IP Library Granted Patent US 8,873,684
Granted Patent B2
US 8,873,684 · App. 14/104,543 · Granted Oct 28, 2014

BICM decoding in the presence of co-channel interference

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Quick Facts
Patent No.
US 8,873,684
App. No.
14/104,543
Granted
Oct 28, 2014
Kind
B2
Abstract

Systems and methods are provided for computing soft information for digital information based on a received signal, where the received signal suffers from noise and interference. A receiver that decodes the received signal may estimate channel information, such as the channel gain, associated with the interfering source. The receiver may also obtain modulation information through a backbone network or by decoding control information transmitted by the interfering source. Using the modulation information and the channel information, the receiver may estimate the effect that interference has on the received signal, and may compute soft information (e.g., a log-likelihood ratio) for the digital information.

Claims (590)

1. A method of computing soft information for use in estimating digital information from an intended source, the method comprising:

estimating interference channel information associated with at least one interfering source;

estimating intended channel information associated with the intended source;

determining intended modulation information associated with the intended source;

receiving a signal corresponding to the digital information; and

computing soft information for the digital information from the signal based on the interference channel information, the intended channel information and the intended modulation information.

2. The method of claim 1 , further comprising:

receiving a pilot signal from a channel associated with the intended source,

wherein estimating the intended channel information comprises determining a magnitude and phase of the received pilot signal, and

wherein determining the intended modulation information comprises decoding the received pilot signal to identify a modulation scheme used by the intended source.

3. The method of claim 2 , wherein estimating the interference channel information comprises:

computing an estimate of a channel gain associated with the at least one interfering source.

4. The method of claim 3 , wherein estimating the interference channel information further comprises:

computing an estimate of at least one of an average squared magnitude of the channel gain and an instantaneous squared magnitude of the channel gain.

5. The method of claim 1 , wherein estimating the interference channel information comprises:

receiving a pilot signal from a channel associated with the at least one interfering source;

analyzing a pseudo-noise (PN) sequence associated with the pilot signal to determine that the pilot signal was transmitted by the at least one interfering source; and

determining a magnitude and phase of the received pilot signal.

6. The method of claim 1 further comprising determining interference modulation information associated with the at least one interfering source, wherein determining the interference modulation information comprises:

receiving a pilot signal from a channel associated with the at least one interfering source;

analyzing a pseudo-noise (PN) sequence associated with the pilot signal to determine that the pilot signal was transmitted by the at least one interfering source; and

decoding the pilot signal to identify a modulation scheme used by the at least one interfering source.

7. The method of claim 1 , wherein the signal corresponding to the digital information is received in accordance with a communication protocol, the method further comprising determining a number of interfering sources based on at least one of a number of frequency channels and a frequency reuse of the communications protocol.

8. The method of claim 1 , wherein computing soft information comprises computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

log

(

x

X

l

i

(

1

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

-

g

k

i

s

2

σ

z

2

)

)

-

log

(

x

X

l

i

(

0

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

-

g

k

i

s

2

σ

z

2

)

)

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, g is an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k i is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

9. The method of claim 1 , wherein computing soft information comprises computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

1

σ

z

2

[

min

x

X

l

i

(

0

)

,

s

S

{

y

k

i

-

h

k

i

x

-

g

k

i

s

2

}

-

min

x

X

l

i

(

1

)

,

s

S

{

y

k

i

-

h

k

i

x

-

g

k

i

s

2

}

]

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, g is an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k i is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

10. The method of claim 1 , wherein computing soft information comprises computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

log

(

x

X

l

i

(

1

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

2

σ

z

2

+

σ

g

2

s

2

)

)

-

log

(

x

X

l

i

(

0

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

2

σ

z

2

+

σ

g

2

s

2

)

)

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, σ g 2 is an average magnitude square of an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k i is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

11. A system for computing soft information for use in estimating digital information from an intended source, the system comprising:

computational logic circuitry to:

estimate interference channel information associated with at least one interfering source;

estimate intended channel information associated with the intended source;

determine intended modulation information associated with the intended source;

an input interface to receive a signal corresponding to the digital information; and

a soft bit-metric calculator to compute soft information for the digital information from the signal based on the interference channel information, the intended channel information and the intended modulation information.

12. The system of claim 11 , wherein the computational logic is further configured to:

estimate the intended channel information by determining a magnitude and phase of a pilot signal received from a channel associated with the intended source; and

determine the intended modulation information by decoding the received pilot signal to identify a modulation scheme used by the intended source.

13. The system of claim 12 , wherein the computational logic estimates the interference channel information by:

computing an estimate of a channel gain associated with the at least one interfering source.

14. The system of claim 13 , wherein the computational logic estimates the interference channel information by:

computing an estimate of at least one of an average squared magnitude of the channel gain and an instantaneous squared magnitude of the channel gain.

15. The system of claim 11 , wherein the computational logic estimates the interference channel information by:

analyzing a pseudo-noise (PN) sequence associated with a pilot signal received from a channel associated with the at least one interfering source to determine that the pilot signal was transmitted by the at least one interfering source; and

determining a magnitude and phase of the received pilot signal.

16. The system of claim 11 , wherein the computational logic determines interference modulation information associated with the at least one interfering source by:

analyzing a pseudo-noise (PN) sequence associated with a pilot signal received from a channel associated with the at least one interfering source to determine that the pilot signal was transmitted by the at least one interfering source; and

decoding the pilot signal to identify a modulation scheme used by the at least one interfering source.

17. The system of claim 11 , wherein the signal corresponding to the digital information is received in accordance with a communication protocol, and wherein the computational logic determines a number of interfering sources based on at least one of a number of frequency channels and a frequency reuse of the communications protocol.

18. The system of claim 11 , wherein the soft bit-metric calculator computes soft information by computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

log

(

x

X

l

i

(

1

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

-

g

k

i

s

2

σ

z

2

)

)

-

log

(

x

X

l

i

(

0

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

-

g

k

i

s

2

σ

z

2

)

)

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, g is an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k l is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

19. The system of claim 11 , wherein the soft bit-metric calculator computes soft information by computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

1

σ

z

2

[

min

x

X

l

i

(

0

)

,

s

S

{

y

k

i

-

h

k

i

x

-

g

k

i

s

2

}

-

min

x

X

l

i

(

1

)

,

s

S

{

y

k

i

-

h

k

i

x

-

g

k

i

s

2

}

]

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, g is an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k l is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

20. The system of claim 11 , wherein the soft bit-metric calculator computes soft information by computing a log-likelihood ratio (LLR) for an ith bit in the digital information according to:

LLR

i

=

log

(

x

X

l

i

(

1

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

2

σ

z

2

+

σ

g

2

s

2

)

)

-

log

(

x

X

l

i

(

0

)

,

s

S

exp

(

-

y

k

i

-

h

k

i

x

2

σ

z

2

+

σ

g

2

s

2

)

)

,

where i is an integer, y is the received signal, h is an intended channel gain associated with the intended source, σ g 2 is an average magnitude square of an interference channel gain associated with the at least one interfering source, x is at least a portion of the digital information, l i is a bit position of the ith bit, k i is a sampling time of the ith bit, s is an interference signal from the at least one interfering source, and σ z 2 is a power of noise.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 18, 2019
From: MARVELL INTERNATIONAL LTD.
To: NXP USA, INC.
Reel/Frame 051536/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 27, 2019
From: MARVELL WORLD TRADE LTD.
To: MARVELL INTERNATIONAL LTD.
Reel/Frame 050575/0703 →