Apparatus and method for canceling interference in multi-antenna system

• US 20090147890A1
• Filed: 12/02/2008
• Published: 06/11/2009
• Est. Priority Date: 12/05/2007
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Choi, Soong-Yoon, Lee, Jong-Ho, Lee, Joo-Hyun, Hwang, Suk-Seung
• Granted Patent: US 8,385,479 B2
• Time in Patent Office: Days
• US Class Current: 375/341
• CPC Class Codes: H04B 7/0851 using training sequences or error signal minimizing error signal H04B7/0854
• CPC Class Codes: H04L 1/0048 in conjunction with detection of multiuser or interfering signals, e.g. iteration between CDMA or MIMO detector and FEC decoder for spatial equalizer H04L25/03286
• CPC Class Codes: H04L 1/0054 Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
• CPC Class Codes: H04L 25/0204 of multiple channels
• CPC Class Codes: H04L 25/03171 Arrangements involving maximum a posteriori probability [MAP] detection

Abstract

An apparatus and a method for canceling interference based on Maximum Likelihood (ML) at a receiver of a multi-antenna system are provided. The method includes estimating a channel using a signal received over one or more receiver antennas; generating one or more weights using the estimated channel to cancel interference; detecting a candidate symbol having the shortest Euclidean distance through Maximum Likelihood using a first weight; and soft-decoding the candidate symbol using a second weight. Therefore, by receiving the signal based on the ML under the interference, the system capacity can be increased and the reception performance can be enhanced.

Claims

1. A method for receiving a signal at a receiver of a multi-antenna system, the method comprising:

estimating a channel using a signal received over one or more receiver antennas;

generating one or more weights using the estimated channel to cancel interference;

detecting a candidate symbol having the shortest Euclidean distance through Maximum Likelihood using a first weight; and

decoding the candidate symbol using a second weight.

2. The method of claim 1, wherein the first weight and the second weight have different values or the same value.

3. The method of claim 1, wherein, when the candidate symbol detected at the receiver is the same as a symbol transmitted from a serving base station (BS), the first weight is a weight to minimize a Euclidean distance of a channel to the serving BS and a Euclidean distance of a channel of at least one interference signal.

4. The method of claim 1, wherein the second weight is a weight to minimize a Euclidean distance of a channel to a serving BS and a Euclidean distance of a channel of at least one interference signal with respect to all of candidate symbols applicable to the ML at the receiver.

5. The method of claim 1, wherein the generating of the weights comprises:

when not able to estimate a channel of an interference signal, generating one or more weights for the interference cancellation using the estimated channel and a correlation value of the receive signal and the interference signal.

6. The method of claim 1, wherein the generating of the weights comprises:

generating one or more weights for the interference cancellation using any one of Zero Forcing (ZF) and Minimum Mean Squared Error (MMSE).

7. The method of claim 1, wherein the detecting of the candidate symbol comprises:

selecting a candidate symbol having the shortest Euclidean distance calculated by nulling an interference signal using the first weight based on the following equation;

$\begin{array}{cc}\begin{array}{c}{\hat{s}}_{\mathrm{Prop}}=\underset{s}{\min }<br><br>{<br><br>W_{\mathrm{HD}}<br><br>\left(r-\hat{H}<br><br>s\right)<br><br>}^2\\ =\underset{s}{\min }<br><br>{<br><br>W_{\mathrm{HD}}<br><br>\left\{\hat{H}<br><br>\left(s_{\mathrm{ML}}-s\right)+\hat{G}<br><br>i+n\right\}<br><br>}^2\end{array}& \end{array}$

where ŝ

_Prop denotes a symbol selected using ML detection by considering the interference cancellation, W_HD denotes the first weight for nulling the interference signal in the ML detection, r denotes a receive signal vector, Ĥ

denotes a channel matrix estimated using the signal received at the receiver from the serving BS, Ĝ

denotes a channel matrix estimated for the interference signal, s_ML denotes a signal vector transmitted from the serving BS to the receiver, s denotes one or more candidate symbols applied to the ML detection, i denotes an interference signal vector, and n denotes a noise vector.

8. The method of claim 1, further comprising:

after detecting the candidate symbol, determining whether to perform soft decoding using the second weight in consideration of interference influence on a reception performance,

wherein, when determining to perform the soft decoding using the second weight, the candidate symbol is soft-decoded using the second weight.

