IP Library Granted Patent US 9,843,417
Granted Patent B2
US 9,843,417 · App. 14/619,612 · Granted Dec 12, 2017

Differential MIMO transceiver

Inventors: Akbar M. Sayeed (Madison, WI); John H. Brady (Madison, WI)
Assignee: Wisconsin Alumni Research Foundation
H04L1/0618H04B7/0617H04B7/0626H04B7/0697
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Quick Facts
Patent No.
US 9,843,417
App. No.
14/619,612
Granted
Dec 12, 2017
Kind
B2
Abstract

A method of estimating a spatial filter matrix is provided. A conjugate of a received first signal defines a conjugate first signal. A Kronecker product of the defined first signal and a received second signal define a differential measurement signal. The computations are repeated for a plurality of first and second signals sufficient to compute an estimate of a channel matrix from the differential measurement signals. A spatial filter matrix is computed from the computed estimate of the channel matrix. The computed spatial filter matrix is used in a data communication phase between the first plurality of antennas and the second plurality of antennas.

Claims (72)

1. A method of estimating a spatial filter matrix, the method comprising:

(a) receiving a first signal by a receiver, the first signal received from a first plurality of antennas, wherein the first signal is a result of a first transmitted signal transmitted by a second plurality of antennas;

(b) computing a conjugate of the received first signal to define a conjugate first signal;

(c) receiving a second signal by the receiver from the first plurality of antennas, wherein the second signal is received after the first signal, wherein the second signal is a result of a second transmitted signal transmitted by the second plurality of antennas;

(d) computing a Kronecker product of the defined conjugate first signal and the received second signal to define a differential measurement signal;

(e) repeating (a) to (d) for a plurality of first and second signals sufficient to compute an estimate of a channel matrix;

computing the estimate of the channel matrix from the differential measurement signals defined in (d); and

computing a spatial filter matrix from the computed estimate of the channel matrix;

wherein the computed spatial filter matrix is used in a data communication phase between the first plurality of antennas and the second plurality of antennas.

2. The method of claim 1 , wherein the differential measurement signal is computed using r* T r, where r* T is the defined conjugate first signal and r is the received second signal, and indicates the Kronecker product.

3. The method of claim 1 , wherein each pair of first and second signals is selected so that a single column of the channel matrix is estimated from the associated differential measurement signal defined in (d).

4. The method of claim 1 , wherein the spatial filter matrix is computed using H d H (ρ 2 H d H d H +Σ w ) −1 , where H d is the estimated channel matrix, H d H is a hermitian matrix computed from H d , ρ is a signal to noise ratio, Σ w is a covariance matrix of w, and w is a noise vector.

5. The method of claim 1 , further comprising, in the data communication phase:

receiving a third signal by the receiver, the third signal received from the first plurality of antennas, wherein the third signal is a result of a third transmitted signal transmitted by the second plurality of antennas;

computing a conjugate of the received third signal to define a conjugate third signal;

receiving a fourth signal by the receiver from the first plurality of antennas, wherein the fourth signal is a result of a fourth transmitted signal transmitted by the second plurality of antennas, wherein the fourth signal is received after the third signal;

computing a Kronecker product of the defined conjugate third signal and the received fourth signal to define a second differential measurement signal;

spatially filtering the defined second differential measurement signal using the computed spatial filter matrix to define an estimate vector; and

detecting a plurality of information symbols from the defined estimate vector.

6. The method of claim 1 , wherein the spatial filter matrix is computed using H O H (ρH O H O H +σ 2 I n ) −1 , where H O is the estimated channel matrix, H O H is a hermitian matrix computed from H O , ρ is a signal to noise ratio, σ 2 is noise power, and I n is an identity matrix.

7. The method of claim 6 , wherein each pair of first and second signals is selected so that a single column of a first channel matrix is estimated from the associated differential measurement signal defined in (d).

8. The method of claim 7 , wherein H O is computed from the estimated first channel matrix.

9. The method of claim 6 , further comprising, in the data communication phase:

receiving a third signal by the receiver, the third signal received from the first plurality of antennas, wherein the third signal is a result of a third transmitted signal transmitted by the second plurality of antennas;

spatially filtering the received third signal using the computed spatial filter matrix to define a first filtered signal; and

computing a conjugate of the first filtered signal to define a conjugate first filtered signal;

receiving a fourth signal by the receiver from the first plurality of antennas, wherein the fourth signal is a result of a fourth transmitted signal transmitted by the second plurality of antennas, wherein the fourth signal is received after the third signal;

spatially filtering the received fourth signal using the computed spatial filter matrix to define a second filtered signal; and

computing a Hadamard product of the defined second filtered signal and the defined, conjugate first filtered signal to define a second differential measurement signal; and

detecting a plurality of information symbols from the defined second differential measurement signal.

