrix estimate for a next iteration.

16. The apparatus of claim 15 , wherein the processing in the feedback direction includes:

performing soft symbol mapping using the likelihoods resulting in intermediate symbol estimates and an intermediate autocorrelation estimate; and

generating the symbol estimate and the input autocorrelation matrix estimate by transforming, using an inverse of the two-dimensional symplectic Fourier transform, the intermediate symbol estimates and the intermediate autocorrelation estimate.

17. The apparatus of claim 13 , wherein the processing in the feedback direction includes:

performing soft symbol mapping using the likelihoods resulting in intermediate symbol estimates and an intermediate autocorrelation estimate; and

generating the symbol estimate and the input autocorrelation matrix estimate by transforming, using an inverse of the two-dimensional symplectic Fourier transform, the intermediate symbol estimates and the intermediate autocorrelation estimate.

18. A non-transitory computer readable storage medium having code stored thereupon, the code, when executed, causing a processor to implement a method recovering information bits from a received signal by performing iterative two dimensional equalization, comprising:

receiving, at an iterative equalizer, iteration inputs including a two dimensional estimate of a wireless channel over which the received signal is received, a stream of received symbols, a symbol estimate from a previous iteration, an input autocorrelation matrix estimate from the previous iteration, and

computing, from the iteration inputs, a Wiener estimate of the stream of received symbols;

transforming the Wiener estimate to symbol estimates a two dimensional delay-Doppler grid using a two-dimensional symplectic Fourier transform; and

processing in a feedback direction, by generating a symbol estimate and an input autocorrelation matrix estimate for a next iteration.

19. The non-transitory computer readable storage medium of claim 17 , wherein the method further includes:

estimating likelihoods of the symbol estimates in the two dimensional delay-Doppler grid and

generating estimates of data from the likelihoods.

20. The non-transitory computer readable storage medium of claim 19 , wherein the generating the estimates includes

deinterleaving the likelihoods of the symbols; and

performing error correction on an output of the deinterleaving.

21. The non-transitory computer readable storage medium of claim 18 , wherein the processing in the feedback direction includes:

performing soft symbol mapping using the likelihoods resulting in intermediate symbol estimates and an intermediate autocorrelation estimate; and

generating the symbol estimate and the input autocorrelation matrix estimate by transforming, using an inverse of the two-dimensional symplectic Fourier transform, the intermediate symbol estimates and the intermediate autocorrelation estimate.

22. The non-transitory computer readable storage medium of claim 18 , wherein the two-dimensional symplectic Fourier transform is a symplectic fast Fourier transform (SFFT).

23. The non-transitory computer readable storage medium of claim 18 , wherein the computing the Wiener estimates comprises:

receiving information about erased time-frequency resource elements from the received signal; and

using prior symbol estimates from a feedback direction as outputs of the computing the Wiener estimates.

Assignments (4)
RELEASE OF SECURITY INTEREST Recorded Jul 10, 2025
From: NEW ENTERPRISE ASSOCIATES 14, LIMITED PARTNERSHIP
To: COHERE TECHNOLOGIES, INC.
Reel/Frame 071913/0090 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 6, 2021
From: HADANI, RONNY; KONS, SHACHAR
To: COHERE TECHNOLOGIES, INC.
Reel/Frame 055843/0062 →
SECURITY INTEREST Recorded Apr 1, 2020
From: COHERE TECHNOLOGIES, INC.
To: NEW ENTERPRISE ASSOCIATES 14, LIMITED PARTNERSHIP
Reel/Frame 052287/0739 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 24, 2019
From: HADANI, RONNY; KONS, SHACHAR
To: COHERE TECHNOLOGIES, INC.
Reel/Frame 049848/0625 →
Continuity (3)
Continuation PCTUS2017025578 · Mar 31, 2017
Provisional Application 62317420 · Apr 1, 2016
Related Publication 20190036741A1 · Jan 31, 2019