9. The method of claim 8, wherein the determining of whether to perform the soft decoding using the second weight comprises:

comparing a first noise power generated when the soft-decoding is conducted without using the second weight, with a second noise power generated when the soft decoding is conducted using the second weight; and

determining to perform the soft decoding using the second weight when a great influence of the interference is determined by comparing the first noise power and the second noise power.

10. The method of claim 8, wherein the determining of whether to perform the soft decoding using the second weight comprises:

determining a Signal to Interference Ratio (SIR); and

when determining a greater influence of the interference signal based on the SIR, determining to conduct the soft decoding using the second weight.

11. The method of claim 8, further comprising:

when determining not to use the second weight, soft-decoding the candidate symbol without using the second weight.

12. An apparatus for a receiver in a multi-antenna system, comprising:

one or more receive antennas;

a channel estimator for estimating a channel using a signal received via the antennas;

a weight generator for generating one or more weights using the estimated channel to cancel interference;

a Maximum Likelihood (ML) detector for detecting a candidate symbol having the shortest Euclidean distance through ML using a first weight; and

a decoder for decoding the candidate symbol using a second weight.

13. The apparatus of claim 12, wherein the weight generator generates the first weight and the second weight having the same value or different values.

14. The apparatus of claim 12, wherein, when the candidate symbol detected at the receiver is the same as a symbol transmitted from a serving base station (BS), the weight generator generates the first weight which minimizes a Euclidean distance of a channel to the serving base station and a Euclidean distance of a channel of at least one interference signal.

15. The apparatus of claim 12, wherein the weight generator generates the second weight which minimizes a Euclidean distance of a channel to a serving base station and a Euclidean distance of a channel of at least one interference signal with respect to all of candidate symbols applicable to the ML at the receiver.

16. The apparatus of claim 12, wherein the weight generator, when not able to estimate a channel of an interference signal, generates one or more weights for the interference cancellation using the estimated channel and a correlation value of the receive signal and the interference signal.

17. The apparatus of claim 12, wherein the weight generator generates one or more weights for the interference cancellation using any one of Zero Forcing (ZF) and Minimum Mean Squared Error (MMSE).

18. The apparatus of claim 12, wherein the ML detector selects a candidate symbol having the shortest Euclidean distance calculated by nulling an interference signal using the first weight based on the following equation:

$\begin{array}{c}{\hat{s}}_{\mathrm{Prop}}=\underset{s}{\min }<br><br>{<br><br>W_{\mathrm{HD}}<br><br>\left(r-\hat{H}<br><br>s\right)<br><br>}^2\\ =\underset{s}{\min }<br><br>{<br><br>W_{\mathrm{HD}}<br><br>\left\{\hat{H}<br><br>\left(s_{\mathrm{ML}}-s\right)+\hat{G}<br><br>i+n\right\}<br><br>}^2\end{array}$

where ŝ

_Prop denotes a symbol selected using ML detection by considering the interference cancellation, W_HD denotes the first weight for nulling the interference signal in the ML detection, r denotes a receive signal vector, Ĥ

denotes a channel matrix estimated for the signal received at the receiver from the serving BS, Ĝ

denotes a channel matrix estimated for the interference signal, s_ML denotes a signal vector transmitted from the serving BS to the receiver, s denotes one or more candidate symbols applied to the ML detection, i denotes an interference signal vector, and n denotes a noise vector.

19. The apparatus of claim 12, further comprising:

a soft decoding controller for determining whether to perform soft decoding using the second weight in consideration of interference influence on a reception performance,

wherein, when the soft decoding controller determines to perform the soft decoding using the second weight, the soft decoder soft-decodes the candidate symbol using the second weight.

20. The apparatus of claim 19, wherein the soft decoding controller compares a first noise power generated when the soft-decoding is conducted without using the second weight, with a second noise power generated when the soft decoding is conducted using the second weight, and determines to perform the soft decoding using the second weight when determining a great influence of the interference signal.

21. The apparatus of claim 19, wherein the soft decoding controller, when determining a greater influence of the interference signal based on the SIR, determines to conduct the soft decoding using the second weight.

22. The apparatus of claim 19, wherein, when the soft decoding controller determines not to use the second weight, the soft decoder soft-decodes the candidate symbol without using the second weight.