10. A receiver comprising:

a processor configured to

(a) receive a first signal, the first signal received from a first plurality of antennas, wherein the first signal is a result of a first transmitted signal transmitted by a second plurality of antennas;

(b) compute a conjugate of the received first signal to define a conjugate first signal;

(c) receive a second signal from the first plurality of antennas, wherein the second signal is received after the first signal, wherein the second signal is a result of a second transmitted signal transmitted by the second plurality of antennas;

(d) compute a Kronecker product of the defined conjugate first signal and the received second signal to define a differential measurement signal;

(e) repeat (a) to (d) for a plurality of first and second signals sufficient to compute an estimate of a channel matrix;

compute the estimate of the channel matrix from the differential measurement signals defined in (d); and

compute a spatial filter matrix from the computed estimate of the channel matrix;

wherein the computed spatial filter matrix is used in a data communication phase between the first plurality of antennas and the second plurality of antennas.

11. The receiver of claim 10 , wherein the differential measurement signal is computed using r* T r, where r* T is the defined conjugate first signal and r is the received second signal, and indicates the Kronecker product.

12. The receiver of claim 10 , wherein each pair of first and second signals is selected so that a single column of the channel matrix is estimated from the associated differential measurement signal defined in (d).

13. The receiver of claim 10 , wherein the spatial filter matrix is computed using H d H (ρ 2 H d H d H +Σ w ) −1 , where H d is the estimated channel matrix, H d H is a hermitian matrix computed from H d , ρ is a signal to noise ratio, Σ w is a covariance matrix of w, and w is a noise vector.

14. The receiver of claim 10 , wherein the processor is further configured to, in the data communication phase:

receive a third signal by the receiver, the third signal received from the first plurality of antennas, wherein the third signal is a result of a third transmitted signal transmitted by the second plurality of antennas;

compute a conjugate of the received third signal to define a conjugate third signal;

receive a fourth signal by the receiver from the first plurality of antennas, wherein the fourth signal is a result of a fourth transmitted signal transmitted by the second plurality of antennas, wherein the fourth signal is received after the third signal;

compute a Kronecker product of the defined conjugate third signal and the received fourth signal to define a second differential measurement signal;

spatially filter the defined differential measurement signal using the computed spatial filter matrix to define an estimate vector; and

detect a plurality of information symbols from the defined estimate vector.

15. The receiver of claim 10 , wherein the spatial filter matrix is computed using H O H (ρH O H O H +σ 2 I n ) −1 , where H O is the estimated channel matrix, H O H is a hermitian matrix computed from H O , ρ is a signal to noise ratio, σ 2 is noise power, and I n is an identity matrix.

16. The receiver of claim 15 , wherein each pair of first and second signals is selected so that a single column of a first channel matrix is estimated from the associated differential measurement signal defined in (d).

17. The receiver of claim 16 , wherein H O is computed from the estimated first channel matrix.

18. The receiver of claim 15 , wherein the processor is further configured to, in the data communication phase:

receive a third signal by the receiver, the third signal received from the first plurality of antennas, wherein the third signal is a result of a third transmitted signal transmitted by the second plurality of antennas, wherein the third signal includes a first transmitted symbol;

spatially filter the received third signal using the computed spatial filter matrix to define a first filtered signal; and

compute a conjugate of the first filtered signal to define a conjugate first filtered signal;

receive a fourth signal by the receiver from the first plurality of antennas, wherein the fourth signal is a result of a fourth transmitted signal transmitted by the second plurality of antennas, wherein the fourth signal includes a second transmitted symbol, wherein the fourth signal is received after the third signal;

spatially filter the received fourth signal using the computed spatial filter matrix to define a second filtered signal; and

compute a Hadamard product of the defined second filtered signal and the defined, conjugate first filtered signal to define a second differential measurement signal; and

detect a plurality of information symbols from the defined second differential measurement signal.

19. A transmitter comprising:

a processor configured to

(a) receive a first signal, the first signal received from a first plurality of antennas, wherein the first signal is a result of a first transmitted signal transmitted by a second plurality of antennas;

(b) compute a conjugate of the received first signal to define a conjugate first signal;

(c) receive a second signal from the first plurality of antennas, wherein the second signal is received after the first signal, wherein the second signal is a result of a second transmitted signal transmitted by the second plurality of antennas;

(d) compute a Kronecker product of the defined conjugate first signal and the received second signal to define a differential measurement signal;

(e) repeat (a) to (d) for a plurality of first and second signals sufficient to compute an estimate of a channel matrix;

compute the estimate of the channel matrix from the differential measurement signals defined in (d);

compute a spatial filter matrix from the computed estimate of the channel matrix; and

transmit a third signal to the second plurality of antennas, wherein the third signal is precoded using the computed spatial filter matrix.

20. The transmitter of claim 19 , wherein the third signal is precoded as s→Gs V , where s is the transmitted third signal, s V is a symbol vector, G=αF, α=√{square root over (ρ/tr(FΛ s F H ))}, F is the computed spatial filter matrix, ρ is a signal to noise ratio, Λ s =E[s V s V H ] is a diagonal covariance of transmitted symbol vectors, F H is a hermitian matrix computed from F, and tr(A) denotes a trace of a square matrix A, which is a sum of diagonal entries of A.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 10, 2017
From: BRADY, JOHN; SAYEED, AKBAR
To: WISCONSIN ALUMNI RESEARCH FOUNDATION
Reel/Frame 043254/0003 →
Continuity (1)
Related Publication 20170317854A1 · Nov 2, 2017